Most-cited articles · 2023
The 50 most-cited articles in Nucleic Acids Research, 2023
Ranked by OpenAlex citation count on 29 October 2026, out of 1,212 eligible articles Nucleic Acids Research published in 2023. Ranks are frozen; this page will not change. Number one, with 2,321 citations: antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structures and visualisation.
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- 1top 0.1%
antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structures and visualisation
Kai Blin, Simon Shaw, Hannah E. Augustijn, Zachary L. Reitz, Friederike Biermann and 8 more
2,321 citationsOpen access (CC-BY)doi:10.1093/nar/gkad344OpenAlex
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Microorganisms produce small bioactive compounds as part of their secondary or specialised metabolism. Often, such metabolites have antimicrobial, anticancer, antifungal, antiviral or other bio-activities and thus play an important role for applications in medicine and agriculture. In the past decade, genome mining has become a widely-used method to explore, access, and analyse the available biodiversity of these compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' (https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free to use web server and as a standalone tool under an OSI-approved open source licence. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in archaea, bacteria, and fungi. Here, we present the updated version 7 of antiSMASH. antiSMASH 7 increases the number of supported cluster types from 71 to 81, as well as containing improvements in the areas of chemical structure prediction, enzymatic assembly-line…
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AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences
Mihály Váradi, Damian Bertoni, Paulyna Magaña, Urmila Paramval, Ivanna Pidruchna and 18 more
2,046 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1011OpenAlex
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The AlphaFold Database Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) has significantly impacted structural biology by amassing over 214 million predicted protein structures, expanding from the initial 300k structures released in 2021. Enabled by the groundbreaking AlphaFold2 artificial intelligence (AI) system, the predictions archived in AlphaFold DB have been integrated into primary data resources such as PDB, UniProt, Ensembl, InterPro and MobiDB. Our manuscript details subsequent enhancements in data archiving, covering successive releases encompassing model organisms, global health proteomes, Swiss-Prot integration, and a host of curated protein datasets. We detail the data access mechanisms of AlphaFold DB, from direct file access via FTP to advanced queries using Google Cloud Public Datasets and the programmatic access endpoints of the database. We also discuss the improvements and services added since its initial release, including enhancements to the Predicted Aligned Error viewer, customisation options for the 3D viewer, and improvements in the…
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Proksee: in-depth characterization and visualization of bacterial genomes
Jason R Grant, Eric Enns, Eric Marinier, Arnab Mandal, Emily K. Herman and 4 more
1,907 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad326OpenAlex
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Proksee (https://proksee.ca) provides users with a powerful, easy-to-use, and feature-rich system for assembling, annotating, analysing, and visualizing bacterial genomes. Proksee accepts Illumina sequence reads as compressed FASTQ files or pre-assembled contigs in raw, FASTA, or GenBank format. Alternatively, users can supply a GenBank accession or a previously generated Proksee map in JSON format. Proksee then performs assembly (for raw sequence data), generates a graphical map, and provides an interface for customizing the map and launching further analysis jobs. Notable features of Proksee include unique and informative assembly metrics provided via a custom reference database of assemblies; a deeply integrated high-performance genome browser for viewing and comparing analysis results at individual base resolution (developed specifically for Proksee); an ever-growing list of embedded analysis tools whose results can be seamlessly added to the map or searched and explored in other formats; and the option to export graphical maps, analysis results, and log files for data sharing…
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DrugBank 6.0: the DrugBank Knowledgebase for 2024
Craig Knox, Mike Wilson, Christen M. Klinger, Mark Franklin, Eponine Oler and 25 more
1,770 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad976OpenAlex
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First released in 2006, DrugBank (https://go.drugbank.com) has grown to become the 'gold standard' knowledge resource for drug, drug-target and related pharmaceutical information. DrugBank is widely used across many diverse biomedical research and clinical applications, and averages more than 30 million views/year. Since its last update in 2018, we have been actively enhancing the quantity and quality of the drug data in this knowledgebase. In this latest release (DrugBank 6.0), the number of FDA approved drugs has grown from 2646 to 4563 (a 72% increase), the number of investigational drugs has grown from 3394 to 6231 (a 38% increase), the number of drug-drug interactions increased from 365 984 to 1 413 413 (a 300% increase), and the number of drug-food interactions expanded from 1195 to 2475 (a 200% increase). In addition to this notable expansion in database size, we have added thousands of new, colorful, richly annotated pathways depicting drug mechanisms and drug metabolism. Likewise, existing datasets have been significantly improved and expanded, by adding more information on…
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g:Profiler—interoperable web service for functional enrichment analysis and gene identifier mapping (2023 update)
Liis Kolberg, Uku Raudvere, Ivan Kuzmin, Priit Adler, Jaak Vilo and 1 more
1,688 citationsOpen access (CC-BY)doi:10.1093/nar/gkad347OpenAlex
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g:Profiler is a reliable and up-to-date functional enrichment analysis tool that supports various evidence types, identifier types and organisms. The toolset integrates many databases, including Gene Ontology, KEGG and TRANSFAC, to provide a comprehensive and in-depth analysis of gene lists. It also provides interactive and intuitive user interfaces and supports ordered queries and custom statistical backgrounds, among other settings. g:Profiler provides multiple programmatic interfaces to access its functionality. These can be easily integrated into custom workflows and external tools, making them valuable resources for researchers who want to develop their own solutions. g:Profiler has been available since 2007 and is used to analyse millions of queries. Research reproducibility and transparency are achieved by maintaining working versions of all past database releases since 2015. g:Profiler supports 849 species, including vertebrates, plants, fungi, insects and parasites, and can analyse any organism through user-uploaded custom annotation files. In this update article, we…
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The Reactome Pathway Knowledgebase 2024
Marija Orlic-Milacic, Deidre Beavers, Patrick Conley, Chuqiao Gong, Marc E. Gillespie and 19 more
1,509 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1025OpenAlex
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The Reactome Knowledgebase (https://reactome.org), an Elixir and GCBR core biological data resource, provides manually curated molecular details of a broad range of normal and disease-related biological processes. Processes are annotated as an ordered network of molecular transformations in a single consistent data model. Reactome thus functions both as a digital archive of manually curated human biological processes and as a tool for discovering functional relationships in data such as gene expression profiles or somatic mutation catalogs from tumor cells. Here we review progress towards annotation of the entire human proteome, targeted annotation of disease-causing genetic variants of proteins and of small-molecule drugs in a pathway context, and towards supporting explicit annotation of cell- and tissue-specific pathways. Finally, we briefly discuss issues involved in making Reactome more fully interoperable with other related resources such as the Gene Ontology and maintaining the resulting community resource network.
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The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods
Barbara Zdrazil, Eloy Félix, Fiona M. I. Hunter, Emma Jayne Manners, James Blackshaw and 15 more
1,453 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1004OpenAlex
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ChEMBL (https://www.ebi.ac.uk/chembl/) is a manually curated, high-quality, large-scale, open, FAIR and Global Core Biodata Resource of bioactive molecules with drug-like properties, previously described in the 2012, 2014, 2017 and 2019 Nucleic Acids Research Database Issues. Since its introduction in 2009, ChEMBL's content has changed dramatically in size and diversity of data types. Through incorporation of multiple new datasets from depositors since the 2019 update, ChEMBL now contains slightly more bioactivity data from deposited data vs data extracted from literature. In collaboration with the EUbOPEN consortium, chemical probe data is now regularly deposited into ChEMBL. Release 27 made curated data available for compounds screened for potential anti-SARS-CoV-2 activity from several large-scale drug repurposing screens. In addition, new patent bioactivity data have been added to the latest ChEMBL releases, and various new features have been incorporated, including a Natural Product likeness score, updated flags for Natural Products, a new flag for Chemical Probes, and the…
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Tree Visualization By One Table (tvBOT): a web application for visualizing, modifying and annotating phylogenetic trees
Jianmin Xie, Yuerong Chen, Guanjing Cai, Runlin Cai, Zhong Hu and 1 more
1,376 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad359OpenAlex
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tvBOT is a user-friendly and efficient web application for visualizing, modifying, and annotating phylogenetic trees. It is highly efficient in data preparation without requiring redundant style and syntax data. Tree annotations are powered by a data-driven engine that only requires practical data organized in uniform formats and saved as one table file. A layer manager is developed to manage annotation dataset layers, allowing the addition of a specific layer by selecting the columns of a corresponding annotation data file. Furthermore, tvBOT renders style adjustments in real-time and diversified ways. All style adjustments can be made on a highly interactive user interface and are available for mobile devices. The display engine allows the changes to be updated and rendered in real-time. In addition, tvBOT supports the combination display of 26 annotation dataset types to achieve multiple formats for tree annotations with reusable phylogenetic data. Besides several publication-ready graphics formats, JSON format can be exported to save the final drawing state and all related data,…
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JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles
Ieva Rauluševičiūtė, Rafael Riudavets Puig, Romain Blanc‐Mathieu, Jaime Abraham Castro-Mondragon, Katalin Ferenc and 15 more
1,120 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1059OpenAlex
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JASPAR (https://jaspar.elixir.no/) is a widely-used open-access database presenting manually curated high-quality and non-redundant DNA-binding profiles for transcription factors (TFs) across taxa. In this 10th release and 20th-anniversary update, the CORE collection has expanded with 329 new profiles. We updated three existing profiles and provided orthogonal support for 72 profiles from the previous release's UNVALIDATED collection. Altogether, the JASPAR 2024 update provides a 20% increase in CORE profiles from the previous release. A trimming algorithm enhanced profiles by removing low information content flanking base pairs, which were likely uninformative (within the capacity of the PFM models) for TFBS predictions and modelling TF-DNA interactions. This release includes enhanced metadata, featuring a refined classification for plant TFs' structural DNA-binding domains. The new JASPAR collections prompt updates to the genomic tracks of predicted TF binding sites (TFBSs) in 8 organisms, with human and mouse tracks available as native tracks in the UCSC Genome browser. All data…
- 10top 0.9%
dbCAN3: automated carbohydrate-active enzyme and substrate annotation
Jinfang Zheng, Qiwei Ge, Yuchen Yan, Xinpeng Zhang, Le Huang and 1 more
1,100 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad328OpenAlex
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Carbohydrate active enzymes (CAZymes) are made by various organisms for complex carbohydrate metabolism. Genome mining of CAZymes has become a routine data analysis in (meta-)genome projects, owing to the importance of CAZymes in bioenergy, microbiome, nutrition, agriculture, and global carbon recycling. In 2012, dbCAN was provided as an online web server for automated CAZyme annotation. dbCAN2 (https://bcb.unl.edu/dbCAN2) was further developed in 2018 as a meta server to combine multiple tools for improved CAZyme annotation. dbCAN2 also included CGC-Finder, a tool for identifying CAZyme gene clusters (CGCs) in (meta-)genomes. We have updated the meta server to dbCAN3 with the following new functions and components: (i) dbCAN-sub as a profile Hidden Markov Model database (HMMdb) for substrate prediction at the CAZyme subfamily level; (ii) searching against experimentally characterized polysaccharide utilization loci (PULs) with known glycan substates of the dbCAN-PUL database for substrate prediction at the CGC level; (iii) a majority voting method to consider all CAZymes with…
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Chemistry, structure and function of approved oligonucleotide therapeutics
Martin Egli, Muthiah Manoharan
844 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad067OpenAlex
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Eighteen nucleic acid therapeutics have been approved for treatment of various diseases in the last 25 years. Their modes of action include antisense oligonucleotides (ASOs), splice-switching oligonucleotides (SSOs), RNA interference (RNAi) and an RNA aptamer against a protein. Among the diseases targeted by this new class of drugs are homozygous familial hypercholesterolemia, spinal muscular atrophy, Duchenne muscular dystrophy, hereditary transthyretin-mediated amyloidosis, familial chylomicronemia syndrome, acute hepatic porphyria, and primary hyperoxaluria. Chemical modification of DNA and RNA was central to making drugs out of oligonucleotides. Oligonucleotide therapeutics brought to market thus far contain just a handful of first- and second-generation modifications, among them 2'-fluoro-RNA, 2'-O-methyl RNA and the phosphorothioates that were introduced over 50 years ago. Two other privileged chemistries are 2'-O-(2-methoxyethyl)-RNA (MOE) and the phosphorodiamidate morpholinos (PMO). Given their importance in imparting oligonucleotides with high target affinity, metabolic…
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The UNITE database for molecular identification and taxonomic communication of fungi and other eukaryotes: sequences, taxa and classifications reconsidered
Kessy Abarenkov, R. Henrik Nilsson, Karl‐Henrik Larsson, Andy F. S. Taylor, Tom W. May and 25 more
841 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1039OpenAlex
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UNITE (https://unite.ut.ee) is a web-based database and sequence management environment for molecular identification of eukaryotes. It targets the nuclear ribosomal internal transcribed spacer (ITS) region and offers nearly 10 million such sequences for reference. These are clustered into ∼2.4M species hypotheses (SHs), each assigned a unique digital object identifier (DOI) to promote unambiguous referencing across studies. UNITE users have contributed over 600 000 third-party sequence annotations, which are shared with a range of databases and other community resources. Recent improvements facilitate the detection of cross-kingdom biological associations and the integration of undescribed groups of organisms into everyday biological pursuits. Serving as a digital twin for eukaryotic biodiversity and communities worldwide, the latest release of UNITE offers improved avenues for biodiversity discovery, precise taxonomic communication and integration of biological knowledge across platforms.
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Ensembl 2024
Peter W. Harrison, M Ridwan Amode, Olanrewaju Austine-Orimoloye, Andrey G Azov, Matthieu Barba and 25 more
741 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1049OpenAlex
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Ensembl (https://www.ensembl.org) is a freely available genomic resource that has produced high-quality annotations, tools, and services for vertebrates and model organisms for more than two decades. In recent years, there has been a dramatic shift in the genomic landscape, with a large increase in the number and phylogenetic breadth of high-quality reference genomes, alongside major advances in the pan-genome representations of higher species. In order to support these efforts and accelerate downstream research, Ensembl continues to focus on scaling for the rapid annotation of new genome assemblies, developing new methods for comparative analysis, and expanding the depth and quality of our genome annotations. This year we have continued our expansion to support global biodiversity research, doubling the number of annotated genomes we support on our Rapid Release site to over 1700, driven by our close collaboration with biodiversity projects such as Darwin Tree of Life. We have also strengthened support for key agricultural species, including the first regulatory builds for farmed…
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PHASTEST: faster than PHASTER, better than PHAST
David Scott Wishart, Scott Han, Sukanta Saha, Eponine Oler, Harrison Peters and 3 more
659 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad382OpenAlex
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PHASTEST (PHAge Search Tool with Enhanced Sequence Translation) is the successor to the PHAST and PHASTER prophage finding web servers. PHASTEST is designed to support the rapid identification, annotation and visualization of prophage sequences within bacterial genomes and plasmids. PHASTEST also supports rapid annotation and interactive visualization of all other genes (protein coding regions, tRNA/tmRNA/rRNA sequences) in bacterial genomes. Given that bacterial genome sequencing has become so routine, the need for fast tools to comprehensively annotate bacterial genomes has become progressively more important. PHASTEST not only offers faster and more accurate prophage annotations than its predecessors, it also provides more complete whole genome annotations and much improved genome visualization capabilities. In standardized tests, we found that PHASTEST is 31% faster and 2-3% more accurate in prophage identification than PHASTER. Specifically, PHASTEST can process a typical bacterial genome in 3.2 min (raw sequence) or in 1.3 min when given a pre-annotated GenBank file.…
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TTD: Therapeutic Target Database describing target druggability information
Ying Zhou, Yintao Zhang, Donghai Zhao, Xinyuan Yu, Xinyi Shen and 5 more
657 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad751OpenAlex
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Target discovery is one of the essential steps in modern drug development, and the identification of promising targets is fundamental for developing first-in-class drug. A variety of methods have emerged for target assessment based on druggability analysis, which refers to the likelihood of a target being effectively modulated by drug-like agents. In the therapeutic target database (TTD), nine categories of established druggability characteristics were thus collected for 426 successful, 1014 clinical trial, 212 preclinical/patented, and 1479 literature-reported targets via systematic review. These characteristic categories were classified into three distinct perspectives: molecular interaction/regulation, human system profile and cell-based expression variation. With the rapid progression of technology and concerted effort in drug discovery, TTD and other databases were highly expected to facilitate the explorations of druggability characteristics for the discovery and validation of innovative drug target. TTD is now freely accessible at: https://idrblab.org/ttd/.
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MicrobiomeAnalyst 2.0: comprehensive statistical, functional and integrative analysis of microbiome data
Yao Ping Lu, Guangyan Zhou, Jessica Ewald, Zhiqiang Pang, Tanisha Jean Shiri and 1 more
630 citationsOpen access (CC-BY)doi:10.1093/nar/gkad407OpenAlex
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Microbiome studies have become routine in biomedical, agricultural and environmental sciences with diverse aims, including diversity profiling, functional characterization, and translational applications. The resulting complex, often multi-omics datasets demand powerful, yet user-friendly bioinformatics tools to reveal key patterns, important biomarkers, and potential activities. Here we introduce MicrobiomeAnalyst 2.0 to support comprehensive statistics, visualization, functional interpretation, and integrative analysis of data outputs commonly generated from microbiome studies. Compared to the previous version, MicrobiomeAnalyst 2.0 features three new modules: (i) a Raw Data Processing module for amplicon data processing and taxonomy annotation that connects directly with the Marker Data Profiling module for downstream statistical analysis; (ii) a Microbiome Metabolomics Profiling module to help dissect associations between community compositions and metabolic activities through joint analysis of paired microbiome and metabolomics datasets; and (iii) a Statistical Meta-Analysis…
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COSMIC: a curated database of somatic variants and clinical data for cancer
Zbysław Sońdka, Nidhi Bindal, Denise Carvalho‐Silva, S Jupe, Madhumita and 24 more
542 citationsOpen access (CC-BY)doi:10.1093/nar/gkad986OpenAlex
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The Catalogue Of Somatic Mutations In Cancer (COSMIC), https://cancer.sanger.ac.uk/cosmic, is an expert-curated knowledgebase providing data on somatic variants in cancer, supported by a comprehensive suite of tools for interpreting genomic data, discerning the impact of somatic alterations on disease, and facilitating translational research. The catalogue is accessed and used by thousands of cancer researchers and clinicians daily, allowing them to quickly access information from an immense pool of data curated from over 29 thousand scientific publications and large studies. Within the last 4 years, COSMIC has substantially expanded its utility by adding new resources: the Mutational Signatures catalogue, the Cancer Mutation Census, and Actionability. To improve data accessibility and interoperability, somatic variants have received stable genomic identifiers that are associated with their genomic coordinates in GRCh37 and GRCh38, and new export files with reduced data redundancy have been made available for download.
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OrthoVenn3: an integrated platform for exploring and visualizing orthologous data across genomes
Jiahe Sun, Fang Lü, Yongjiang Luo, Lingzi Bie, Ling Xu and 1 more
534 citationsOpen access (CC-BY)doi:10.1093/nar/gkad313OpenAlex
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Advancements in comparative genomics research have led to a growing interest in studying species evolution and genetic diversity. To facilitate this research, OrthoVenn3 has been developed as a powerful, web-based tool that enables users to efficiently identify and annotate orthologous clusters and infer phylogenetic relationships across a range of species. The latest upgrade of OrthoVenn includes several important new features, including enhanced orthologous cluster identification accuracy, improved visualization capabilities for numerous sets of data, and wrapped phylogenetic analysis. Furthermore, OrthoVenn3 now provides gene family contraction and expansion analysis to support researchers better understanding the evolutionary history of gene families, as well as collinearity analysis to detect conserved and variable genomic structures. With its intuitive user interface and robust functionality, OrthoVenn3 is a valuable resource for comparative genomics research. The tool is freely accessible at https://orthovenn3.bioinfotoolkits.net.
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DGIdb 5.0: rebuilding the drug–gene interaction database for precision medicine and drug discovery platforms
Matthew J. Cannon, James Stevenson, Kathryn Stahl, Rohit Basu, Adam C. Coffman and 9 more
531 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1040OpenAlex
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The Drug-Gene Interaction Database (DGIdb, https://dgidb.org) is a publicly accessible resource that aggregates genes or gene products, drugs and drug-gene interaction records to drive hypothesis generation and discovery for clinicians and researchers. DGIdb 5.0 is the latest release and includes substantial architectural and functional updates to support integration into clinical and drug discovery pipelines. The DGIdb service architecture has been split into separate client and server applications, enabling consistent data access for users of both the application programming interface (API) and web interface. The new interface was developed in ReactJS, and includes dynamic visualizations and consistency in the display of user interface elements. A GraphQL API has been added to support customizable queries for all drugs, genes, annotations and associated data. Updated documentation provides users with example queries and detailed usage instructions for these new features. In addition, six sources have been added and many existing sources have been updated. Newly added sources…
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NCBI GEO: archive for gene expression and epigenomics data sets: 23-year update
Emily Clough, Tanya Barrett, Stephen E. Wilhite, Pierre Ledoux, Carlos C. Evangelista and 12 more
521 citationsOpen access (PUBLIC-DOMAIN)doi:10.1093/nar/gkad965OpenAlex
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The Gene Expression Omnibus (GEO) is an international public repository that archives gene expression and epigenomics data sets generated by next-generation sequencing and microarray technologies. Data are typically submitted to GEO by researchers in compliance with widespread journal and funder mandates to make generated data publicly accessible. The resource handles raw data files, processed data files and descriptive metadata for over 200 000 studies and 6.5 million samples, all of which are indexed, searchable and downloadable. Additionally, GEO offers web-based tools that facilitate analysis and visualization of differential gene expression. This article presents the current status and recent advancements in GEO, including the generation of consistently computed gene expression count matrices for thousands of RNA-seq studies, and new interactive graphical plots in GEO2R that help users identify differentially expressed genes and assess data set quality. The GEO repository is built and maintained by the National Center for Biotechnology Information (NCBI), a division of the…
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WikiPathways 2024: next generation pathway database
Ayushi Agrawal, Hasan Balcı, Kristina Hanspers, Susan L. Coort, Marvin Martens and 17 more
472 citationsOpen access (CC-BY)doi:10.1093/nar/gkad960OpenAlex
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WikiPathways (wikipathways.org) is an open-source biological pathway database. Collaboration and open science are pivotal to the success of WikiPathways. Here we highlight the continuing efforts supporting WikiPathways, content growth and collaboration among pathway researchers. As an evolving database, there is a growing need for WikiPathways to address and overcome technical challenges. In this direction, WikiPathways has undergone major restructuring, enabling a renewed approach for sharing and curating pathway knowledge, thus providing stability for the future of community pathway curation. The website has been redesigned to improve and enhance user experience. This next generation of WikiPathways continues to support existing features while improving maintainability of the database and facilitating community input by providing new functionality and leveraging automation.
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CADD v1.7: using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions
Max Schubach, Thorben Maaß, Lusiné Nazaretyan, Sebastian Röner, Martin Kircher
453 citationsOpen access (CC-BY)doi:10.1093/nar/gkad989OpenAlex
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Machine Learning-based scoring and classification of genetic variants aids the assessment of clinical findings and is employed to prioritize variants in diverse genetic studies and analyses. Combined Annotation-Dependent Depletion (CADD) is one of the first methods for the genome-wide prioritization of variants across different molecular functions and has been continuously developed and improved since its original publication. Here, we present our most recent release, CADD v1.7. We explored and integrated new annotation features, among them state-of-the-art protein language model scores (Meta ESM-1v), regulatory variant effect predictions (from sequence-based convolutional neural networks) and sequence conservation scores (Zoonomia). We evaluated the new version on data sets derived from ClinVar, ExAC/gnomAD and 1000 Genomes variants. For coding effects, we tested CADD on 31 Deep Mutational Scanning (DMS) data sets from ProteinGym and, for regulatory effect prediction, we used saturation mutagenesis reporter assay data of promoter and enhancer sequences. The inclusion of new…
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MODOMICS: a database of RNA modifications and related information. 2023 update
Andrea Cappannini, Angana Ray, Elżbieta Purta, Sunandan Mukherjee, Pietro Boccaletto and 6 more
411 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1083OpenAlex
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The MODOMICS database was updated with recent data and now includes new data types related to RNA modifications. Changes to the database include an expanded modification catalog, encompassing both natural and synthetic residues identified in RNA structures. This addition aids in representing RNA sequences from the RCSB PDB database more effectively. To manage the increased number of modifications, adjustments to the nomenclature system were made. Updates in the RNA sequences section include the addition of new sequences and the reintroduction of sequence alignments for tRNAs and rRNAs. The protein section was updated and connected to structures from the RCSB PDB database and predictions by AlphaFold. MODOMICS now includes a data annotation system, with 'Evidence' and 'Estimated Reliability' features, offering clarity on data support and accuracy. This system is open to all MODOMICS entries, enhancing the accuracy of RNA modification data representation. MODOMICS is available at https://iimcb.genesilico.pl/modomics/.
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The Human Phenotype Ontology in 2024: phenotypes around the world
Michael A. Gargano, Nicolas Matentzoglu, Ben D Coleman, Eunice B Addo-Lartey, Anna V. Anagnostopoulos and 25 more
410 citationsOpen access (OTHER-OA)doi:10.1093/nar/gkad1005OpenAlex
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The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium…
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MetaboLights: open data repository for metabolomics
Ozgur Yurekten, Thomas Payne, Noemı́ Tejera, Felix Xavier Amaladoss, Callum D. Martin and 2 more
405 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1045OpenAlex
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MetaboLights is a global database for metabolomics studies including the raw experimental data and the associated metadata. The database is cross-species and cross-technique and covers metabolite structures and their reference spectra as well as their biological roles and locations where available. MetaboLights is the recommended metabolomics repository for a number of leading journals and ELIXIR, the European infrastructure for life science information. In this article, we describe the continued growth and diversity of submissions and the significant developments in recent years. In particular, we highlight MetaboLights Labs, our new Galaxy Project instance with repository-scale standardized workflows, and how data public on MetaboLights are being reused by the community. Metabolomics resources and data are available under the EMBL-EBI's Terms of Use at https://www.ebi.ac.uk/metabolights and under Apache 2.0 at https://github.com/EBI-Metabolights.
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Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities
Sophia Müller‐Dott, Eirini Tsirvouli, Miguél Vázquez, Ricardo O. Ramirez Flores, Pau Badia-i-Mompel and 4 more
391 citationsOpen access (CC-BY)doi:10.1093/nar/gkad841OpenAlex
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Gene regulation plays a critical role in the cellular processes that underlie human health and disease. The regulatory relationship between transcription factors (TFs), key regulators of gene expression, and their target genes, the so called TF regulons, can be coupled with computational algorithms to estimate the activity of TFs. However, to interpret these findings accurately, regulons of high reliability and coverage are needed. In this study, we present and evaluate a collection of regulons created using the CollecTRI meta-resource containing signed TF-gene interactions for 1186 TFs. In this context, we introduce a workflow to integrate information from multiple resources and assign the sign of regulation to TF-gene interactions that could be applied to other comprehensive knowledge bases. We find that the signed CollecTRI-derived regulons outperform other public collections of regulatory interactions in accurately inferring changes in TF activities in perturbation experiments. Furthermore, we showcase the value of the regulons by examining TF activity profiles in three…
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Database resources of the National Center for Biotechnology Information
Eric W Sayers, Jeffrey D. Beck, Evan Bolton, James Rodney Brister, Jessica Chan and 25 more
381 citationsOpen access (PUBLIC-DOMAIN)doi:10.1093/nar/gkad1044OpenAlex
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The National Center for Biotechnology Information (NCBI) provides online information resources for biology, including the GenBank® nucleic acid sequence database and the PubMed® database of citations and abstracts published in life science journals. NCBI provides search and retrieval operations for most of these data from 35 distinct databases. The E-utilities serve as the programming interface for most of these databases. Resources receiving significant updates in the past year include PubMed, PMC, Bookshelf, SciENcv, the NIH Comparative Genomics Resource (CGR), NCBI Virus, SRA, RefSeq, foreign contamination screening tools, Taxonomy, iCn3D, ClinVar, GTR, MedGen, dbSNP, ALFA, ClinicalTrials.gov, Pathogen Detection, antimicrobial resistance resources, and PubChem. These resources can be accessed through the NCBI home page at https://www.ncbi.nlm.nih.gov.
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Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2024
CNCB-NGDC Members and Partners, Xue Lian Bai, Yīmíng Bào, Shaoqi Bei, Congfan Bu and 25 more
353 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1078OpenAlex
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The National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support the global academic and industrial communities. With the rapid accumulation of multi-omics data at an unprecedented pace, CNCB-NGDC continuously expands and updates core database resources through big data archiving, integrative analysis and value-added curation. Importantly, NGDC collaborates closely with major international databases and initiatives to ensure seamless data exchange and interoperability. Over the past year, significant efforts have been dedicated to integrating diverse omics data, synthesizing expanding knowledge, developing new resources, and upgrading major existing resources. Particularly, several database resources are newly developed for the biodiversity of protists (P10K), bacteria (NTM-DB, MPA) as well as plant (PPGR, SoyOmics, PlantPan) and disease/trait association (CROST, HervD Atlas, HALL, MACdb, BioKA, BioKA, RePoS, PGG.SV, NAFLDkb). All the resources and services are publicly accessible at…
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The UCSC Genome Browser database: 2024 update
Brian J. Raney, Galt P Barber, Anna Benet‐Pagès, Jonathan Casper, Hiram Clawson and 22 more
340 citationsOpen access (CC-BY)doi:10.1093/nar/gkad987OpenAlex
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The UCSC Genome Browser (https://genome.ucsc.edu) is a web-based genomic visualization and analysis tool that serves data to over 7,000 distinct users per day worldwide. It provides annotation data on thousands of genome assemblies, ranging from human to SARS-CoV2. This year, we have introduced new data from the Human Pangenome Reference Consortium and on viral genomes including SARS-CoV2. We have added 1,200 new genomes to our GenArk genome system, increasing the overall diversity of our genomic representation. We have added support for nine new user-contributed track hubs to our public hub system. Additionally, we have released 29 new tracks on the human genome and 11 new tracks on the mouse genome. Collectively, these new features expand both the breadth and depth of the genomic knowledge that we share publicly with users worldwide.
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LIPID MAPS: update to databases and tools for the lipidomics community
M.J. Conroy, Robert Andrews, Simon Andrews, Lauren Cockayne, Edward A. Dennis and 10 more
334 citationsOpen access (CC-BY)doi:10.1093/nar/gkad896OpenAlex
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LIPID MAPS (LIPID Metabolites and Pathways Strategy), www.lipidmaps.org, provides a systematic and standardized approach to organizing lipid structural and biochemical data. Founded 20 years ago, the LIPID MAPS nomenclature and classification has become the accepted community standard. LIPID MAPS provides databases for cataloging and identifying lipids at varying levels of characterization in addition to numerous software tools and educational resources, and became an ELIXIR-UK data resource in 2020. This paper describes the expansion of existing databases in LIPID MAPS, including richer metadata with literature provenance, taxonomic data and improved interoperability to facilitate FAIR compliance. A joint project funded by ELIXIR-UK, in collaboration with WikiPathways, curates and hosts pathway data, and annotates lipids in the context of their biochemical pathways. Updated features of the search infrastructure are described along with implementation of programmatic access via API and SPARQL. New lipid-specific databases have been developed and provision of lipidomics tools to the…
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GenBank 2024 Update
Eric W Sayers, Mark L. Cavanaugh, Karen Clark, Kim D. Pruitt, Stephen T. Sherry and 2 more
317 citationsOpen access (PUBLIC-DOMAIN)doi:10.1093/nar/gkad903OpenAlex
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GenBank® (https://www.ncbi.nlm.nih.gov/genbank/) is a comprehensive, public database that contains 25 trillion base pairs from over 3.7 billion nucleotide sequences for 557 000 formally described species. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. Recent updates include policies for including spatio-temporal metadata, clarified documentation for GenBank data processing, enhanced foreign contamination screening tools, new processes in the Submission Portal, migration of Entrez Genome and Assembly displays into NCBI Datasets, and the impending retirement of tbl2asn, replaced by table2asn.
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DDMut: predicting effects of mutations on protein stability using deep learning
Yunzhuo Zhou, Qisheng Pan, Douglas E. V. Pires, Carlos H. M. Rodrigues, David Benjamin Ascher
264 citationsOpen access (CC-BY)doi:10.1093/nar/gkad472OpenAlex
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Understanding the effects of mutations on protein stability is crucial for variant interpretation and prioritisation, protein engineering, and biotechnology. Despite significant efforts, community assessments of predictive tools have highlighted ongoing limitations, including computational time, low predictive power, and biased predictions towards destabilising mutations. To fill this gap, we developed DDMut, a fast and accurate siamese network to predict changes in Gibbs Free Energy upon single and multiple point mutations, leveraging both forward and hypothetical reverse mutations to account for model anti-symmetry. Deep learning models were built by integrating graph-based representations of the localised 3D environment, with convolutional layers and transformer encoders. This combination better captured the distance patterns between atoms by extracting both short-range and long-range interactions. DDMut achieved Pearson's correlations of up to 0.70 (RMSE: 1.37 kcal/mol) on single point mutations, and 0.70 (RMSE: 1.84 kcal/mol) on double/triple mutants, outperforming most…
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VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center in 2023
Jorge Álvarez-Jarreta, Beatrice Amos, Cristina Aurrecoechea, Saikou Y. Bah, Matthieu Barba and 25 more
253 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1003OpenAlex
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The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) is a Bioinformatics Resource Center funded by the National Institutes of Health with additional funding from the Wellcome Trust. VEuPathDB supports >600 organisms that comprise invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Since 2004, VEuPathDB has analyzed omics data from the public domain using contemporary bioinformatic workflows, including orthology predictions via OrthoMCL, and integrated the analysis results with analysis tools, visualizations, and advanced search capabilities. The unique data mining platform coupled with >3000 pre-analyzed data sets facilitates the exploration of pertinent omics data in support of hypothesis driven research. Comparisons are easily made across data sets, data types and organisms. A Galaxy workspace offers the opportunity for the analysis of private large-scale datasets and for porting to VEuPathDB for comparisons with integrated data. The MapVEu tool provides a platform…
- 34top 2.9%
Enrichr-KG: bridging enrichment analysis across multiple libraries
John Erol Evangelista, Zhuorui Xie, Giacomo B. Marino, Nhi Le Uyen Nguyen, Daniel J. B. Clarke and 1 more
236 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad393OpenAlex
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Gene and protein set enrichment analysis is a critical step in the analysis of data collected from omics experiments. Enrichr is a popular gene set enrichment analysis web-server search engine that contains hundreds of thousands of annotated gene sets. While Enrichr has been useful in providing enrichment analysis with many gene set libraries from different categories, integrating enrichment results across libraries and domains of knowledge can further hypothesis generation. To this end, Enrichr-KG is a knowledge graph database and a web-server application that combines selected gene set libraries from Enrichr for integrative enrichment analysis and visualization. The enrichment results are presented as subgraphs made of nodes and links that connect genes to their enriched terms. In addition, users of Enrichr-KG can add gene-gene links, as well as predicted genes to the subgraphs. This graphical representation of cross-library results with enriched and predicted genes can illuminate hidden associations between genes and annotated enriched terms from across datasets and resources.…
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The miRNA–target interactions: An underestimated intricacy
Caroline Diener, Andreas Keller, Eckart U. Meese
234 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1142OpenAlex
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MicroRNAs (miRNAs) play indispensable roles in posttranscriptional gene regulation. Their cellular regulatory impact is determined not solely by their sheer number, which likely amounts to >2000 individual miRNAs in human, than by the regulatory effectiveness of single miRNAs. Although, one begins to develop an understanding of the complex mechanisms underlying miRNA-target interactions (MTIs), the overall knowledge of MTI functionality is still rather patchy. In this critical review, we summarize key features of mammalian MTIs. We especially highlight latest insights on (i) the dynamic make-up of miRNA binding sites including non-canonical binding sites, (ii) the cooperativity between miRNA binding sites, (iii) the adaptivity of MTIs through sequence modifications, (iv) the bearing of intra-cellular miRNA localization changes and (v) the role of cell type and cell status specific miRNA interaction partners. The MTI biology is discussed against the background of state-of-the-art approaches with particular emphasis on experimental strategies for evaluating miRNA functionality.
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Vesiclepedia 2024: an extracellular vesicles and extracellular particles repository
Sai V. Chitti, Sriram Gummadi, Taeyoung Kang, Sanjay K. Shahi, Akbar L. Marzan and 10 more
232 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1007OpenAlex
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Vesiclepedia (http://www.microvesicles.org) is a free web-based compendium of DNA, RNA, proteins, lipids and metabolites that are detected or associated with extracellular vesicles (EVs) and extracellular particles (EPs). EVs are membranous vesicles that are secreted ubiquitously by cells from all domains of life from archaea to eukaryotes. In addition to EVs, it was reported recently that EPs like exomeres and supermeres are secreted by some mammalian cells. Both EVs and EPs contain proteins, nucleic acids, lipids and metabolites and has been proposed to be implicated in several key biological functions. Vesiclepedia catalogues proteins, DNA, RNA, lipids and metabolites from both published and unpublished studies. Currently, Vesiclepedia contains data obtained from 3533 EV studies, 50 550 RNA entries, 566 911 protein entries, 3839 lipid entries, 192 metabolite and 167 DNA entries. Quantitative data for 62 822 entries from 47 EV studies is available in Vesiclepedia. The datasets available in Vesiclepedia can be downloaded as tab-delimited files or accessible through the…
- 37top 3.1%
The IUPHAR/BPS Guide to PHARMACOLOGY in 2024
Simon D Harding, Jane F Armstrong, Elena Faccenda, Christopher Southan, S P H Alexander and 3 more
226 citationsOpen access (CC-BY)doi:10.1093/nar/gkad944OpenAlex
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The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb; https://www.guidetopharmacology.org) is an open-access, expert-curated, online database that provides succinct overviews and key references for pharmacological targets and their recommended experimental ligands. It includes over 3039 protein targets and 12 163 ligand molecules, including approved drugs, small molecules, peptides and antibodies. Here, we report recent developments to the resource and describe expansion in content over the six database releases made during the last two years. The database update section of this paper focuses on two areas relating to important global health challenges. The first, SARS-CoV-2 COVID-19, remains a major concern and we describe our efforts to expand the database to include a new family of coronavirus proteins. The second area is antimicrobial resistance, for which we have extended our coverage of antibacterials in partnership with AntibioticDB, a collaboration that has continued through support from GARDP. We discuss other areas of curation and also focus on our external links to resources such…
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PhageScope: a well-annotated bacteriophage database with automatic analyses and visualizations
Ruo Han Wang, Shuo Yang, Zhixuan Liu, Yuanzheng Zhang, Xueying Wang and 3 more
212 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad979OpenAlex
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Bacteriophages are viruses that infect bacteria or archaea. Understanding the diverse and intricate genomic architectures of phages is essential to study microbial ecosystems and develop phage therapy strategies. However, the existing phage databases are short of meticulous annotations. To this end, we propose PhageScope (https://phagescope.deepomics.org), an online phage database with comprehensive annotations. PhageScope harbors a collection of 873 718 phage sequences from various sources. Applying fifteen state-of-the-art tools to perform systematic annotations and analyses, PhageScope provides annotations on genome completeness, host range, lifestyle information, taxonomy classification, nine types of structural and functional genetic elements, and three types of comparative genomic studies for curated phages. Additionally, PhageScope incorporates automatic analyses and visualizations for curated and customized phages, serving as an efficient platform for phage study.
- 39top 3.3%
BATMAN-TCM 2.0: an enhanced integrative database for known and predicted interactions between traditional Chinese medicine ingredients and target proteins
Xiangren Kong, Chao Liu, Zuzhen Zhang, Meiqi Cheng, Zhijun Mei and 15 more
212 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad926OpenAlex
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Traditional Chinese medicine (TCM) is increasingly recognized and utilized worldwide. However, the complex ingredients of TCM and their interactions with the human body make elucidating molecular mechanisms challenging, which greatly hinders the modernization of TCM. In 2016, we developed BATMAN-TCM 1.0, which is an integrated database of TCM ingredient-target protein interaction (TTI) for pharmacology research. Here, to address the growing need for a higher coverage TTI dataset, and using omics data to screen active TCM ingredients or herbs for complex disease treatment, we updated BATMAN-TCM to version 2.0 (http://bionet.ncpsb.org.cn/batman-tcm/). Using the same protocol as version 1.0, we collected 17 068 known TTIs by manual curation (with a 62.3-fold increase), and predicted ∼2.3 million high-confidence TTIs. In addition, we incorporated three new features into the updated version: (i) it enables simultaneous exploration of the target of TCM ingredient for pharmacology research and TCM ingredients binding to target proteins for drug discovery; (ii) it has significantly expanded…
- 40top 3.4%
PAE viewer: a webserver for the interactive visualization of the predicted aligned error for multimer structure predictions and crosslinks
Christoph Elfmann, Jörg Stülke
202 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad350OpenAlex
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The development of AlphaFold for protein structure prediction has opened a new era in structural biology. This is even more the case for AlphaFold-Multimer for the prediction of protein complexes. The interpretation of these predictions has become more important than ever, but it is difficult for the non-specialist. While an evaluation of the prediction quality is provided for monomeric protein predictions by the AlphaFold Protein Structure Database, such a tool is missing for predicted complex structures. Here, we present the PAE Viewer webserver (http://www.subtiwiki.uni-goettingen.de/v4/paeViewerDemo), an online tool for the integrated visualization of predicted protein complexes using a 3D structure display combined with an interactive representation of the Predicted Aligned Error (PAE). This metric allows an estimation of the quality of the prediction. Importantly, our webserver also allows the integration of experimental cross-linking data which helps to interpret the reliability of the structure predictions. With the PAE Viewer, the user obtains a unique online tool which for…
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STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization
Zhicheng Xu, Weiwen Wang, Tao Yang, Ling Li, Xizheng Ma and 25 more
192 citationsOpen access (CC-BY)doi:10.1093/nar/gkad933OpenAlex
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Recent technological developments in spatial transcriptomics allow researchers to measure gene expression of cells and their spatial locations at the single-cell level, generating detailed biological insight into biological processes. A comprehensive database could facilitate the sharing of spatial transcriptomic data and streamline the data acquisition process for researchers. Here, we present the Spatial TranscriptOmics DataBase (STOmicsDB), a database that serves as a one-stop hub for spatial transcriptomics. STOmicsDB integrates 218 manually curated datasets representing 17 species. We annotated cell types, identified spatial regions and genes, and performed cell-cell interaction analysis for these datasets. STOmicsDB features a user-friendly interface for the rapid visualization of millions of cells. To further facilitate the reusability and interoperability of spatial transcriptomic data, we developed standards for spatial transcriptomic data archiving and constructed a spatial transcriptomic data archiving system. Additionally, we offer a distinctive capability of customizing…
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TarBase-v9.0 extends experimentally supported miRNA–gene interactions to cell-types and virally encoded miRNAs
Giorgos Skoufos, Panos Kakoulidis, Spyros Tastsoglou, Elissavet Zacharopoulou, Vasiliki Kotsira and 17 more
184 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1071OpenAlex
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TarBase is a reference database dedicated to produce, curate and deliver high quality experimentally-supported microRNA (miRNA) targets on protein-coding transcripts. In its latest version (v9.0, https://dianalab.e-ce.uth.gr/tarbasev9), it pushes the envelope by introducing virally-encoded miRNAs, interactions leading to target-directed miRNA degradation (TDMD) events and the largest collection of miRNA-gene interactions to date in a plethora of experimental settings, tissues and cell-types. It catalogues ∼6 million entries, comprising ∼2 million unique miRNA-gene pairs, supported by 37 experimental (high- and low-yield) protocols in 172 tissues and cell-types. Interactions are annotated with rich metadata including information on genes/transcripts, miRNAs, samples, experimental contexts and publications, while millions of miRNA-binding locations are also provided at cell-type resolution. A completely re-designed interface with state-of-the-art web technologies, incorporates more features, and allows flexible and ingenious use. The new interface provides the capability to design…
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ELM—the Eukaryotic Linear Motif resource—2024 update
Manjeet Kumar, Sushama Michael, Jesús Alvarado-Valverde, András Zeke, Tamás Lázár and 20 more
184 citationsOpen access (OTHER-OA)doi:10.1093/nar/gkad1058OpenAlex
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Short Linear Motifs (SLiMs) are the smallest structural and functional components of modular eukaryotic proteins. They are also the most abundant, especially when considering post-translational modifications. As well as being found throughout the cell as part of regulatory processes, SLiMs are extensively mimicked by intracellular pathogens. At the heart of the Eukaryotic Linear Motif (ELM) Resource is a representative (not comprehensive) database. The ELM entries are created by a growing community of skilled annotators and provide an introduction to linear motif functionality for biomedical researchers. The 2024 ELM update includes 346 novel motif instances in areas ranging from innate immunity to both protein and RNA degradation systems. In total, 39 classes of newly annotated motifs have been added, and another 17 existing entries have been updated in the database. The 2024 ELM release now includes 356 motif classes incorporating 4283 individual motif instances manually curated from 4274 scientific publications and including >700 links to experimentally determined 3D structures.…
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DeepBIO: an automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation and visualization analysis
Ruheng Wang, Yi Jiang, Junru Jin, Chenglin Yin, Haoqing Yu and 6 more
176 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad055OpenAlex
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Here, we present DeepBIO, the first-of-its-kind automated and interpretable deep-learning platform for high-throughput biological sequence functional analysis. DeepBIO is a one-stop-shop web service that enables researchers to develop new deep-learning architectures to answer any biological question. Specifically, given any biological sequence data, DeepBIO supports a total of 42 state-of-the-art deep-learning algorithms for model training, comparison, optimization and evaluation in a fully automated pipeline. DeepBIO provides a comprehensive result visualization analysis for predictive models covering several aspects, such as model interpretability, feature analysis and functional sequential region discovery. Additionally, DeepBIO supports nine base-level functional annotation tasks using deep-learning architectures, with comprehensive interpretations and graphical visualizations to validate the reliability of annotated sites. Empowered by high-performance computers, DeepBIO allows ultra-fast prediction with up to million-scale sequence data in a few hours, demonstrating its…
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HMDD v4.0: a database for experimentally supported human microRNA-disease associations
Chunmei Cui, Bitao Zhong, Rui Fan, Qinghua Cui
168 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad717OpenAlex
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MicroRNAs (miRNAs) are a class of important small non-coding RNAs with critical molecular functions in almost all biological processes, and thus, they play important roles in disease diagnosis and therapy. Human MicroRNA Disease Database (HMDD) represents an important and comprehensive resource for biomedical researchers in miRNA-related medicine. Here, we introduce HMDD v4.0, which curates 53530 miRNA-disease association entries from literatures. In comparison to HMDD v3.0 released five years ago, HMDD v4.0 contains 1.5 times more entries. In addition, some new categories have been curated, including exosomal miRNAs implicated in diseases, virus-encoded miRNAs involved in human diseases, and entries containing miRNA-circRNA interactions. We also curated sex-biased miRNAs in diseases. Furthermore, in a case study, disease similarity analysis successfully revealed that sex-biased miRNAs related to developmental anomalies are associated with a number of human diseases with sex bias. HMDD can be freely visited at http://www.cuilab.cn/hmdd.
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HOCOMOCO in 2024: a rebuild of the curated collection of binding models for human and mouse transcription factors
Ilya E. Vorontsov, Irina A. Eliseeva, Arsenii O. Zinkevich, Mikhail Nikonov, Sergey Abramov and 11 more
160 citationsOpen access (CC-BY)doi:10.1093/nar/gkad1077OpenAlex
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We present a major update of the HOCOMOCO collection that provides DNA binding specificity patterns of 949 human transcription factors and 720 mouse orthologs. To make this release, we performed motif discovery in peak sets that originated from 14 183 ChIP-Seq experiments and reads from 2554 HT-SELEX experiments yielding more than 400 thousand candidate motifs. The candidate motifs were annotated according to their similarity to known motifs and the hierarchy of DNA-binding domains of the respective transcription factors. Next, the motifs underwent human expert curation to stratify distinct motif subtypes and remove non-informative patterns and common artifacts. Finally, the curated subset of 100 thousand motifs was supplied to the automated benchmarking to select the best-performing motifs for each transcription factor. The resulting HOCOMOCO v12 core collection contains 1443 verified position weight matrices, including distinct subtypes of DNA binding motifs for particular transcription factors. In addition to the core collection, HOCOMOCO v12 provides motif sets optimized for the…
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PEP-FOLD4: a pH-dependent force field for peptide structure prediction in aqueous solution
Julien Rey, Samuel Murail, Sjoerd J. de Vries, Philippe Derreumaux, Pierre Tufféry
160 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkad376OpenAlex
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Accurate and fast structure prediction of peptides of less 40 amino acids in aqueous solution has many biological applications, but their conformations are pH- and salt concentration-dependent. In this work, we present PEP-FOLD4 which goes one step beyond many machine-learning approaches, such as AlphaFold2, TrRosetta and RaptorX. Adding the Debye-Hueckel formalism for charged-charged side chain interactions to a Mie formalism for all intramolecular (backbone and side chain) interactions, PEP-FOLD4, based on a coarse-grained representation of the peptides, performs as well as machine-learning methods on well-structured peptides, but displays significant improvements for poly-charged peptides. PEP-FOLD4 is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD4. This server is free and there is no login requirement.
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PlantPAN 4.0: updated database for identifying conserved non-coding sequences and exploring dynamic transcriptional regulation in plant promoters
Chi-Nga Chow, Chien-Wen Yang, Nai-Yun Wu, Hung-Teng Wang, Kuan-Chieh Tseng and 3 more
159 citationsOpen access (CC-BY)doi:10.1093/nar/gkad945OpenAlex
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PlantPAN 4.0 (http://PlantPAN.itps.ncku.edu.tw/) is an integrative resource for constructing transcriptional regulatory networks for diverse plant species. In this release, the gene annotation and promoter sequences were expanded to cover 115 species. PlantPAN 4.0 can help users characterize the evolutionary differences and similarities among cis-regulatory elements; furthermore, this system can now help in identification of conserved non-coding sequences among homologous genes. The updated transcription factor binding site repository contains 3428 nonredundant matrices for 18305 transcription factors; this expansion helps in exploration of combinational and nucleotide variants of cis-regulatory elements in conserved non-coding sequences. Additionally, the genomic landscapes of regulatory factors were manually updated, and ChIP-seq data sets derived from a single-cell green alga (Chlamydomonas reinhardtii) were added. Furthermore, the statistical review and graphical analysis components were improved to offer intelligible information through ChIP-seq data analysis. These…
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Haplogrep 3 - an interactive haplogroup classification and analysis platform
Sebastian Schönherr, Hansi Weißensteiner, Florian Kronenberg, Lukas Forer
159 citationsOpen access (CC-BY)doi:10.1093/nar/gkad284OpenAlex
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Over the last decade, Haplogrep has become a standard tool for haplogroup classification in the field of human mitochondrial DNA and is widely used by medical, forensic, and evolutionary researchers. Haplogrep scales well for thousands of samples, supports many file formats and provides an intuitive graphical web interface. Nevertheless, the currently available version has limitations when applying it to large biobank-scale data. In this paper, we present a major upgrade to the software by adding (a) haplogroup summary statistics and variant annotations from various publicly available genome databases, (b) an interface to connect new phylogenetic trees, (c) a new state-of-the-art web framework managing large scale data, (d) algorithmic adaptions to improve FASTA classification using BWA-specific alignment rules and (e) a pre-classification quality control step for VCF samples. These improvements will give researchers the opportunity to classify thousands of samples as usual but providing additional ways to investigate the dataset directly in the browser. The web service and its…
- 50top 4.2%
Targeted tissue delivery of RNA therapeutics using antibody–oligonucleotide conjugates (AOCs)
Barbora Malecová, Rob S. Burke, Michael Cochran, Michael D Hood, Rachel E. Johns and 10 more
156 citationsOpen access (CC-BY)doi:10.1093/nar/gkad415OpenAlex
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Although targeting TfR1 to deliver oligonucleotides to skeletal muscle has been demonstrated in rodents, effectiveness and pharmacokinetic/pharmacodynamic (PKPD) properties remained unknown in higher species. We developed antibody-oligonucleotide conjugates (AOCs) towards mice or monkeys utilizing anti-TfR1 monoclonal antibodies (αTfR1) conjugated to various classes of oligonucleotides (siRNA, ASOs and PMOs). αTfR1 AOCs delivered oligonucleotides to muscle tissue in both species. In mice, αTfR1 AOCs achieved a > 15-fold higher concentration to muscle tissue than unconjugated siRNA. A single dose of an αTfR1 conjugated to an siRNA against Ssb mRNA produced > 75% Ssb mRNA reduction in mice and monkeys, and mRNA silencing was greatest in skeletal and cardiac (striated) muscle with minimal to no activity in other major organs. In mice the EC50 for Ssb mRNA reduction in skeletal muscle was >75-fold less than in systemic tissues. Oligonucleotides conjugated to control antibodies or cholesterol produced no mRNA reduction or were 10-fold less potent, respectively. Tissue PKPD of AOCs…
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The cohort is every article, review and book chapter OpenAlex attributes to Nucleic Acids Research with publication year 2023, excluding retracted works and paratext such as editorials and errata. The top 50 by citation count are listed; the percentile is the rank divided by the cohort size. 50 of the 50 entries have an abstract in OpenAlex. Counts were read on 29 October 2026 and will not be updated on this page, so a quoted rank stays verifiable. Full rules on the methodology page.
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