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The 2012 Bioinformatics Links Directory update marks the 10th special Web Server issue from Nucleic Acids Research. Beginning with content from their 2003 publication, the Bioinformatics Links Directory in collaboration with Nucleic Acids Research has compiled and published a comprehensive list of freely accessible, online tools, databases and resource materials for the bioinformatics and life science research communities. The past decade has exhibited significant growth and change in the types of tools, databases and resources being put forth, reflecting both technology changes and the nature of research over that time. With the addition of 90 web server tools and 12 updates from the July 2012 Web Server issue of Nucleic Acids Research, the Bioinformatics Links Directory at http://bioinformatics.ca/links_directory/ now contains an impressive 134 resources, 455 databases and 1205 web server tools, mirroring the continued activity and efforts of our field.

The Bioinformatics Links Directory continues its collaboration with Nucleic Acids Research to collaboratively publish and compile a freely accessible, online collection of tools, databases and resource materials for bioinformatics and molecular biology research. The July 2011 Web Server issue of Nucleic Acids Research adds an additional 78 web server tools and 14 updates to the directory at http://bioinformatics.ca/links_directory/.

Genome annotation and access to information from large-scale experimental approaches at the genome level are essential to improve our understanding of living cells and organisms. This is even more the case for model organisms that are the basis to study pathogens and technologically important species. We have generated SubtiWiki, a database for the Gram-positive model bacterium Bacillus subtilis (http://subtiwiki.uni-goettingen.de/). In addition to the established companion modules of SubtiWiki, SubtiPathways and SubtInteract, we have now created SubtiExpress, a third module, to visualize genome scale transcription data that are of unprecedented quality and density. Today, SubtiWiki is one of the most complete collections of knowledge on a living organism in one single resource. peerReviewed

The current deluge of genomic sequences has spawned the creation of tools capable of making sense of the data. Computational and high-throughput experimental methods for generating links between proteins have recently been emerging. These methods effectively act as hypothesis machines, allowing researchers to screen large sets of data to detect interesting patterns that can then be studied in greater detail. Although the potential use of these putative links in predicting gene function has been demonstrated, a central repository for all such links for many genomes would maximize their usefulness. Here we present Predictome, a database of predicted links between the proteins of 44 genomes based on the implementation of three computational methods--chromosomal proximity, phylogenetic profiling and domain fusion--and large-scale experimental screenings of protein-protein interaction data. The combination of data from various predictive methods in one database allows for their comparison with each other, as well as visualization of their correlation with known pathway information. As a repository for such data, Predictome is an ongoing resource for the community, providing functional relationships among proteins as new genomic data emerges. Predictome is available at http://predictome.bu.edu.

All of the life science research web servers published in this and previous issues of Nucleic Acids Research, together with other useful tools, databases and resources for bioinformatics and molecular biology research are freely accessible online through the Bioinformatics Links Directory, http:// bioinformatics.ca/links_directory/. Entirely dependent on user feedback and community input, the Bioinformatics Links Directory exemplifies an open access research tool and resource. With 112 websites featured in the July 2009 Web Server Issue of Nucleic Acids Research, the 2009 update brings the total number of servers listed in the Bioinformatics Links Directory close to an impressive 1400 links. A complete list of all links listed in this Nucleic Acids Research 2009 Web Server Issue can be accessed online at http://bioinfomatics.ca/links_ directory/narweb2009/. The 2009 update of the Bioinformatics Links Directory, which includes the Web Server list and summaries, is also available online at the Nucleic Acids Research website, http://nar.oxfordjournals.org/.

The Bioinformatics Links Directory, http://bioinformatics.ca/links_directory/, is an online resource for public access to all of the life science research web servers published in this and previous issues of Nucleic Acids Research, together with other useful tools, databases and resources for bioinformatics and molecular biology research. Dependent on community input and development, the Bioinformatics Links Directory exemplifies an open access research tool and resource. The 2008 update includes the 94 web servers featured in the July 2008 Web Server issue of Nucleic Acids Research, bringing the total number of servers listed in the Bioinformatics Links Directory to over 1200 links. A complete list of all links listed in this Nucleic Acids Research 2008 Web Server issue can be accessed online at http://bioinfomatics.ca/links_directory/narweb2008/. The 2008 update of the Bioinformatics Links Directory, which includes the Web Server list and summaries, is also available online at the Nucleic Acids Research website, http://nar.oxfordjournals.org/.

The Bioinformatics Links Directory is a public online resource that lists the servers published in this and all previously published Nucleic Acids Research Web Server issues together with other useful tools, databases and resources for bioinformatics and molecular biology research. This rich directory of tools and websites can be browsed and searched with all listed links freely accessible to the public. The 2006 update includes the 149 websites highlighted in the July 2006 issue of Nucleic Acids Research and brings the total number of servers listed in the Bioinformatics Links Directory to over 1000 links. To aid navigation through this growing resource, all link entries contain a brief synopsis, a citation list and are classified by function in descriptive biological categories. The most up-to-date version of this actively maintained listing of bioinformatics resources is available at the Bioinformatics Links Directory website, http://bioinformatics.ubc.ca/resources/links_directory/. A complete list of all links listed in this Nucleic Acids Research 2006 Web Server issue can be accessed online at http://bioinformatics.ubc.ca/resources/links_directory/narweb2006/. The 2006 update of the Bioinformatics Links Directory, which includes the Web Server list and summaries, is also available online at the Nucleic Acids Research website, http://nar.oupjournals.org/.

The Links Directory at Bioinformatics.ca continues its collaboration with Nucleic Acids Research to jointly publish and compile a freely accessible, online collection of tools, databases and resource materials for bioinformatics and molecular biology research. The July 2010 Web Server issue of Nucleic Acids Research adds an additional 115 web server tools and 7 updates to the directory at http://bioinformatics.ca/links_directory/, bringing the total number of servers listed close to an impressive 1500 links. The Bioinformatics Links Directory represents an excellent community resource for locating bioinformatic tools and databases to aid one’s research, and in this context bioinformatic education needs and initiatives are discussed. A complete list of all links featured in this Nucleic Acids Research 2010 Web Server issue can be accessed online at http://bioinformatics.ca/links_directory/narweb2010/. The 2010 update of the Bioinformatics Links Directory, which includes the Web Server list and summaries, is also available online at the Nucleic Acids Research website, http://nar.oxfordjournals.org/.

The Bioinformatics Links Directory is an online community resource that contains a directory of freely available tools, databases, and resources for bioinformatics and molecular biology research. The listing of the servers published in this and previous issues of Nucleic Acids Research together with other useful tools and websites represents a rich repository of resources that are openly provided to the research community using internet technologies. The 166 servers highlighted in the 2005 90002 are included in the more than 700 links to useful online resources that are currently contained within the descriptive biological categories of the Bioinformatics Links Directory. This curated listing of bioinformatics resources is available online at the Bioinformatics Links Directory web site, http://bioinformatics.ubc.ca/resources/links_directory/. A complete listing of the 2005 Nucleic Acids Research 90002 servers is available online at the Nucleic Acids web site, http://nar.oupjournals.org/, and on the Bioinformatics Links Directory web site, http://bioinformatics.ubc.ca/resources/links_directory/narweb2005/.

With so many databases available for research in the Human Genome Project, it is crucial to efficiently relate information from different resources. For that purpose, we maintain Virgil, a database of rich links for data browsing, data analysis and database interconnection. Virgil current version contains more than 40 000 rich links from five major databases: SWISS-PROT, GenBank, PDB, GDB and OMIM. Materials described in this paper are available from http://www.infobiogen.fr/services/virgil/

The Database of Ribosomal Cross-links (DRC) was created in 1997. Here we describe new data incorporated into this database and several new features of the DRC. The DRC is freely available via World Wide Web at http://visitweb.com/database/ or http://www. mpimg-berlin-dahlem.mpg.de/ approximately ag_ribo/ag_brimacombe/drc/

Mitochondria are the only organelles in the animal cells that have their own genome. Due to a key role in energy production, generation of damaging factors (ROS, heat), and apoptosis, mitochondria and mtDNA in particular have long been considered one of the major players in the mechanisms of aging, longevity and age-related diseases. The rapidly increasing number of species with fully sequenced mtDNA, together with accumulated data on longevity records, provides a new fascinating basis for comparative analysis of the links between mtDNA features and animal longevity. To facilitate such analyses and to support the scientific community in carrying these out, we developed the MitoAge database containing calculated mtDNA compositional features of the entire mitochondrial genome, mtDNA coding (tRNA, rRNA, protein-coding genes) and non-coding (D-loop) regions, and codon usage/amino acids frequency for each protein-coding gene. MitoAge includes 922 species with fully sequenced mtDNA and maximum lifespan records. The database is available through the MitoAge website (www.mitoage.org or www.mitoage.info), which provides the necessary tools for searching, browsing, comparing and downloading the data sets of interest for selected taxonomic groups across the Kingdom Animalia. The MitoAge website assists in statistical analysis of different features of the mtDNA and their correlative links to longevity.

MoonProt 2.0 (http://moonlightingproteins.org) is an updated, comprehensive and open-access database storing expert-curated annotations for moonlighting proteins. Moonlighting proteins contain two or more physiologically relevant distinct functions performed by a single polypeptide chain. Here, we describe developments in the MoonProt website and database since our previous report in the Database Issue of Nucleic Acids Research. For this V 2.0 release, we expanded the number of proteins annotated to 370 and modified several dozen protein annotations with additional or updated information, including more links to protein structures in the Protein Data Bank, compared with the previous release. The new entries include more examples from humans and several model organisms, more proteins involved in disease, and proteins with different combinations of functions. The updated web interface includes a search function using BLAST to enable users to search the database for proteins that share amino acid sequence similarity with a protein of interest. The updated website also includes additional background information about moonlighting proteins and an expanded list of links to published articles about moonlighting proteins.

We have created tRFdb, the first database of transfer RNA fragments (tRFs), available at http://genome.bioch.virginia.edu/trfdb/. With over 100 small RNA libraries analyzed, the database currently contains the sequences and read counts of the three classes of tRFs for eight species: R. sphaeroides, S. pombe, D. melanogaster, C. elegans, Xenopus, zebra fish, mouse and human, for a total of 12,877 tRFs. The database can be searched by tRF ID or tRF sequence, and the results can be limited by organism. The search results show the genome coordinates and names of the tRNAs the sequence may derive from, and there are links for the sequence of the tRF and parental tRNA, and links for the read counts in all the corresponding small RNA libraries. As a case study for how this database may be used, we have shown that a certain class of tRFs, tRF-1s, is highly upregulated in B-cell malignancies.

RNA splicing is an important aspect of gene regulation in many organisms. Splicing of RNA is regulated by complicated mechanisms involving numerous RNA-binding proteins and the intricate network of interactions among them. Mutations in cis-acting splicing elements or its regulatory proteins have been shown to be involved in human diseases. Defects in pre-mRNA splicing process have emerged as a common disease-causing mechanism. Therefore, a database integrating RNA splicing and disease associations would be helpful for understanding not only the RNA splicing but also its contribution to disease. In SpliceDisease database, we manually curated 2337 splicing mutation disease entries involving 303 genes and 370 diseases, which have been supported experimentally in 898 publications. The SpliceDisease database provides information including the change of the nucleotide in the sequence, the location of the mutation on the gene, the reference Pubmed ID and detailed description for the relationship among gene mutations, splicing defects and diseases. We standardized the names of the diseases and genes and provided links for these genes to NCBI and UCSC genome browser for further annotation and genomic sequences. For the location of the mutation, we give direct links of the entry to the respective position/region in the genome browser. The users can freely browse, search and download the data in SpliceDisease at http://cmbi.bjmu.edu.cn/sdisease.

FunCoup (http://FunCoup.sbc.su.se) is a database that maintains and visualizes global gene/protein networks of functional coupling that have been constructed by Bayesian integration of diverse high-throughput data. FunCoup achieves high coverage by orthology-based integration of data sources from different model organisms and from different platforms. We here present release 2.0 in which the data sources have been updated and the methodology has been refined. It contains a new data type Genetic Interaction, and three new species: chicken, dog and zebra fish. As FunCoup extensively transfers functional coupling information between species, the new input datasets have considerably improved both coverage and quality of the networks. The number of high-confidence network links has increased dramatically. For instance, the human network has more than eight times as many links above confidence 0.5 as the previous release. FunCoup provides facilities for analysing the conservation of subnetworks in multiple species. We here explain how to do comparative interactomics on the FunCoup website. AuthorCount; 6

Phytohormone studies enlightened our knowledge of plant responses to various changes. To provide a systematic and comprehensive view of genes participating in plant hormonal regulation, an online accessible database Arabidopsis Hormone Database (AHD) has been developed, which is a collection of hormone related genes of the model organism Arabidopsis thaliana (AHRGs). Recently we updated our database from AHD to a new version AHD2.0 by adding several pronounced features: (i) updating our collection of AHRGs based on most recent publications as well as constructing elaborate schematic diagrams of each hormone biosynthesis and signaling pathways; (ii) adding orthologs of sequenced plants listed in OrthoMCL-DB to each AHRG in the updated database; (iii) providing predicted miRNA splicing site(s) for each AHRG; (iv) integrating genes that genetically interact with each AHRG according to literatures mining; (v) providing links to a powerful online analysis platform WebLab for the convenience of in-time bioinformatics analysis and (vi) providing links to widely used protein databases and integrating more expression profiling information that would facilitate users for a more systematic and integrative analysis related to phytohormone research.

One of the greatest challenges in bioinformatics is to shed light on the relationship between genomic and chemical significances of metabolic pathways. Here, we demonstrate two types of chemical structure search servers: SIMCOMP (http://www.genome.jp/tools/simcomp/) for the chemical similarity search and SUBCOMP (http://www.genome.jp/tools/subcomp/) for the chemical substructure search, where both servers provide links to the KEGG PATHWAY and BRITE databases. The SIMCOMP is a graph-based method for searching the maximal common subgraph isomorphism by finding the maximal cliques in the association graph. In contrast, the SUBCOMP is an extended method for solving the subgraph isomorphism problem. The obtained links to PATHWAY or BRITE databases can be used to interpret as the biological meanings of chemical structures from the viewpoint of the various biological functions including metabolic networks.

The plant organelles database (PODB; http://podb.nibb.ac.jp/Organellome) was built to promote a comprehensive understanding of organelle dynamics, including organelle function, biogenesis, differentiation, movement and interactions with other organelles. This database consists of three individual parts, the organellome database, the functional analysis database and external links to other databases and homepages. The organellome database provides images of various plant organelles that were visualized with fluorescent and nonfluorescent probes in various tissues of several plant species at different developmental stages. The functional analysis database is a collection of protocols for plant organelle research. External links give access primarily to other databases and Web pages with information on transcriptomes and proteomes. All the data and protocols in the organellome database and the functional analysis database are populated by direct submission of experimentally determined data from plant researchers and can be freely downloaded. Our database promotes the exchange of information between plant organelle researchers for the comprehensive study of the organelle dynamics that support integrated functions in higher plants. We would also appreciate contributions of data and protocols from all plant researchers to maximize the usefulness of the database.

Phospho.ELM is a manually curated database of eukaryotic phosphorylation sites. The resource includes data collected from published literature as well as high-throughput data sets. The current release of Phospho.ELM (version 7.0, July 2007) contains 4078 phospho-protein sequences covering 12 025 phospho-serine, 2362 phospho-threonine and 2083 phospho-tyrosine sites. The entries provide information about the phosphorylated proteins and the exact position of known phosphorylated instances, the kinases responsible for the modification (where known) and links to bibliographic references. The database entries have hyperlinks to easily access further information from UniProt, PubMed, SMART, ELM, MSD as well as links to the protein interaction databases MINT and STRING. A new BLAST search tool, complementary to retrieval by keyword and UniProt accession number, allows users to submit a protein query (by sequence or UniProt accession) to search against the curated data set of phosphorylated peptides. Phospho.ELM is available on line at: http://phospho.elm.eu.org

Asterias (http://www.asterias.info) is an opensource, web-based, suite for the analysis of gene expression and aCGH data. Asterias implements validated statistical methods, and most of the applications use parallel computing, which permits taking advantage of multicore CPUs and computing clusters. Access to, and further analysis of, additional biological information and annotations (PubMed references, Gene Ontology terms, KEGG and Reactome pathways) are available either for individual genes (from clickable links in tables and figures) or sets of genes. These applications cover from array normalization to imputation and preprocessing, differential gene expression analysis, class and survival prediction and aCGH analysis. The source code is available, allowing for extention and reuse of the software. The links and analysis of additional functional information, parallelization of computation and open-source availability of the code make Asterias a unique suite that can exploit features specific to web-based environments, Funding was provided by Fundación de Investigación Médica Mutua Madrileña and Project TIC2003-09331- C02-02 of the Spanish Ministry of Education and Science (MEC). R.D.U. is partially supported by the Ramón y Cajal programme of the Spanish MEC. Applications are running on clusters of machines purchased with funds from the RTICCC from the Spanish FIS. Funding to pay the Open Access publication charges for this article was provided by the Fundación de Investigación Médica Mutua Madrileña

Hematopoiesis describes the process of the normal formation and development of blood cells, involving both proliferation and differentiation from stem cells. Abnormalities in this developmental program yield blood cell diseases, such as leukemia. Although, in recent years, extensive molecular research in normal hematopoietic development has characterized transcription factors and their binding sites in the target gene promoters, the information generated is highly fragmented. In order to integrate this important regulatory information with the corresponding genomic sequences, we have developed a new database called Hematopoiesis Promoter Database (HemoPDB). HemoPDB is a comprehensive resource focused on transcriptional regulation during hematopoietic development and associated aberrances that result in malignancy. HemoPDB (version 1.0) contains 246 promoter sequences and 604 experimentally known cis-regulatory elements of 187 different transcription factors, with links to published references. Orthologous promoters from different species are linked with each other and displayed in the same database record, accompanied by a visual image of the promoters and corresponding annotations of cis-regulatory elements. HemoPDB may be searched for the promoter of a specific gene, transcription factors and target genes, and genes that are expressed in a certain cell type or lineage, through a user-friendly web interface at http://bioinformatics.med.ohio-state.edu/HemoPDB. Links to the documentation and other technical details are provided on this website.

Saccharomyces cerevisiae, i.e. baker's yeast, is a widely studied model organism in eukaryote genetics because of its simple protocols for genetic manipulation and phenotype profiling. The high abundance of publicly available data that has been generated through diverse 'omics' approaches has led to the use of yeast for many systems biology studies, including large-scale gene network modeling to better understand the molecular basis of the cellular phenotype. We have previously developed a genome-scale gene network for yeast, YeastNet v2, which has been used for various genetics and systems biology studies. Here, we present an updated version, YeastNet v3 (available at http://www.inetbio.org/yeastnet/), that significantly improves the prediction of gene-phenotype associations. The extended genome in YeastNet v3 covers up to 5818 genes (similar to 99% of the coding genome) wired by 362 512 functional links. YeastNet v3 provides a new web interface to run the tools for network-guided hypothesis generations. YeastNet v3 also provides edge information for all data-specific networks (similar to 2 million functional links) as well as the integrated networks. Therefore, users can construct alternative versions of the integrated network by applying their own data integration algorithm to the same data-specific links.

As a result of the continuous evolution of drug resistant bacteria, new antibiotics are urgently needed. Encoded by biosynthetic gene clusters (BGCs), antibiotic compounds are mostly produced by bacteria. With the exponential increase in the number of publicly available, sequenced genomes and the advancements of BGC prediction tools, genome mining algorithms have uncovered millions of uncharacterized BGCs for further evaluation. Since compound identification and characterization remain bottlenecks, a major challenge is prioritizing promising BGCs. Recently, researchers adopted self-resistance based strategies allowing them to predict the biological activities of natural products encoded by uncharacterized BGCs. Since 2017, the Antibiotic Resistant Target Seeker (ARTS) facilitated this so-called target-directed genome mining (TDGM) approach for the prioritization of BGCs encoding potentially novel antibiotics. Here, we present the ARTS database, available at https://arts-db.ziemertlab.com/. The ARTS database provides pre-computed ARTS results for >70,000 genomes and metagenome assembled genomes in total. Advanced search queries allow users to rapidly explore the fundamental criteria of TDGM such as BGC proximity, duplication and horizontal gene transfers of essential housekeeping genes. Furthermore, the ARTS database provides results interconnected throughout the bacterial kingdom as well as links to known databases in natural product research.

The 2014 Web Server Issue of Nucleic Acids Research is the 12th in a series of annual special issues dedicated to web-based software resources for analysis and visualization of molecular biology data. It is freely available online under NAR's open access policy. The present issue reports on 80 web servers. Topics. This year's special emphasis is on tools for synthetic biology design, analysis of high throughput sequencing data, network and pathway analysis, and biological text mining. A total of 19 papers deal with these topics. The other major topic categories include analysis involving DNA and RNA (12 papers); gene prioritization (5 papers); drug-target interactions (5 papers); and proteins, including structure, ligand binding, and functional site prediction (24 papers). The 2014 Web Server issue continues the presentation of two special categories, one for stand-alone programs that analyze high-throughput data, such as high throughput sequencing data, and one for large collections of web services for automated analyses that can be utilized programmatically rather than through manual interaction with a web browser. Six papers fall in these categories. Acknowledgements. The Web Server issue would not be possible without the work of the many scientists and programmers who have provided us with outstanding, freely available web resources, and the conscientious efforts of literally hundreds of reviewers. My work was made possible, first, by the editorial assistance of Fay Oppenheim. Thank you. Thanks also to Allyson Byrd and Joe Perez-Rogers, PhD students in the Boston University Bioinformatics Program, and Artem Mamonov, Research Associate in the BU department of Biomedical Engineering, for their outstanding assistance in evaluating the proposal websites (Figure 1). Additional thanks to Martine Bernardes-Silva, Editorial Manager, NAR, and Jennifer Boyd and the staff at Oxford University Press. Instructions for Submissions. To streamline the review process, authors are required to send a one-page summary of their web server to the editor, Dr. Gary Benson (ude.ub@vrsbwran), for pre-approval prior to manuscript submission. For the 2014 issue, 269 summaries were submitted and 106, or 39%, were approved for manuscript submission. Of those approved, 80, or 75%, were ultimately accepted for publication. Review of a summary includes evaluation of the proposal and extensive testing of web server functionality. The key criteria for pre-approval are high scientific quality, wide interest, the ability to do computations on user-submitted data, and a well designed, well implemented, and fully functional website. Note that there is a minimum two-year interval before publication in the Web Server issue for web servers, or essentially similar web servers, that have been the subject of a previous publication, including publication in journals other than NAR. With respect to the website, the following are guidelines for approval. It should have an easy-to-find submission page with a simple mechanism for loading test data and setting test parameters. The preferred method is one-click loading. Additional mechanisms that assist the user in submitting data should be implemented where appropriate, for example, automatic download of a pdb structure file once the user has entered the appropriate identifier. Output should be dynamic and rich in detail. Wherever possible, supporting evidence used in calculations and/or links to external databases containing additional information should be provided. Numerical, textual, and visual output should be mixed and any visualization tools that add information or increase the user's understanding should be utilized. Note that output consisting merely of a few numerical values, a static spreadsheet, or a series of files to be opened in other programs will not be approved. Web servers that do not finish their calculations immediately must implement a mechanism for returning results to the user. Notification by email may be provided as an option, but an alternative that returns a web link at the time of data submission, which the user can then bookmark and access at a later time, is required. This link should ideally report the status of the job (queued, running, finished). Websites that require a guest login will not be approved. Note that uploaded data and the results of analysis for each user must be private and not viewable by other users. The website should be supported by an extensive help section or tutorial that guides the user through the submission process, contains details about input file formats and parameters, and importantly, explains the meaning of the output. Whenever possible, the help pages should link to dynamic output examples similar to those provided by the website. Text and figure help pages, rather than video tutorials, are preferred because they simplify quick look-up. Any proposal for a web server that is predictive must include details on validation of predictions from new data not used in training. N-fold cross validation methods will not be considered sufficient. Details should include size and composition of the validation data set (number of positive and negative cases), and several measures of predictive performance, including sensitivity, specificity, and precision. Proposals are frequently rejected for lack of adequate prediction validation information. Websites not clearly designed to accept and analyze user-submitted data will be rejected. This applies to those established primarily for lookup or exploration in a data set, or serve the function of “data aggregators.” Authors of websites that provide novel data should consider the NAR Database Issue as a possible venue (see the instructions at http://www.oxfordjournals.org/our_journals/nar/for_authors/msprep_database.html). Proposals that describe a new analysis method are generally not appropriate for the Web Server issue because limited space makes adequate method description and validation problematic. Authors of such methods might instead consider sending their manuscript to NAR as a regular computational biology paper (see the instructions for authors at http://www.oxfordjournals.org/our_journals/nar/for_authors/criteria_scope.html#Computational%20Biology). Figure 1. Allyson Byrd and Joe Perez-Rogers, PhD students in the Boston University Bioinformatics Graduate Program, and Artem Mamonov, Research Associate in the BU Department of Biomedical Engineering, helped with testing the Web Server proposal websites. Special Emphasis for 2015. For the 2015 issue, the topics of special emphasis will be tools for synthetic biology design, analysis of high throughput sequencing data, and network and pathway analysis. Deadlines for 2015. Authors wishing to submit manuscripts for the 2015 Web Server issue must submit their one page proposal along with the URL address of the fully functional website to ude.ub@vrsbwran by 31 December 2014. Detailed instructions and requirements are presented at http://www.oxfordjournals.org/nar/for_authors/submission_webserver.html. This information should be consulted before sending in the summary. The deadline for submission of articles is 31 January 2015. Requirement for References Links. Manuscripts submitted for the 2015 issue must format their References section to include active links to electronic versions of the cited papers, including links to PubMed, PubMed Central, and a DOI link. Instructions for incorporating these links into the manuscript are presented at http://www.oxfordjournals.org/nar/for_authors/submission_webserver.html.

The iProClass database is an integrated resource that provides comprehensive family relationships and structural and functional features of proteins, with rich links to various databases. It is extended from ProClass, a protein family database that integrates PIR superfamilies and PROSITE motifs. The iProClass currently consists of more than 200 000 non-redundant PIR and SWISS-PROT proteins organized with more than 28 000 superfamilies, 2600 domains, 1300 motifs, 280 post-translational modification sites and links to more than 30 databases of protein families, structures, functions, genes, genomes, literature and taxonomy. Protein and family summary reports provide rich annotations, including membership information with length, taxonomy and keyword statistics, full family relationships, comprehensive enzyme and PDB cross-references and graphical feature display. The database facilitates classification-driven annotation for protein sequence databases and complete genomes, and supports structural and functional genomic research. The iProClass is implemented in Oracle 8i object-relational system and available for sequence search and report retrieval at http://pir.georgetow n.edu/iproclass/.

HubMed is an alternative search interface to the PubMed database of biomedical literature, incorporating external web services and providing functions to improve the efficiency of literature search, browsing and retrieval. Users can create and visualize clusters of related articles, export citation data in multiple formats, receive daily updates of publications in their areas of interest, navigate links to full text and other related resources, retrieve data from formatted bibliography lists, navigate citation links and store annotated metadata for articles of interest. HubMed is freely available at http://www.hubmed.org/.

IMGT/GENE-DB is the comprehensive IMGT genome database for immunoglobulin (IG) and T cell receptor (TR) genes from human and mouse, and, in development, from other vertebrates. IMGT/GENE-DB is the international reference for the IG and TR gene nomenclature and works in close collaboration with the HUGO Nomenclature Committee, Mouse Genome Database and genome committees for other species. IMGT/GENE-DB allows a search of IG and TR genes by locus, group and subgroup, which are CLASSIFICATION concepts of IMGT-ONTOLOGY. Short cuts allow the retrieval gene information by gene name or clone name. Direct links with configurable URL give access to information usable by humans or programs. An IMGT/GENE-DB entry displays accurate gene data related to genome (gene localization), allelic polymorphisms (number of alleles, IMGT reference sequences, functionality, etc.) gene expression (known cDNAs), proteins and structures (Protein displays, IMGT Colliers de Perles). It provides internal links to the IMGT sequence databases and to the IMGT Repertoire Web resources, and external links to genome and generalist sequence databases. IMGT/GENE-DB manages the IMGT reference directory used by the IMGT tools for IG and TR gene and allele comparison and assignment, and by the IMGT databases for gene data annotation. IMGT/GENE-DB is freely available at http://imgt.cines.fr.

Long non-coding RNAs (lncRNAs) play important functional roles in many diverse biological processes. However, not all expressed lncRNAs are functional. Thus, it is necessary to manually collect all experimentally validated functional lncRNAs (EVlncRNA) with their sequences, structures, and functions annotated in a central database. The first release of such a database (EVLncRNAs) was made using the literature prior to 1 May 2016. Since then (till 15 May 2020), 19 245 articles related to lncRNAs have been published. In EVLncRNAs 2.0, these articles were manually examined for a major expansion of the data collected. Specifically, the number of annotated EVlncRNAs, associated diseases, lncRNA-disease associations, and interaction records were increased by 260%, 320%, 484% and 537%, respectively. Moreover, the database has added several new categories: 8 lncRNA structures, 33 exosomal lncRNAs, 188 circular RNAs, and 1079 drug-resistant, chemoresistant, and stress-resistant lncRNAs. All records have checked against known retraction and fake articles. This release also comes with a highly interactive visual interaction network that facilitates users to track the underlying relations among lncRNAs, miRNAs, proteins, genes and other functional elements. Furthermore, it provides links to four new bioinformatics tools with improved data browsing and searching functionality. EVLncRNAs 2.0 is freely available at https://www.sdklab-biophysics-dzu.net/EVLncRNAs2/.

The Database of Antimicrobial Activity and Structure of Peptides (DBAASP) is an open-access, comprehensive database containing information on amino acid sequences, chemical modifications, 3D structures, bioactivities and toxicities of peptides that possess antimicrobial properties. DBAASP is updated continuously, and at present, version 3.0 (DBAASP v3) contains >15 700 entries (8000 more than the previous version), including >14 500 monomers and nearly 400 homo- and hetero-multimers. Of the monomeric antimicrobial peptides (AMPs), >12 000 are synthetic, about 2700 are ribosomally synthesized, and about 170 are non-ribosomally synthesized. Approximately 3/4 of the entries were added after the initial release of the database in 2014 reflecting the recent sharp increase in interest in AMPs. Despite the increased interest, adoption of peptide antimicrobials in clinical practice is still limited as a consequence of several factors including side effects, problems with bioavailability and high production costs. To assist in developing and optimizing de novo peptides with desired biological activities, DBAASP offers several tools including a sophisticated multifactor analysis of relevant physicochemical properties. Furthermore, DBAASP has implemented a structure modelling pipeline that automates the setup, execution and upload of molecular dynamics (MD) simulations of database peptides. At present, >3200 peptides have been populated with MD trajectories and related analyses that are both viewable within the web browser and available for download. More than 400 DBAASP entries also have links to experimentally determined structures in the Protein Data Bank. DBAASP v3 is freely accessible at http://dbaasp.org.

CRISPR genetic screens in cancer cell models are a powerful tool to elucidate oncogenic mechanisms and to identify promising therapeutic targets. The Project Score database (https://score.depmap.sanger.ac.uk/) uses genome-wide CRISPR–Cas9 dropout screening data in hundreds of highly annotated cancer cell models to identify genes required for cell fitness and prioritize novel oncology targets. The Project Score database currently allows users to investigate the fitness effect of 18 009 genes tested across 323 cancer cell models. Through interactive interfaces, users can investigate data by selecting a specific gene, cancer cell model or tissue type, as well as browsing all gene fitness scores. Additionally, users can identify and rank candidate drug targets based on an established oncology target prioritization pipeline, incorporating genetic biomarkers and clinical datasets for each target, and including suitability for drug development based on pharmaceutical tractability. Data are freely available and downloadable. To enhance analyses, links to other key resources including Open Targets, COSMIC, the Cell Model Passports, UniProt and the Genomics of Drug Sensitivity in Cancer are provided. The Project Score database is a valuable new tool for investigating genetic dependencies in cancer cells and the identification of candidate oncology targets.

Computational analysis of biosynthetic gene clusters (BGCs) has revolutionized natural product discovery by enabling the rapid investigation of secondary metabolic potential within microbial genome sequences. Grouping homologous BGCs into Gene Cluster Families (GCFs) facilitates mapping their architectural and taxonomic diversity and provides insights into the novelty of putative BGCs, through dereplication with BGCs of known function. While multiple databases exist for exploring BGCs from publicly available data, no public resources exist that focus on GCF relationships. Here, we present BiG-FAM, a database of 29,955 GCFs capturing the global diversity of 1,225,071 BGCs predicted from 209,206 publicly available microbial genomes and metagenome-assembled genomes (MAGs). The database offers rich functionalities, such as multi-criterion GCF searches, direct links to BGC databases such as antiSMASH-DB, and rapid GCF annotation of user-supplied BGCs from antiSMASH results. BiG-FAM can be accessed online at https://bigfam.bioinformatics.nl., Graphical Abstract Graphical AbstractConstructed based on a large-scale homology analysis of 1.2 million biosynthetic gene clusters, BiG-FAM provides a platform to explore their genomic diversity and to discover their relationships to newly sequenced ones.

Zebra2 is a highly automated web-tool to search for subfamily-specific and conserved positions (i.e. the determinants of functional diversity as well as the key catalytic and structural residues) in protein superfamilies. The bioinformatic analysis is facilitated by Mustguseal—a companion web-server to automatically collect and superimpose a large representative set of functionally diverse homologs with high structure similarity but low sequence identity to the selected query protein. The results are automatically prioritized and provided at four information levels to facilitate the knowledge-driven expert selection of the most promising positions on-line: as a sequence similarity network; interfaces to sequence-based and 3D-structure-based analysis of conservation and variability; and accompanied by the detailed annotation of proteins accumulated from the integrated databases with links to the external resources. The integration of Zebra2 and Mustguseal web-tools provides the first of its kind out-of-the-box open-access solution to conduct a systematic analysis of evolutionarily related proteins implementing different functions within a shared 3D-structure of the superfamily, determine common and specific patterns of function-associated local structural elements, assist to select hot-spots for rational design and to prepare focused libraries for directed evolution. The web-servers are free and open to all users at https://biokinet.belozersky.msu.ru/zebra2, no login required.

Three-dimensional structures are now known within many protein families and it is quite likely, in searching a sequence database, that one will encounter a homolog with known structure. The goal of Entrez’s 3D-structure database is to make this information, and the functional annotation it can provide, easily accessible to molecular biologists. To this end Entrez’s search engine provides three powerful features. (i) Sequence and structure neighbors; one may select all sequences similar to one of interest, for example, and link to any known 3D structures. (ii) Links between databases; one may search by term matching in MEDLINE, for example, and link to 3D structures reported in these articles. (iii) Sequence and structure visualization; identifying a homolog with known structure, one may view molecular-graphic and alignment displays, to infer approximate 3D structure. In this article we focus on two features of Entrez’s Molecular Modeling Database (MMDB) not described previously: links from individual biopolymer chains within 3D structures to a systematic taxonomy of organisms represented in molecular databases, and links from individual chains (and compact 3D domains within them) to structure neighbors, other chains (and 3D domains) with similar 3D structure. MMDB may be accessed at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Structure.

Mitochondria, besides their central role in energy metabolism, have recently been found to be involved in a number of basic processes of cell life and to contribute to the pathogenesis of many degenerative diseases. All functions of mitochondria depend on the interaction of nuclear and organelle genomes. Mitochondrial genomes have been extensively sequenced and analysed and data have been collected in several specialised databases. In order to collect information on nuclear coded mitochondrial proteins we developed MitoNuc, a database containing detailed information on sequenced nuclear genes coding for mitochondrial proteins in Metazoa. The MitoNuc database can be retrieved through SRS and is available via the web site http://bighost.area.ba.cnr.it/mitochondriome where other mitochondrial databases developed by our group, the complete list of the sequenced mitochondrial genomes, links to other mitochondrial sites and related information, are available. The MitoAln database, related to MitoNuc in the previous release, reporting the multiple alignments of the relevant homologous protein coding regions, is no longer supported in the present release. In order to keep the links among entries in MitoNuc from homologous proteins, a new field in the database has been defined: the cluster identifier, an alpha numeric code used to identify each cluster of homologous proteins. A comment field derived from the corresponding SWISS-PROT entry has been introduced; this reports clinical data related to dysfunction of the protein. The logic scheme of MitoNuc database has been implemented in the ORACLE DBMS. This will allow the end-users to retrieve data through a friendly interface that will be soon implemented.

The Human Gene Mutation Database (HGMD) represents a comprehensive core collection of data on published germline mutations in nuclear genes underlying human inherited disease. By September 1997, the database contained nearly 12 000 different lesions in a total of 636 different genes, with new entries currently accumulating at a rate of over 2000 per annum. Although originally established for the scientific study of mutational mechanisms in human genes, HGMD has acquired a much broader utility to researchers, physicians and genetic counsellors so that it was made publicly available at http://www.uwcm.ac.uk/uwcm/mg/hgmd0.html in April 1996. Mutation data in HGMD are accessible on the basis of every gene being allocated one web page per mutation type, if data of that type are present. Meaningful integration with phenotypic, structural and mapping information has been accomplished through bi-directional links between HGMD and both the Genome Database (GDB) and Online Mendelian Inheritance in Man (OMIM), Baltimore, USA. Hypertext links have also been established to Medline abstracts through Entrez, and to a collection of 458 reference cDNA sequences also used for data checking. Being both comprehensive and fully integrated into the existing bioinformatics structures relevant to human genetics, HGMD has established itself as the central core database of inherited human gene mutations.

CyanoBase (http://www.kazusa.or.jp/cyano/) is a database containing genomic information on the cyanobacterium Synechocystis sp. strain PCC6803. It furnishes an annotation to each of the 3168 protein genes deduced from the entire nucleotide sequence of this genome. Information on the genome can be directly accessed through three different menus: a clickable physical map of the genome, a gene classification list, and a keyword search menu, all of which are accessible from the main page of the database. The entry page for a gene annotation contains the following information: the location of the gene on the genome, the nucleotide and deduced amino acid sequence of the gene, the result of a similarity search, and the classification of the deduced gene product according to its function. This page has reverse-links to the local physical map and gene classification list so that relevant genes can be searched in terms of their location on the genome and their function. In addition, the main page of CyanoBase provides engines for similarity searches between a query sequence and the entire genome sequence and for keyword searches, in addition to numerous links to pages containing related information.

RNA-seq has been widely used in experimental studies and produced a massive amount of data deposited in public databases. New biological insights can be obtained by retrospective analyses of previously published data. However, the barrier to efficiently utilize these data remains high, especially for those who lack bioinformatics skills and computational resources. We present MetazExp (https://bioinfo.njau.edu.cn/metazExp), a database for gene expression and alternative splicing profiles based on 53 615 uniformly processed publicly available RNA-seq samples from 72 metazoan species. The gene expression and alternative splicing profiles can be conveniently queried by gene IDs, symbols, functional terms and sequence similarity. Users can flexibly customize experimental groups to perform differential and specific expression and alternative splicing analyses. A suite of data visualization tools and comprehensive links with external databases allow users to efficiently explore the results and gain insights. In conclusion, MetazExp is a valuable resource for the research community to efficiently utilize the vast public RNA-seq datasets.

The Clusters of Orthologous Genes (COG) database, also referred to as the Clusters of Orthologous Groups of proteins, was created in 1997 and went through several rounds of updates, most recently, in 2014. The current update, available at https://www.ncbi.nlm.nih.gov/research/COG, substantially expands the scope of the database to include complete genomes of 1187 bacteria and 122 archaea, typically, with a single genome per genus. In addition, the current version of the COGs includes the following new features: (i) the recently deprecated NCBI’s gene index (gi) numbers for the encoded proteins are replaced with stable RefSeq or GenBank\ENA\DDBJ coding sequence (CDS) accession numbers; (ii) COG annotations are updated for >200 newly characterized protein families with corresponding references and PDB links, where available; (iii) lists of COGs grouped by pathways and functional systems are added; (iv) 266 new COGs for proteins involved in CRISPR-Cas immunity, sporulation in Firmicutes and photosynthesis in cyanobacteria are included; and (v) the database is made available as a web page, in addition to FTP. The current release includes 4877 COGs. Future plans include further expansion of the COG collection by adding archaeal COGs (arCOGs), splitting the COGs containing multiple paralogs, and continued refinement of COG annotations.

PULs (polysaccharide utilization loci) are discrete gene clusters of CAZymes (Carbohydrate Active EnZymes) and other genes that work together to digest and utilize carbohydrate substrates. While PULs have been extensively characterized in Bacteroidetes, there exist PULs from other bacterial phyla, as well as archaea and metagenomes, that remain to be catalogued in a database for efficient retrieval. We have developed an online database dbCAN-PUL (http://bcb.unl.edu/dbCAN_PUL/) to display experimentally verified CAZyme-containing PULs from literature with pertinent metadata, sequences, and annotation. Compared to other online CAZyme and PUL resources, dbCAN-PUL has the following new features: (i) Batch download of PUL data by target substrate, species/genome, genus, or experimental characterization method; (ii) Annotation for each PUL that displays associated metadata such as substrate(s), experimental characterization method(s) and protein sequence information, (iii) Links to external annotation pages for CAZymes (CAZy), transporters (UniProt) and other genes, (iv) Display of homologous gene clusters in GenBank sequences via integrated MultiGeneBlast tool and (v) An integrated BLASTX service available for users to query their sequences against PUL proteins in dbCAN-PUL. With these features, dbCAN-PUL will be an important repository for CAZyme and PUL research, complementing our other web servers and databases (dbCAN2, dbCAN-seq).

The 2019 Nucleic Acids Research (NAR) Database Issue contains 168 papers spanning molecular biology. Among them, 64 are new and another 92 are updates describing resources that appeared in the Issue previously. The remaining 12 are updates on databases most recently published elsewhere. This Issue contains two Breakthrough articles, on the Virtual Metabolic Human (VMH) database which links human and gut microbiota metabolism with diet and disease, and Vibrism DB, a database of mouse brain anatomy and gene (co-)expression with sophisticated visualization and session sharing. Major returning nucleic acid databases include RNAcentral, miRBase and LncRNA2Target. Protein sequence databases include UniProtKB, InterPro and Pfam, while wwPDB and RCSB cover protein structure. STRING and KEGG update in the section on metabolism and pathways. Microbial genomes are covered by IMG/M and resources for human and model organism genomics include Ensembl, UCSC Genome Browser, GENCODE and Flybase. Genomic variation and disease are well-covered by GWAS Catalog, PopHumanScan, OMIM and COSMIC, CADD being another major newcomer. Major new proteomics resources reporting here include iProX and jPOSTdb. The entire database issue is freely available online on the NAR website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been updated, reviewing 506 entries, adding 66 new resources and eliminating 147 discontinued URLs, bringing the current total to 1613 databases. It is available at http://www.oxfordjournals.org/nar/database/c.

International audience; Lectins, and related receptors such as adhesins and toxins, are glycan-binding proteins from all origins that decipher the glycocode, i.e. the structural information encoded in the conformation of complex carbohydrates present on the surface of all cells. Lectins are still poorly classified and annotated, but since their functions are based on ligand recognition, their 3D-structures provide a solid foundation for characterization. UniLectin3D is a curated database that classifies lectins on origin and fold, with cross-links to literature, other databases in glycosciences and functional data such as known specificity. The database provides detailed information on lectins, their bound glycan ligands, and features their interactions using the Protein-Ligand Interaction Profiler (PLIP) server. Special care was devoted to the description of the bound glycan ligands with the use of simple graphical representation and numerical format for cross-linking to other databases in glyco-science. We conceived the design of the database architecture and the navigation tools to account for all organisms, as well as to search for oligosaccharide epitopes complexed within specified binding sites. UniLectin3D is accessible at https://www.unilectin. eu/unilectin3D.

Due to the involvement of G protein-coupled receptors (GPCRs) in most of the physiological and pathological processes in humans they have been attracting a lot of attention from pharmaceutical industry as well as from scientific community. Therefore, the need for new, high quality structures of GPCRs is enormous. The updated homology modeling service GPCRM (http://gpcrm.biomodellab.eu/) meets those expectations by greatly reducing the execution time of submissions (from days to hours/minutes) with nearly the same average quality of obtained models. Additionally, due to three different scoring functions (Rosetta, Rosetta-MP, BCL::Score) it is possible to select accurate models for the required purposes: the structure of the binding site, the transmembrane domain or the overall shape of the receptor. Currently, no other web service for GPCR modeling provides this possibility. GPCRM is continually upgraded in a semi-automatic way and the number of template structures has increased from 20 in 2013 to over 90 including structures the same receptor with different ligands which can influence the structure not only in the on/off manner. Two types of protein viewers can be used for visual inspection of obtained models. The extended sortable tables with available templates provide links to external databases and display ligand–receptor interactions in visual form.

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, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities.

The Protein Data Bank in Europe (PDBe, pdbe.org) is actively engaged in the deposition, annotation, remediation, enrichment and dissemination of macromolecular structure data. This paper describes new developments and improvements at PDBe addressing three challenging areas: data enrichment, data dissemination and functional reusability. New features of the PDBe Web site are discussed, including a context dependent menu providing links to raw experimental data and improved presentation of structures solved by hybrid methods. The paper also summarizes the features of the LiteMol suite, which is a set of services enabling fast and interactive 3D visualization of structures, with associated experimental maps, annotations and quality assessment information. We introduce a library of Web components which can be easily reused to port data and functionality available at PDBe to other services. We also introduce updates to the SIFTS resource which maps PDB data to other bioinformatics resources, and the PDBe REST API.

Europe PMC (https://europepmc.org) is a comprehensive resource of biomedical research publications that offers advanced tools for search, retrieval, and interaction with the scientific literature. This article outlines new developments since 2014. In addition to delivering the core database and services, Europe PMC focuses on three areas of development: individual user services, data integration, and infrastructure to support text and data mining. Europe PMC now provides user accounts to save search queries and claim publications to ORCIDs, as well as open access profiles for authors based on public ORCID records. We continue to foster connections between scientific data and literature in a number of ways. All the data behind the paper - whether in structured archives, generic archives or as supplemental files - are now available via links to the BioStudies database. Text-mined biological concepts, including database accession numbers and data DOIs, are highlighted in the text and linked to the appropriate data resources. The SciLite community annotation platform accepts text-mining results from various contributors and overlays them on research articles as licence allows. In addition, text miners and developers can access all open content via APIs or via the FTP site.

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.

The Membranome database was developed to assist analysis and computational modeling of single-pass (bitopic) transmembrane (TM) proteins and their complexes by providing structural information about these proteins on a genomic scale. The database currently collects data on >6000 bitopic proteins from Homo sapiens, Arabidopsis thaliana, Dictyostelium discoideum, Saccharomyces cerevisiae, Escherichia coli and Methanocaldococcus jannaschii. It presents the following data: (i) hierarchical classification of bitopic proteins into 15 functional classes, 689 structural superfamilies and 1404 families; (ii) 446 complexes of bitopic proteins with known three-dimensional (3D) structures classified into 129 families; (iii) computationally generated three-dimensional models of TM α-helices positioned in membranes; (iv) amino acid sequences, domain architecture, functional annotation and available experimental structures of bitopic proteins; (v) TM topology and intracellular localization, (vi) physical interactions between proteins from the database along with links to other resources. The database is freely accessible at http://membranome.org. There is a variety of options for browsing, sorting, searching and retrieval of the content, including downloadable coordinate files of TM domains with calculated membrane boundaries.

Soybean (Glycine max) is a legume crop with substantial economic value, providing a source of oil and protein for humans and livestock. More than 50% of edible oils consumed globally are derived from this crop. Soybean plants are also important for soil fertility, as they fix atmospheric nitrogen by symbiosis with microorganisms. The latest soybean genome annotation (version 2.0) lists 56 044 coding genes, yet their functional contributions to crop traits remain mostly unknown. Co-functional networks have proven useful for identifying genes that are involved in a particular pathway or phenotype with various network algorithms. Here, we present SoyNet (available at www.inetbio.org/soynet), a database of co-functional networks for G. max and a companion web server for network-based functional predictions. SoyNet maps 1 940 284 co-functional links between 40 812 soybean genes (72.8% of the coding genome), which were inferred from 21 distinct types of genomics data including 734 microarrays and 290 RNA-seq samples from soybean. SoyNet provides a new route to functional investigation of the soybean genome, elucidating genes and pathways of agricultural importance.

Here we present an updated version of the AU-Rich Element Database (ARED-Plus) that is freely available at http://brp.kfshrc.edu.sa/ared. AREs are conserved sequence elements that were first discovered in the 3′UTR of mammalian transcripts. Over the past years, we compiled a series of ARE databases that revealed the extent and wide distribution of ARE-containing genes. For this update, we adopted an optimized search algorithm with improved specificity and sensitivity in ARE selection. The designation of the different ARE clusters was simplified by directly correlating the number of the ARE cluster to the number of overlapping AUUUA pentamers. Additionally, the new database was expanded to include genes with intronic AREs (pre-mRNAs) and their characteristics since recent observations reported their abundance and biological significance. Several enhancements were incorporated such as customized column view, additional search options and live search functionalities. The new version includes links to AREsite and AREScore, two related ARE assessment algorithms for further evaluation of the ARE characteristics. ARED-Plus now contains an updated repertoire of AREs in the human transcriptome that may be useful in several research fields.