Most-cited articles · 2017
The 50 most-cited articles in Nucleic Acids Research, 2017
Ranked by OpenAlex citation count on 29 October 2026, out of 1,348 eligible articles Nucleic Acids Research published in 2017. Ranks are frozen; this page will not change. Number one, with 9,846 citations: GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses.
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- 1top 0.1%
GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses
Zefang Tang, Chenwei Li, Boxi Kang, Ge Gao, Cheng Li and 1 more
9,846 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx247OpenAlex
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Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping…
- 2top 0.2%
DrugBank 5.0: a major update to the DrugBank database for 2018
David Scott Wishart, Yannick Djoumbou-Feunang, An Chi Guo, Elvis J Lo, Ana Marcu and 17 more
8,383 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1037OpenAlex
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DrugBank (www.drugbank.ca) is a web-enabled database containing comprehensive molecular information about drugs, their mechanisms, their interactions and their targets. First described in 2006, DrugBank has continued to evolve over the past 12 years in response to marked improvements to web standards and changing needs for drug research and development. This year's update, DrugBank 5.0, represents the most significant upgrade to the database in more than 10 years. In many cases, existing data content has grown by 100% or more over the last update. For instance, the total number of investigational drugs in the database has grown by almost 300%, the number of drug-drug interactions has grown by nearly 600% and the number of SNP-associated drug effects has grown more than 3000%. Significant improvements have been made to the quantity, quality and consistency of drug indications, drug binding data as well as drug-drug and drug-food interactions. A great deal of brand new data have also been added to DrugBank 5.0. This includes information on the influence of hundreds of drugs on…
- 3top 0.3%
ClinVar: improving access to variant interpretations and supporting evidence
Melissa Landrum, Jennifer M. Lee, Mark Benson, Garth Brown, Chen Chao and 17 more
4,190 citationsOpen access (PUBLIC-DOMAIN)doi:10.1093/nar/gkx1153OpenAlex
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ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease, maintained at the National Institutes of Health. Interpretations of the clinical significance of variants are submitted by clinical testing laboratories, research laboratories, expert panels and other groups. ClinVar aggregates data by variant-disease pairs, and by variant (or set of variants). Data aggregated by variant are accessible on the website, in an improved set of variant call format files and as a new comprehensive XML report. ClinVar recently started accepting submissions that are focused primarily on providing phenotypic information for individuals who have had genetic testing. Submissions may come from clinical providers providing their own interpretation of the variant ('provider interpretation') or from groups such as patient registries that primarily provide phenotypic information from patients ('phenotyping only'). ClinVar continues to make improvements to its search and retrieval functions. Several new…
- 4top 0.3%
GeSeq – versatile and accurate annotation of organelle genomes
Michael Tillich, Pascal Lehwark, Tommaso Pellizzer, Elena S. Ulbricht-Jones, Axel Fischer and 2 more
3,479 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx391OpenAlex
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We have developed the web application GeSeq (https://chlorobox.mpimp-golm.mpg.de/geseq.html) for the rapid and accurate annotation of organellar genome sequences, in particular chloroplast genomes. In contrast to existing tools, GeSeq combines batch processing with a fully customizable reference sequence selection of organellar genome records from NCBI and/or references uploaded by the user. For the annotation of chloroplast genomes, the application additionally provides an integrated database of manually curated reference sequences. GeSeq identifies genes or other feature-encoding regions by BLAT-based homology searches and additionally, by profile HMM searches for protein and rRNA coding genes and two de novo predictors for tRNA genes. These unique features enable the user to conveniently compare the annotations of different state-of-the-art methods, thus supporting high-quality annotations. The main output of GeSeq is a GenBank file that usually requires only little curation and is instantly visualized by OGDRAW. GeSeq also offers a variety of optional additional outputs that…
- 5top 0.4%
HMDB 4.0: the human metabolome database for 2018
David Scott Wishart, Yannick Djoumbou-Feunang, Ana Marcu, An Chi Guo, Kevin Y. H. Liang and 23 more
3,439 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1089OpenAlex
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The Human Metabolome Database or HMDB (www.hmdb.ca) is a web-enabled metabolomic database containing comprehensive information about human metabolites along with their biological roles, physiological concentrations, disease associations, chemical reactions, metabolic pathways, and reference spectra. First described in 2007, the HMDB is now considered the standard metabolomic resource for human metabolic studies. Over the past decade the HMDB has continued to grow and evolve in response to emerging needs for metabolomics researchers and continuing changes in web standards. This year's update, HMDB 4.0, represents the most significant upgrade to the database in its history. For instance, the number of fully annotated metabolites has increased by nearly threefold, the number of experimental spectra has grown by almost fourfold and the number of illustrated metabolic pathways has grown by a factor of almost 60. Significant improvements have also been made to the HMDB's chemical taxonomy, chemical ontology, spectral viewing, and spectral/text searching tools. A great deal of brand new…
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The Reactome Pathway Knowledgebase
Antonio Fabregat, S Jupe, Lisa R. Matthews, Konstantinos Sidiropoulos, Marc E. Gillespie and 18 more
2,859 citationsOpen access (CC-BY)doi:10.1093/nar/gkx1132OpenAlex
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The Reactome Knowledgebase (https://reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism, and other cellular processes as an ordered network of molecular transformations-an extended version of a classic metabolic map, in a single consistent data model. Reactome functions both as an archive of biological processes and as a tool for discovering unexpected functional relationships in data such as gene expression profiles or somatic mutation catalogues from tumor cells. To support the continued brisk growth in the size and complexity of Reactome, we have implemented a graph database, improved performance of data analysis tools, and designed new data structures and strategies to boost diagram viewer performance. To make our website more accessible to human users, we have improved pathway display and navigation by implementing interactive Enhanced High Level Diagrams (EHLDs) with an associated icon library, and subpathway highlighting and zooming, in a simplified and reorganized web site with adaptive design. To encourage re-use of our…
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Ensembl 2018
Daniel R. Zerbino, Premanand Achuthan, Wasiu A. Akanni, M Ridwan Amode, Daniel G. Barrell and 25 more
2,605 citationsOpen access (CC-BY)doi:10.1093/nar/gkx1098OpenAlex
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The Ensembl project has been aggregating, processing, integrating and redistributing genomic datasets since the initial releases of the draft human genome, with the aim of accelerating genomics research through rapid open distribution of public data. Large amounts of raw data are thus transformed into knowledge, which is made available via a multitude of channels, in particular our browser (http://www.ensembl.org). Over time, we have expanded in multiple directions. First, our resources describe multiple fields of genomics, in particular gene annotation, comparative genomics, genetics and epigenomics. Second, we cover a growing number of genome assemblies; Ensembl Release 90 contains exactly 100. Third, our databases feed simultaneously into an array of services designed around different use cases, ranging from quick browsing to genome-wide bioinformatic analysis. We present here the latest developments of the Ensembl project, with a focus on managing an increasing number of assemblies, supporting efforts in genome interpretation and improving our browser.
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LinkedOmics: analyzing multi-omics data within and across 32 cancer types
Suhas V. Vasaikar, Péter Straub, Jing Wang, Bing Zhang
2,323 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1090OpenAlex
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The LinkedOmics database contains multi-omics data and clinical data for 32 cancer types and a total of 11 158 patients from The Cancer Genome Atlas (TCGA) project. It is also the first multi-omics database that integrates mass spectrometry (MS)-based global proteomics data generated by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) on selected TCGA tumor samples. In total, LinkedOmics has more than a billion data points. To allow comprehensive analysis of these data, we developed three analysis modules in the LinkedOmics web application. The LinkFinder module allows flexible exploration of associations between a molecular or clinical attribute of interest and all other attributes, providing the opportunity to analyze and visualize associations between billions of attribute pairs for each cancer cohort. The LinkCompare module enables easy comparison of the associations identified by LinkFinder, which is particularly useful in multi-omics and pan-cancer analyses. The LinkInterpreter module transforms identified associations into biological understanding through pathway and…
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agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update
Tian Tian, Yue Liu, Hengyu Yan, Qi You, Xin Yi and 3 more
2,322 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx382OpenAlex
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The agriGO platform, which has been serving the scientific community for >10 years, specifically focuses on gene ontology (GO) enrichment analyses of plant and agricultural species. We continuously maintain and update the databases and accommodate the various requests of our global users. Here, we present our updated agriGO that has a largely expanded number of supporting species (394) and datatypes (865). In addition, a larger number of species have been classified into groups covering crops, vegetables, fish, birds and insects closely related to the agricultural community. We further improved the computational efficiency, including the batch analysis and P-value distribution (PVD), and the user-friendliness of the web pages. More visualization features were added to the platform, including SEACOMPARE (cross comparison of singular enrichment analysis), direct acyclic graph (DAG) and Scatter Plots, which can be merged by choosing any significant GO term. The updated platform agriGO v2.0 is now publicly accessible at http://systemsbiology.cau.edu.cn/agriGOv2/.
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20 years of the SMART protein domain annotation resource
Ivica Letunić, Peer Bork B
2,022 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx922OpenAlex
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SMART (Simple Modular Architecture Research Tool) is a web resource (http://smart.embl.de) for the identification and annotation of protein domains and the analysis of protein domain architectures. SMART version 8 contains manually curated models for more than 1300 protein domains, with approximately 100 new models added since our last update article (1). The underlying protein databases were synchronized with UniProt (2), Ensembl (3) and STRING (4), doubling the total number of annotated domains and other protein features to more than 200 million. In its 20th year, the SMART analysis results pages have been streamlined again and its information sources have been updated. SMART's vector based display engine has been extended to all protein schematics in SMART and rewritten to use the latest web technologies. The internal full text search engine has been redesigned and updated, resulting in greatly increased search speed.
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TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions
Heonjong Han, Jae-Won Cho, Sangyoung Lee, Ayoung Yun, Hyojin Kim and 15 more
1,981 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1013OpenAlex
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Transcription factors (TFs) are major trans-acting factors in transcriptional regulation. Therefore, elucidating TF-target interactions is a key step toward understanding the regulatory circuitry underlying complex traits such as human diseases. We previously published a reference TF-target interaction database for humans-TRRUST (Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining)-which was constructed using sentence-based text mining, followed by manual curation. Here, we present TRRUST v2 (www.grnpedia.org/trrust) with a significant improvement from the previous version, including a significantly increased size of the database consisting of 8444 regulatory interactions for 800 TFs in humans. More importantly, TRRUST v2 also contains a database for TF-target interactions in mice, including 6552 TF-target interactions for 828 mouse TFs. TRRUST v2 is also substantially more comprehensive and less biased than other TF-target interaction databases. We also improved the web interface, which now enables prioritization of key TFs for a physiological condition…
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MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data
Achal Dhariwal, Jasmine Chong, Salam M. Habib, Irah L. King, Luis B. Agellon and 1 more
1,888 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx295OpenAlex
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The widespread application of next-generation sequencing technologies has revolutionized microbiome research by enabling high-throughput profiling of the genetic contents of microbial communities. How to analyze the resulting large complex datasets remains a key challenge in current microbiome studies. Over the past decade, powerful computational pipelines and robust protocols have been established to enable efficient raw data processing and annotation. The focus has shifted toward downstream statistical analysis and functional interpretation. Here, we introduce MicrobiomeAnalyst, a user-friendly tool that integrates recent progress in statistics and visualization techniques, coupled with novel knowledge bases, to enable comprehensive analysis of common data outputs produced from microbiome studies. MicrobiomeAnalyst contains four modules - the Marker Data Profiling module offers various options for community profiling, comparative analysis and functional prediction based on 16S rRNA marker gene data; the Shotgun Data Profiling module supports exploratory data analysis, functional…
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miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions
Chih‐Hung Chou, Sirjana Shrestha, Chi-Dung Yang, Nai-Wen Chang, Yuling Lin and 25 more
1,813 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1067OpenAlex
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MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased ∼1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available…
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MODOMICS: a database of RNA modification pathways. 2017 update
Pietro Boccaletto, Magdalena A. Machnicka, Elżbieta Purta, Paweł Piątkowski, Błażej Bagiński and 7 more
1,784 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1030OpenAlex
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MODOMICS is a database of RNA modifications that provides comprehensive information concerning the chemical structures of modified ribonucleosides, their biosynthetic pathways, the location of modified residues in RNA sequences, and RNA-modifying enzymes. In the current database version, we included the following new features and data: extended mass spectrometry and liquid chromatography data for modified nucleosides; links between human tRNA sequences and MINTbase - a framework for the interactive exploration of mitochondrial and nuclear tRNA fragments; new, machine-friendly system of unified abbreviations for modified nucleoside names; sets of modified tRNA sequences for two bacterial species, updated collection of mammalian tRNA modifications, 19 newly identified modified ribonucleosides and 66 functionally characterized proteins involved in RNA modification. Data from MODOMICS have been linked to the RNAcentral database of RNA sequences. MODOMICS is available at http://modomics.genesilico.pl.
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LigParGen web server: an automatic OPLS-AA parameter generator for organic ligands
Leela S. Dodda, Israel Cabeza de Vaca, Julian Tirado‐Rives, William L. Jorgensen
1,765 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx312OpenAlex
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The accurate calculation of protein/nucleic acid-ligand interactions or condensed phase properties by force field-based methods require a precise description of the energetics of intermolecular interactions. Despite the progress made in force fields, small molecule parameterization remains an open problem due to the magnitude of the chemical space; the most critical issue is the estimation of a balanced set of atomic charges with the ability to reproduce experimental properties. The LigParGen web server provides an intuitive interface for generating OPLS-AA/1.14*CM1A(-LBCC) force field parameters for organic ligands, in the formats of commonly used molecular dynamics and Monte Carlo simulation packages. This server has high value for researchers interested in studying any phenomena based on intermolecular interactions with ligands via molecular mechanics simulations. It is free and open to all at jorgensenresearch.com/ligpargen, and has no login requirements.
- 16top 1.2%
BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes
Martin Closter Jespersen, Bjoern Peters, Morten Nielsen, Paolo Marcatili
1,749 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx346OpenAlex
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Antibodies have become an indispensable tool for many biotechnological and clinical applications. They bind their molecular target (antigen) by recognizing a portion of its structure (epitope) in a highly specific manner. The ability to predict epitopes from antigen sequences alone is a complex task. Despite substantial effort, limited advancement has been achieved over the last decade in the accuracy of epitope prediction methods, especially for those that rely on the sequence of the antigen only. Here, we present BepiPred-2.0 (http://www.cbs.dtu.dk/services/BepiPred/), a web server for predicting B-cell epitopes from antigen sequences. BepiPred-2.0 is based on a random forest algorithm trained on epitopes annotated from antibody-antigen protein structures. This new method was found to outperform other available tools for sequence-based epitope prediction both on epitope data derived from solved 3D structures, and on a large collection of linear epitopes downloaded from the IEDB database. The method displays results in a user-friendly and informative way, both for computer-savvy…
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The MEROPS database of proteolytic enzymes, their substrates and inhibitors in 2017 and a comparison with peptidases in the PANTHER database
Neil David Rawlings, A. John Barrett, Paul D. Thomas, Xiaosong Huang, Alex G. Bateman and 1 more
1,746 citationsOpen access (CC-BY)doi:10.1093/nar/gkx1134OpenAlex
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The MEROPS database (http://www.ebi.ac.uk/merops/) is an integrated source of information about peptidases, their substrates and inhibitors. The hierarchical classification is: protein-species, family, clan, with an identifier at each level. The MEROPS website moved to the EMBL-EBI in 2017, requiring refactoring of the code-base and services provided. The interface to sequence searching has changed and the MEROPS protein sequence libraries can be searched at the EMBL-EBI with HMMER, FastA and BLASTP. Cross-references have been established between MEROPS and the PANTHER database at both the family and protein-species level, which will help to improve curation and coverage between the resources. Because of the increasing size of the MEROPS sequence collection, in future only sequences of characterized proteins, and from completely sequenced genomes of organisms of evolutionary, medical or commercial significance will be added. As an example, peptidase homologues in four proteomes from the Asgard superphylum of Archaea have been identified and compared to other archaean, bacterial and…
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The Encyclopedia of DNA elements (ENCODE): data portal update
Carrie Davis, Benjamin C. Hitz, Cricket Alicia Sloan, Esther T. Chan, Jean M. Davidson and 13 more
1,717 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1081OpenAlex
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The Encyclopedia of DNA Elements (ENCODE) Data Coordinating Center has developed the ENCODE Portal database and website as the source for the data and metadata generated by the ENCODE Consortium. Two principles have motivated the design. First, experimental protocols, analytical procedures and the data themselves should be made publicly accessible through a coherent, web-based search and download interface. Second, the same interface should serve carefully curated metadata that record the provenance of the data and justify its interpretation in biological terms. Since its initial release in 2013 and in response to recommendations from consortium members and the wider community of scientists who use the Portal to access ENCODE data, the Portal has been regularly updated to better reflect these design principles. Here we report on these updates, including results from new experiments, uniformly-processed data from other projects, new visualization tools and more comprehensive metadata to describe experiments and analyses. Additionally, the Portal is now home to meta(data) from related…
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The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: updates and expansion to encompass the new guide to IMMUNOPHARMACOLOGY
Simon D Harding, Joanna L Sharman, Elena Faccenda, Christopher Southan, Adam J Pawson and 13 more
1,646 citationsOpen access (CC-BY)doi:10.1093/nar/gkx1121OpenAlex
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The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb, www.guidetopharmacology.org) and its precursor IUPHAR-DB, have captured expert-curated interactions between targets and ligands from selected papers in pharmacology and drug discovery since 2003. This resource continues to be developed in conjunction with the International Union of Basic and Clinical Pharmacology (IUPHAR) and the British Pharmacological Society (BPS). As previously described, our unique model of content selection and quality control is based on 96 target-class subcommittees comprising 512 scientists collaborating with in-house curators. This update describes content expansion, new features and interoperability improvements introduced in the 10 releases since August 2015. Our relationship matrix now describes ∼9000 ligands, ∼15 000 binding constants, ∼6000 papers and ∼1700 human proteins. As an important addition, we also introduce our newly funded project for the Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb, www.guidetoimmunopharmacology.org). This has been 'forked' from the well-established GtoPdb data model and expanded…
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CPC2: a fast and accurate coding potential calculator based on sequence intrinsic features
Yu-Jian Kang, De-Chang Yang, Lei Kong, Mei Ling Hou, Yu-Qi Meng and 2 more
1,643 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx428OpenAlex
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With advances in next-generation sequencing technologies, numerous novel transcripts in a large number of organisms have been identified. With the goal of fast, accurate assessment of the coding ability of RNA transcripts, we upgraded the coding potential calculator CPC1 to CPC2. CPC2 runs ∼1000 times faster than CPC1 and exhibits superior accuracy compared with CPC1, especially for long non-coding transcripts. Moreover, the model of CPC2 is species-neutral, making it feasible for ever-growing non-model organism transcriptomes. A mobile-friendly web server, as well as a downloadable standalone package, is freely available at http://cpc2.cbi.pku.edu.cn.
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PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database
Xia Wang, Yihang Shen, Shiwei Wang, Shiliang Li, Weilin Zhang and 4 more
1,604 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx374OpenAlex
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The PharmMapper online tool is a web server for potential drug target identification by reversed pharmacophore matching the query compound against an in-house pharmacophore model database. The original version of PharmMapper includes more than 7000 target pharmacophores derived from complex crystal structures with corresponding protein target annotations. In this article, we present a new version of the PharmMapper web server, of which the backend pharmacophore database is six times larger than the earlier one, with a total of 23 236 proteins covering 16 159 druggable pharmacophore models and 51 431 ligandable pharmacophore models. The expanded target data cover 450 indications and 4800 molecular functions compared to 110 indications and 349 molecular functions in our last update. In addition, the new web server is united with the statistically meaningful ranking of the identified drug targets, which is achieved through the use of standard scores. It also features an improved user interface. The proposed web server is freely available at http://lilab.ecust.edu.cn/pharmmapper/.
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IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets
Claire Bertelli, Matthew R. Laird, Kelly Porter Williams, Britney Y. Lau, Gemma R Hoad and 2 more
1,549 citationsOpen access (CC-BY)doi:10.1093/nar/gkx343OpenAlex
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IslandViewer (http://www.pathogenomics.sfu.ca/islandviewer/) is a widely-used webserver for the prediction and interactive visualization of genomic islands (GIs, regions of probable horizontal origin) in bacterial and archaeal genomes. GIs disproportionately encode factors that enhance the adaptability and competitiveness of the microbe within a niche, including virulence factors and other medically or environmentally important adaptations. We report here the release of IslandViewer 4, with novel features to accommodate the needs of larger-scale microbial genomics analysis, while expanding GI predictions and improving its flexible visualization interface. A user management web interface as well as an HTTP API for batch analyses are now provided with a secured authentication to facilitate the submission of larger numbers of genomes and the retrieval of results. In addition, IslandViewer's integrated GI predictions from multiple methods have been improved and expanded by integrating the precise Islander method for pre-computed genomes, as well as an updated IslandPath-DIMOB for both…
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Database resources of the National Center for Biotechnology Information
NCBI Resource Coordinators, Richa Agarwala, Tanya Barrett, Jeffrey D. Beck, D. A. Benson and 25 more
1,514 citationsOpen access (PUBLIC-DOMAIN)doi:10.1093/nar/gkx1095OpenAlex
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The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank® nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. The Entrez system provides search and retrieval operations for most of these data from 39 distinct databases. The E-utilities serve as the programming interface for the Entrez system. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. New resources released in the past year include PubMed Data Management, RefSeq Functional Elements, genome data download, variation services API, Magic-BLAST, QuickBLASTp, and Identical Protein Groups. Resources that were updated in the past year include the genome data viewer, a human genome resources page, Gene, virus variation, OSIRIS, and PubChem. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.
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JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework
Aziz Khan, Oriol Fornés, Arnaud Stigliani, Marius Gheorghe, Jaime Abraham Castro-Mondragon and 14 more
1,475 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1126OpenAlex
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JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) and TF flexible models (TFFMs) for TFs across multiple species in six taxonomic groups. In the 2018 release of JASPAR, the CORE collection has been expanded with 322 new PFMs (60 for vertebrates and 262 for plants) and 33 PFMs were updated (24 for vertebrates, 8 for plants and 1 for insects). These new profiles represent a 30% expansion compared to the 2016 release. In addition, we have introduced 316 TFFMs (95 for vertebrates, 218 for plants and 3 for insects). This release incorporates clusters of similar PFMs in each taxon and each TF class per taxon. The JASPAR 2018 CORE vertebrate collection of PFMs was used to predict TF-binding sites in the human genome. The predictions are made available to the scientific community through a UCSC Genome Browser track data hub. Finally, this update comes with a new web framework with an interactive and responsive user-interface, along with new features. All the…
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HDOCK: a web server for protein–protein and protein–DNA/RNA docking based on a hybrid strategy
Yumeng Yan, Di Zhang, Pei Zhou, Botong Li, Sheng‐You Huang
1,472 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx407OpenAlex
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Protein-protein and protein-DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein-protein and protein-DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10-20 min for a docking run. Tested on the cases with weakly homologous complexes of <30% sequence identity from five docking benchmarks, the HDOCK pipeline tied with template-based modeling on the protein-protein and protein-DNA benchmarks and performed better than template-based modeling on the three protein-RNA benchmarks when the top 10 predictions were considered. The performance of HDOCK…
- 26top 2%
Virus taxonomy: the database of the International Committee on Taxonomy of Viruses (ICTV)
Elliot J. Lefkowitz, Donald M. Dempsey, Robert Curtis Hendrickson, Richard J Orton, Stuart G. Siddell and 1 more
1,230 citationsOpen access (CC-BY)doi:10.1093/nar/gkx932OpenAlex
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The International Committee on Taxonomy of Viruses (ICTV) is charged with the task of developing, refining, and maintaining a universal virus taxonomy. This task encompasses the classification of virus species and higher-level taxa according to the genetic and biological properties of their members; naming virus taxa; maintaining a database detailing the currently approved taxonomy; and providing the database, supporting proposals, and other virus-related information from an open-access, public web site. The ICTV web site (http://ictv.global) provides access to the current taxonomy database in online and downloadable formats, and maintains a complete history of virus taxa back to the first release in 1971. The ICTV has also published the ICTV Report on Virus Taxonomy starting in 1971. This Report provides a comprehensive description of all virus taxa covering virus structure, genome structure, biology and phylogenetics. The ninth ICTV report, published in 2012, is available as an open-access online publication from the ICTV web site. The current, 10th report…
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WebGestalt 2017: a more comprehensive, powerful, flexible and interactive gene set enrichment analysis toolkit
Jing Wang, Suhas V. Vasaikar, Zhiao Shi, Michael Greer, Bing Zhang
1,160 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx356OpenAlex
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Functional enrichment analysis has played a key role in the biological interpretation of high-throughput omics data. As a long-standing and widely used web application for functional enrichment analysis, WebGestalt has been constantly updated to satisfy the needs of biologists from different research areas. WebGestalt 2017 supports 12 organisms, 324 gene identifiers from various databases and technology platforms, and 150 937 functional categories from public databases and computational analyses. Omics data with gene identifiers not supported by WebGestalt and functional categories not included in the WebGestalt database can also be uploaded for enrichment analysis. In addition to the Over-Representation Analysis in the previous versions, Gene Set Enrichment Analysis and Network Topology-based Analysis have been added to WebGestalt 2017, providing complementary approaches to the interpretation of high-throughput omics data. The new user-friendly output interface and the GOView tool allow interactive and efficient exploration and comparison of enrichment results. Thus, WebGestalt…
- 28top 2.1%
antiSMASH 4.0—improvements in chemistry prediction and gene cluster boundary identification
Kai Blin, Thomas Wolf, Marc G. Chevrette, Xiaowen Lu, Christopher J. Schwalen and 13 more
1,158 citationsOpen access (CC-BY)doi:10.1093/nar/gkx319OpenAlex
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Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding the production of such compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally synthesized and post-translationally modified peptides cluster products, reporting of sequence similarity to proteins encoded in experimentally characterized gene clusters on a per-protein basis…
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DIANA-TarBase v8: a decade-long collection of experimentally supported miRNA–gene interactions
Dimitra Karagkouni, Maria D. Paraskevopoulou, Serafeim Chatzopoulos, Ioannis S. Vlachos, Spyros Tastsoglou and 8 more
1,120 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1141OpenAlex
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DIANA-TarBase v8 (http://www.microrna.gr/tarbase) is a reference database devoted to the indexing of experimentally supported microRNA (miRNA) targets. Its eighth version is the first database indexing >1 million entries, corresponding to ∼670 000 unique miRNA-target pairs. The interactions are supported by >33 experimental methodologies, applied to ∼600 cell types/tissues under ∼451 experimental conditions. It integrates information on cell-type specific miRNA-gene regulation, while hundreds of thousands of miRNA-binding locations are reported. TarBase is coming of age, with more than a decade of continuous support in the non-coding RNA field. A new module has been implemented that enables the browsing of interactions through different filtering combinations. It permits easy retrieval of positive and negative miRNA targets per species, methodology, cell type and tissue. An incorporated ranking system is utilized for the display of interactions based on the robustness of their supporting methodologies. Statistics, pie-charts and interactive bar-plots depicting the database content…
- 30top 2.3%
Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families
Ioanna Kalvari, Joanna Argasinska, Natalia Quinones‐Olvera, Eric Paul Nawrocki, Elena Rivas and 4 more
1,003 citationsOpen access (CC-BY)doi:10.1093/nar/gkx1038OpenAlex
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The Rfam database is a collection of RNA families in which each family is represented by a multiple sequence alignment, a consensus secondary structure, and a covariance model. In this paper we introduce Rfam release 13.0, which switches to a new genome-centric approach that annotates a non-redundant set of reference genomes with RNA families. We describe new web interface features including faceted text search and R-scape secondary structure visualizations. We discuss a new literature curation workflow and a pipeline for building families based on RNAcentral. There are 236 new families in release 13.0, bringing the total number of families to 2687. The Rfam website is http://rfam.org.
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RefSeq: an update on prokaryotic genome annotation and curation
Daniel H. Haft, Michael N. DiCuccio, Azat J. Badretdin, Vyacheslav V. Brover, Vyacheslav Chetvernin and 16 more
988 citationsOpen access (PUBLIC-DOMAIN)doi:10.1093/nar/gkx1068OpenAlex
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The Reference Sequence (RefSeq) project at the National Center for Biotechnology Information (NCBI) provides annotation for over 95 000 prokaryotic genomes that meet standards for sequence quality, completeness, and freedom from contamination. Genomes are annotated by a single Prokaryotic Genome Annotation Pipeline (PGAP) to provide users with a resource that is as consistent and accurate as possible. Notable recent changes include the development of a hierarchical evidence scheme, a new focus on curating annotation evidence sources, the addition and curation of protein profile hidden Markov models (HMMs), release of an updated pipeline (PGAP-4), and comprehensive re-annotation of RefSeq prokaryotic genomes. Antimicrobial resistance proteins have been reannotated comprehensively, improved structural annotation of insertion sequence transposases and selenoproteins is provided, curated complex domain architectures have given upgraded names to millions of multidomain proteins, and we introduce a new kind of annotation rule-BlastRules. Continual curation of supporting evidence, and…
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HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis
Ivan V. Kulakovskiy, Ilya E. Vorontsov, Ivan Yevshin, Ruslan Sharipov, Alla D. Fedorova and 7 more
921 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1106OpenAlex
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We present a major update of the HOCOMOCO collection that consists of patterns describing DNA binding specificities for human and mouse transcription factors. In this release, we profited from a nearly doubled volume of published in vivo experiments on transcription factor (TF) binding to expand the repertoire of binding models, replace low-quality models previously based on in vitro data only and cover more than a hundred TFs with previously unknown binding specificities. This was achieved by systematic motif discovery from more than five thousand ChIP-Seq experiments uniformly processed within the BioUML framework with several ChIP-Seq peak calling tools and aggregated in the GTRD database. HOCOMOCO v11 contains binding models for 453 mouse and 680 human transcription factors and includes 1302 mononucleotide and 576 dinucleotide position weight matrices, which describe primary binding preferences of each transcription factor and reliable alternative binding specificities. An interactive interface and bulk downloads are available on the web: http://hocomoco.autosome.ru and…
- 33top 2.5%
WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research
Denise Slenter, Martina Kutmon, Kristina Hanspers, Anders Riutta, Jacob Windsor and 17 more
909 citationsOpen access (CC-BY)doi:10.1093/nar/gkx1064OpenAlex
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WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable,…
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The MetaCyc database of metabolic pathways and enzymes
Ron Caspi, Richard Billington, Carol A. Fulcher, Ingrid M. Keseler, Anamika Kothari and 8 more
902 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx935OpenAlex
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MetaCyc (https://MetaCyc.org) is a comprehensive reference database of metabolic pathways and enzymes from all domains of life. It contains more than 2570 pathways derived from >54 000 publications, making it the largest curated collection of metabolic pathways. The data in MetaCyc is strictly evidence-based and richly curated, resulting in an encyclopedic reference tool for metabolism. MetaCyc is also used as a knowledge base for generating thousands of organism-specific Pathway/Genome Databases (PGDBs), which are available in the BioCyc (https://BioCyc.org) and other PGDB collections. This article provides an update on the developments in MetaCyc during the past two years, including the expansion of data and addition of new features.
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DGIdb 3.0: a redesign and expansion of the drug–gene interaction database
Kelsy C. Cotto, Alex Handler Wagner, Yang-Yang Feng, Susanna Kiwala, Adam C. Coffman and 5 more
887 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1143OpenAlex
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The drug-gene interaction database (DGIdb, www.dgidb.org) consolidates, organizes and presents drug-gene interactions and gene druggability information from papers, databases and web resources. DGIdb normalizes content from 30 disparate sources and allows for user-friendly advanced browsing, searching and filtering for ease of access through an intuitive web user interface, application programming interface (API) and public cloud-based server image. DGIdb v3.0 represents a major update of the database. Nine of the previously included 24 sources were updated. Six new resources were added, bringing the total number of sources to 30. These updates and additions of sources have cumulatively resulted in 56 309 interaction claims. This has also substantially expanded the comprehensive catalogue of druggable genes and anti-neoplastic drug-gene interactions included in the DGIdb. Along with these content updates, v3.0 has received a major overhaul of its codebase, including an updated user interface, preset interaction search filters, consolidation of interaction information into…
- 36top 2.7%
N 6-methyladenosine alters RNA structure to regulate binding of a low-complexity protein
Nian Liu, Katherine Ismei Zhou, Marc Parisien, Qing Dai, Luda B. Diatchenko and 1 more
792 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx141OpenAlex
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N6-methyladenosine (m6A) is the most abundant internal modification in eukaryotic messenger RNA (mRNA), and affects almost every stage of the mRNA life cycle. The YTH-domain proteins can specifically recognize m6A modification to control mRNA maturation, translation and decay. m6A can also alter RNA structures to affect RNA-protein interactions in cells. Here, we show that m6A increases the accessibility of its surrounding RNA sequence to bind heterogeneous nuclear ribonucleoprotein G (HNRNPG). Furthermore, HNRNPG binds m6A-methylated RNAs through its C-terminal low-complexity region, which self-assembles into large particles in vitro. The Arg-Gly-Gly repeats within the low-complexity region are required for binding to the RNA motif exposed by m6A methylation. We identified 13,191 m6A sites in the transcriptome that regulate RNA-HNRNPG interaction and thereby alter the expression and alternative splicing pattern of target mRNAs. Low-complexity regions are pervasive among mRNA binding proteins. Our results show that m6A-dependent RNA structural alterations can promote direct binding…
- 37top 2.8%
GenBank
D. A. Benson, Mark L. Cavanaugh, Karen Clark, Ilene Karsch‐Mizrachi, James Ostell and 2 more
760 citationsOpen access (PUBLIC-DOMAIN)doi:10.1093/nar/gkx1094OpenAlex
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GenBank® (www.ncbi.nlm.nih.gov/genbank/) is a comprehensive database that contains publicly available nucleotide sequences for 400 000 formally described species. These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole genome shotgun and environmental sampling projects. Most submissions are made using BankIt, the National Center for Biotechnology Information (NCBI) Submission Portal, or the tool tbl2asn. GenBank staff assign accession numbers upon data receipt. Daily data exchange with the European Nucleotide Archive and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through the NCBI Nucleotide database, which links to related information such as taxonomy, genomes, protein sequences and structures, and biomedical journal literature in PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. Recent updates include changes…
- 38top 2.9%
Human Ageing Genomic Resources: new and updated databases
Robi Tăcutu, Daniel Thornton, Emily Johnson, Arie Budovsky, Diogo Barardo and 7 more
737 citationsOpen access (CC-BY)doi:10.1093/nar/gkx1042OpenAlex
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In spite of a growing body of research and data, human ageing remains a poorly understood process. Over 10 years ago we developed the Human Ageing Genomic Resources (HAGR), a collection of databases and tools for studying the biology and genetics of ageing. Here, we present HAGR's main functionalities, highlighting new additions and improvements. HAGR consists of six core databases: (i) the GenAge database of ageing-related genes, in turn composed of a dataset of >300 human ageing-related genes and a dataset with >2000 genes associated with ageing or longevity in model organisms; (ii) the AnAge database of animal ageing and longevity, featuring >4000 species; (iii) the GenDR database with >200 genes associated with the life-extending effects of dietary restriction; (iv) the LongevityMap database of human genetic association studies of longevity with >500 entries; (v) the DrugAge database with >400 ageing or longevity-associated drugs or compounds; (vi) the CellAge database with >200 genes associated with cell senescence. All our databases are manually curated by experts and…
- 39top 2.9%
IntaRNA 2.0: enhanced and customizable prediction of RNA–RNA interactions
Martin Mann, Patrick Rudolf Wright, Rolf Backofen
716 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx279OpenAlex
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The IntaRNA algorithm enables fast and accurate prediction of RNA-RNA hybrids by incorporating seed constraints and interaction site accessibility. Here, we introduce IntaRNAv2, which enables enhanced parameterization as well as fully customizable control over the prediction modes and output formats. Based on up to date benchmark data, the enhanced predictive quality is shown and further improvements due to more restrictive seed constraints are highlighted. The extended web interface provides visualizations of the new minimal energy profiles for RNA-RNA interactions. These allow a detailed investigation of interaction alternatives and can reveal potential interaction site multiplicity. IntaRNAv2 is freely available (source and binary), and distributed via the conda package manager. Furthermore, it has been included into the Galaxy workflow framework and its already established web interface enables ad hoc usage.
- 40top 3%
Chemistry, mechanism and clinical status of antisense oligonucleotides and duplex RNAs
Xiulong Shen, David R. Corey
637 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1239OpenAlex
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RNA plays a central role in the expression of all genes. Because any sequence within RNA can be recognized by complementary base pairing, synthetic oligonucleotides and oligonucleotide mimics offer a general strategy for controlling processes that affect disease. The two primary antisense approaches for regulating expression through recognition of cellular RNAs are single-stranded antisense oligonucleotides and duplex RNAs. This review will discuss the chemical modifications and molecular mechanisms that make synthetic nucleic acid drugs possible. Lessons learned from recent clinical trials will be summarized. Ongoing clinical trials are likely to decisively test the adequacy of our current generation of antisense nucleic acid technologies and highlight areas where more basic research is needed.
- 41top 3.1%
PlasFlow: predicting plasmid sequences in metagenomic data using genome signatures
Paweł Szczepan Krawczyk, Leszek Lipiński, Andrzej Dziembowski
626 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1321OpenAlex
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Plasmids are mobile genetics elements that play an important role in the environmental adaptation of microorganisms. Although plasmids are usually analyzed in cultured microorganisms, there is a need for methods that allow for the analysis of pools of plasmids (plasmidomes) in environmental samples. To that end, several molecular biology and bioinformatics methods have been developed; however, they are limited to environments with low diversity and cannot recover large plasmids. Here, we present PlasFlow, a novel tool based on genomic signatures that employs a neural network approach for identification of bacterial plasmid sequences in environmental samples. PlasFlow can recover plasmid sequences from assembled metagenomes without any prior knowledge of the taxonomical or functional composition of samples with an accuracy up to 96%. It can also recover sequences of both circular and linear plasmids and can perform initial taxonomical classification of sequences. Compared to other currently available tools, PlasFlow demonstrated significantly better performance on test datasets.…
- 42top 3.2%
VDJdb: a curated database of T-cell receptor sequences with known antigen specificity
Mikhail Shugay, Dmitriy V. Bagaev, Ivan V. Zvyagin, Renske M. A. Vroomans, Jeremy Chase Crawford and 23 more
623 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx760OpenAlex
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The ability to decode antigen specificities encapsulated in the sequences of rearranged T-cell receptor (TCR) genes is critical for our understanding of the adaptive immune system and promises significant advances in the field of translational medicine. Recent developments in high-throughput sequencing methods (immune repertoire sequencing technology, or RepSeq) and single-cell RNA sequencing technology have allowed us to obtain huge numbers of TCR sequences from donor samples and link them to T-cell phenotypes. However, our ability to annotate these TCR sequences still lags behind, owing to the enormous diversity of the TCR repertoire and the scarcity of available data on T-cell specificities. In this paper, we present VDJdb, a database that stores and aggregates the results of published T-cell specificity assays and provides a universal platform that couples antigen specificities with TCR sequences. We demonstrate that VDJdb is a versatile instrument for the annotation of TCR repertoire data, enabling a concatenated view of antigen-specific TCR sequence motifs. VDJdb can be…
- 43top 3.2%
COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information
Chengxin Zhang, Lydia Freddolino, Yang Zhang
606 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx366OpenAlex
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The COFACTOR web server is a unified platform for structure-based multiple-level protein function predictions. By structurally threading low-resolution structural models through the BioLiP library, the COFACTOR server infers three categories of protein functions including gene ontology, enzyme commission and ligand-binding sites from various analogous and homologous function templates. Here, we report recent improvements of the COFACTOR server in the development of new pipelines to infer functional insights from sequence profile alignments and protein-protein interaction networks. Large-scale benchmark tests show that the new hybrid COFACTOR approach significantly improves the function annotation accuracy of the former structure-based pipeline and other state-of-the-art functional annotation methods, particularly for targets that have no close homology templates. The updated COFACTOR server and the template libraries are available at http://zhanglab.ccmb.med.umich.edu/COFACTOR/.
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mirDIP 4.1—integrative database of human microRNA target predictions
Tomáš Tokár, Chiara Pastrello, Andrea E.M. Rossos, Mark Abovsky, Anne-Christin Hauschild and 3 more
574 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1144OpenAlex
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MicroRNAs are important regulators of gene expression, achieved by binding to the gene to be regulated. Even with modern high-throughput technologies, it is laborious and expensive to detect all possible microRNA targets. For this reason, several computational microRNA-target prediction tools have been developed, each with its own strengths and limitations. Integration of different tools has been a successful approach to minimize the shortcomings of individual databases. Here, we present mirDIP v4.1, providing nearly 152 million human microRNA-target predictions, which were collected across 30 different resources. We also introduce an integrative score, which was statistically inferred from the obtained predictions, and was assigned to each unique microRNA-target interaction to provide a unified measure of confidence. We demonstrate that integrating predictions across multiple resources does not cumulate prediction bias toward biological processes or pathways. mirDIP v4.1 is freely available at http://ophid.utoronto.ca/mirDIP/.
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GPCRdb in 2018: adding GPCR structure models and ligands
Gáspár Pándy‐Szekeres, Christian Munk, Tsonko M. Tsonkov, Stefan Mordalski, Kasper Harpsøe and 3 more
556 citationsOpen access (CC-BY)doi:10.1093/nar/gkx1109OpenAlex
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G protein-coupled receptors are the most abundant mediators of both human signalling processes and therapeutic effects. Herein, we report GPCRome-wide homology models of unprecedented quality, and roughly 150 000 GPCR ligands with data on biological activities and commercial availability. Based on the strategy of 'Less model - more Xtal', each model exploits both a main template and alternative local templates. This achieved higher similarity to new structures than any of the existing resources, and refined crystal structures with missing or distorted regions. Models are provided for inactive, intermediate and active states-except for classes C and F that so far only have inactive templates. The ligand database has separate browsers for: (i) target selection by receptor, family or class, (ii) ligand filtering based on cross-experiment activities (min, max and mean) or chemical properties, (iii) ligand source data and (iv) commercial availability. SMILES structures and activity spreadsheets can be downloaded for further processing. Furthermore, three recent landmark publications on…
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NONCODEV5: a comprehensive annotation database for long non-coding RNAs
Shuangsang Fang, LiLi Zhang, Jincheng Guo, Yiwei Niu, Yang Wu and 9 more
553 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1107OpenAlex
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NONCODE (http://www.bioinfo.org/noncode/) is a systematic database that is dedicated to presenting the most complete collection and annotation of non-coding RNAs (ncRNAs), especially long non-coding RNAs (lncRNAs). Since NONCODE 2016 was released two years ago, the amount of novel identified ncRNAs has been enlarged by the reduced cost of next-generation sequencing, which has produced an explosion of newly identified data. The third-generation sequencing revolution has also offered longer and more accurate annotations. Moreover, accumulating evidence confirmed by biological experiments has provided more comprehensive knowledge of lncRNA functions. The ncRNA data set was expanded by collecting newly identified ncRNAs from literature published over the past two years and integration of the latest versions of RefSeq and Ensembl. Additionally, pig was included in the database for the first time, bringing the total number of species to 17. The number of lncRNAs in NONCODEv5 increased from 527 336 to 548 640. NONCODEv5 also introduced three important new features: (i) human lncRNA-disease…
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exoRBase: a database of circRNA, lncRNA and mRNA in human blood exosomes
Shengli Li, Yuchen Li, Bing Chen, Jingjing Zhao, Shulin Yu and 6 more
541 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx891OpenAlex
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Exosomes, which are nanosized endocytic vesicles that are secreted by most cells, contain an abundant cargo of different RNA species that can modulate the behavior of recipient cells and may be used as circulating biomarkers for diseases. Here, we develop a web-accessible database (http://www.exoRBase.org), exoRBase, which is a repository of circular RNA (circRNA), long non-coding RNA (lncRNA) and messenger RNA (mRNA) derived from RNA-seq data analyses of human blood exosomes. Experimental validations from the published literature are also included. exoRBase features the integration and visualization of RNA expression profiles based on normalized RNA-seq data spanning both normal individuals and patients with different diseases. exoRBase aims to collect and characterize all long RNA species in human blood exosomes. The first release of exoRBase contains 58 330 circRNAs, 15 501 lncRNAs and 18 333 mRNAs. The annotation, expression level and possible original tissues are provided. exoRBase will aid researchers in identifying molecular signatures in blood exosomes and will trigger new…
- 48top 3.6%
Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics
Yinghong Li, Chun Yan Yu, Xiao Xu Li, Peng Zhang, Jing Tang and 14 more
523 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx1076OpenAlex
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Extensive efforts have been directed at the discovery, investigation and clinical monitoring of targeted therapeutics. These efforts may be facilitated by the convenient access of the genetic, proteomic, interactive and other aspects of the therapeutic targets. Here, we describe an update of the Therapeutic target database (TTD) previously featured in NAR. This update includes: (i) 2000 drug resistance mutations in 83 targets and 104 target/drug regulatory genes, which are resistant to 228 drugs targeting 63 diseases (49 targets of 61 drugs with patient prevalence data); (ii) differential expression profiles of 758 targets in the disease-relevant drug-targeted tissue of 12 615 patients of 70 diseases; (iii) expression profiles of 629 targets in the non-targeted tissues of 2565 healthy individuals; (iv) 1008 target combinations of 1764 drugs and the 1604 target combination of 664 multi-target drugs; (v) additional 48 successful, 398 clinical trial and 21 research targets, 473 approved, 812 clinical trial and 1120 experimental drugs, and (vi) ICD-10-CM and ICD-9-CM codes for…
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SDM: a server for predicting effects of mutations on protein stability
Arun Prasad Pandurangan, Bernardo Ochoa‐Montaño, David Benjamin Ascher, Tom L. Blundell
501 citationsOpen access (CC-BY)doi:10.1093/nar/gkx439OpenAlex
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Here, we report a webserver for the improved SDM, used for predicting the effects of mutations on protein stability. As a pioneering knowledge-based approach, SDM has been highlighted as the most appropriate method to use in combination with many other approaches. We have updated the environment-specific amino-acid substitution tables based on the current expanded PDB (a 5-fold increase in information), and introduced new residue-conformation and interaction parameters, including packing density and residue depth. The updated server has been extensively tested using a benchmark containing 2690 point mutations from 132 different protein structures. The revised method correlates well against the hypothetical reverse mutations, better than comparable methods built using machine-learning approaches, highlighting the strength of our knowledge-based approach for identifying stabilising mutations. Given a PDB file (a Protein Data Bank file format containing the 3D coordinates of the protein atoms), and a point mutation, the server calculates the stability difference score between the…
- 50top 3.8%
Nuclear speckles: molecular organization, biological function and role in disease
Łukasz Gałgański, Martyna Olga Urbanek-Trzeciak, Włodzimierz J. Krzyżosiak
500 citationsOpen access (CC-BY-NC)doi:10.1093/nar/gkx759OpenAlex
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The nucleoplasm is not homogenous; it consists of many types of nuclear bodies, also known as nuclear domains or nuclear subcompartments. These self-organizing structures gather machinery involved in various nuclear activities. Nuclear speckles (NSs) or splicing speckles, also called interchromatin granule clusters, were discovered as sites for splicing factor storage and modification. Further studies on transcription and mRNA maturation and export revealed a more general role for splicing speckles in RNA metabolism. Here, we discuss the functional implications of the localization of numerous proteins crucial for epigenetic regulation, chromatin organization, DNA repair and RNA modification to nuclear speckles. We highlight recent advances suggesting that NSs facilitate integrated regulation of gene expression. In addition, we consider the influence of abundant regulatory and signaling proteins, i.e. protein kinases and proteins involved in protein ubiquitination, phosphoinositide signaling and nucleoskeletal organization, on pre-mRNA synthesis and maturation. While many of these…
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The cohort is every article, review and book chapter OpenAlex attributes to Nucleic Acids Research with publication year 2017, 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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