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https://weghornlab.org/software.html

Software tool which derives gene-specific probabilistic estimates of the strength of negative and positive selection in cancer.

Proper citation: CBaSE (RRID:SCR_027765) Copy   

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https://github.com/vanallenlab/comut

Software Python library for creating comutation plots to visualize genomic and phenotypic information. Used for visualizing genomic and phenotypic information via comutation plots.

Proper citation: CoMUT (RRID:SCR_027745) Copy   

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http://wiki.c2b2.columbia.edu/honiglab_public/index.php/Software:Jackal

Jackal is a collection of programs designed for the modeling and analysis of protein structures. Its core program is a versatile homology modeling package. It contains twelve individual programs, each with their own function.

Proper citation: Jackal (RRID:SCR_008665) Copy   

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http://rankprop.gs.washington.edu/svm-fold/

This web server makes predictions of family, superfamily and fold level classifications of proteins based on the Structural Classification of Proteins (SCOP) hierarchy using the Support Vector Machine (SVM) learning algorithm. SVM-FOLD detects subtle protein sequence similarities by learning from all available annotated proteins, as well as utilizing potential hits as identified by PSI-BLAST. Predictions of classes of proteins that do not have any known example with a significant pairwise PSI-BLAST E-value can still be found using SVMs.

Proper citation: SVM-fold: Protein Fold Prediction (RRID:SCR_006834) Copy   

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http://sherlock.ucsf.edu/

Service to discover disease genes in GWAS using eQTL signature matching by simply submitting your list of GWAS associations (SNPs and p-values). It is important to upload all SNPs in your association study, not just the top hits. Sherlock may be able to group multiple lower-confidence SNPs to discover functionally-important genes.

Proper citation: Sherlock (RRID:SCR_001628) Copy   

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http://www.phosphosite.org

A freely accessible on-line systems biology resource devoted to all aspects of protein modification, as well as other post-translational modifications. It provides valuable and unique tools for both cell biologists and mass spectroscopists. PhosphoSite is a human- and mouse-centric database. It includes features such as: viewing the locations of modified residues on molecular models; browsing and searching MS2 records by disease, tissue, and cell line; submitting lists of peptides to identify previously reported genes; searching by sub-cellular localization, treatment, tissues, cell types, cell lines and diseases, and protein types and protein domains; searching for experimentally-verified kinase substrates and viewing preferred substrate motifs; and viewing MS2 spectra for peptides and sites not previously published.

Proper citation: PhosphoSitePlus: Protein Modification Site (RRID:SCR_001837) Copy   

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http://www.dbmi.pitt.edu/nlpfront

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. Repository of de-identified clinical reports available for NLP researchers has been designed. Work with the AMIA NLP working group in designing annotation schemas and obtaining annotations, design a repository for shareable annotations, help design and execute a shared task in IE from clinical reports. The University of Pittsburgh NLP Repository contains clinical reports that are available to the community for NLP research purposes and comprises: # Report Repository - one month of de-identified clinical reports from multiple hospitals and # Annotation Repository - annotations performed on reports from the Report Repository. Anyone performing annotations on reports from the NLP Repository is required to deposit their annotations. The Repository contains reports of the following types generated from multiple hospitals during a single month: * History and Physicals * Progress Notes * Consultation Reports * Radiology Reports * Surgical Pathology Reports * Emergency Department Reports * Discharge Summaries * Operative Reports * Cardiology Reports

Proper citation: Open Clinical Report Repository (RRID:SCR_013585) Copy   

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https://www.nature.com/articles/s41467-018-03367-w

Nanodroplet processing platform for deep and quantitative proteome profiling of 10 to 100 mammalian cells. It enhances efficiency and recovery of sample processing by downscaling processing volumes.

Proper citation: nanoPOTS (RRID:SCR_017129) Copy   

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http://pir.georgetown.edu/pro/

An ontological representation of protein-related entities, explicitly defining them and showing the relationships between them. Each PRO term represents a distinct class of entities (including specific modified forms, orthologous isoforms, and protein complexes) ranging from the taxon-neutral to the taxon-specific. PRO encompasses three sub-ontologies: proteins based on evolutionary relatedness (ProEvo); protein forms produced from a given gene locus (ProForm); and protein-containing complexes (ProComp).

Proper citation: PRO (RRID:SCR_002902) Copy   

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http://compgen.bscb.cornell.edu/phast/

A freely available software package for comparative and evolutionary genomics that consists of about half a dozen major programs, plus more than a dozen utilities for manipulating sequence alignments, phylogenetic trees, and genomic annotations. For the most part, PHAST focuses on two kinds of applications: the identification of novel functional elements, including protein-coding exons and evolutionarily conserved sequences; and statistical phylogenetic modeling, including estimation of model parameters, detection of signatures of selection, and reconstruction of ancestral sequences. It consists of over 60,000 lines of C code.

Proper citation: PHAST (RRID:SCR_003204) Copy   

•   Source: SciCrunch Registry

http://biocyc.org/

A collection of Pathway/Genome Databases which describes the genome and metabolic pathways of a single organism. The BioCyc collection of Pathway/Genome Databases (PGDBs) provides an electronic reference source on the genomes and metabolic pathways of sequenced organisms. BioCyc PGDBs are generated by software that predicts the metabolic pathway complements of completely sequenced organisms from their genome sequences. They also include the results of a number of other computational inference procedures applied to these genomes, including predictions of which genes code for missing enzymes in metabolic pathways, and predicted operons. The BioCyc Web site provides a suite of software tools for database searching and visualization, for omics data analysis, and for comparative genomics and comparative pathway questions. The databases within the BioCyc collection are organized into tiers according to the amount of manual review and updating they have received. Tier 1 PGDBs have been created through intensive manual efforts, and receive continuous updating. Tier 2 PGDBs were computationally generated by the PathoLogic program, and have undergone moderate amounts of review and updating. Tier 3 PGDBs were computationally generated by the PathoLogic program, and have undergone no review and updating. There are 967 DBs in Tier 3. The downloadable version of BioCyc that includes the Pathway Tools software provides more speed and power than the BioCyc Web site.

Proper citation: BioCyc (RRID:SCR_002298) Copy   

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http://sfld.rbvi.ucsf.edu/

A database of hierarchical classification of enzymes that relates specific sequence-structure features to specific chemical capabilities. The SFLD classifies evolutionarily related enzymes according to shared chemical functions and maps these shared functions to conserved active site features. The classification is hierarchical, where broader levels encompass more distantly related proteins with fewer shared features. It thus serves as the analysis and archive site for superfamilies targeted by the Enzyme Function Initiative, and is developed by the Babbitt Laboratory in collaboration with the UCSF Resource for Biocomputing, Visualization, and Informatics. The resource also provides a collection of tools and data for investigating sequence-structure-function relationships and hypothesizing function.

Proper citation: Structure-function linkage database (RRID:SCR_001375) Copy   

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http://www.cpc.unc.edu/projects/addhealth

Longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. Public data on about 21,000 people first surveyed in 1994 are available on the first phases of the study, as well as study design specifications. It also includes some parent and biomarker data. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The restricted-use contract includes four hours of free consultation with appropriate staff; after that, there''s a fee for help. Researchers can also share information through a listserv devoted to the database.

Proper citation: Add Health (National Longitudinal Study of Adolescent Health) (RRID:SCR_007434) Copy   

•   Source: SciCrunch Registry

http://posa.sanfordburnham.org/fatcat-cgi/cgi/FSN/fsn.pl

Flexible Structural Neighborhood is a database of structural neighbors of proteins as seen by FATCAT - a flexible protein structure alignment program. The server accepts either a protein (PDB ID) or a domain (SCOP ID) as a query. For the former case, the server first displays the information of chains and domains of a given protein. Afterwards, users can retrieve similar structures for a domain (if domain information is available, i.e., the protein is collected by SCOP), or for a chain otherwise. The protein structure database we collected for similar structure search includes a representative set at 90% sequence identity of SCOP domains, and of up-to-date PDB entries that are not included in the latest release of SCOP.

Proper citation: FATCAT Flexible Structural Neighborhood (RRID:SCR_007665) Copy   

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http://www.bindingdb.org

Web accessible database of data extracted from scientific literature, focusing on proteins that are drug-targets or candidate drug-targets and for which structural data are present in Protein Data Bank . Website supports query types including searches by chemical structure, substructure and similarity, protein sequence, ligand and protein names, affinity ranges and molecular weight . Data sets generated by BindingDB queries can be downloaded in form of annotated SDfiles for further analysis, or used as basis for virtual screening of compound database uploaded by user. Data are linked to structural data in PDB via PDB IDs and chemical and sequence searches, and to literature in PubMed via PubMed IDs .

Proper citation: BindingDB (RRID:SCR_000390) Copy   

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https://rmats.sourceforge.io

Software tool to detect differential alternative splicing events from RNA-Seq data. Calculates P-value and false discovery rate that difference in isoform ratio of gene between two conditions exceeds given user-defined threshold. From RNA-Seq data can automatically detect and analyze alternative splicing events corresponding to all major types of alternative splicing patterns. Handles replicate RNA-Seq data from both paired and unpaired study design.

Proper citation: rMATS (RRID:SCR_023485) Copy   

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http://biomedicalcomputationreview.org

Magazine published by Simbios, a National NIH Center for Biomedical Computing, covering the latest research wherever computation, biology, and medicine intersect. In addition to disseminating information about the latest research in biomedical computation, they aim to foster community amongst the wide audience interested in any and all aspects of biomedical computing. Whether you are a long time researcher in this area or new to it, please consider joining those who have already started to participate in Biomedical Computation Review. You are encouraged to: * Write a letter to the editor on any relevant topics * Suggest your favorite topics that should receive more attention * Suggest an idea for a feature article * Propose an idea for an Under the Hood tutorial * Tell us any other way in which we can better serve this community

Proper citation: Biomedical Computation Review (RRID:SCR_004866) Copy   

•   Source: SciCrunch Registry

http://www.scandb.org/newinterface/about.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A large-scale database of genetics and genomics data associated to a web-interface and a set of methods and algorithms that can be used for mining the data in it. The database contains two categories of single nucleotide polymorphism (SNP) annotations: # Physical-based annotation where SNPs are categorized according to their position relative to genes (intronic, inter-genic, etc.) and according to linkage disequilibrium (LD) patterns (an inter-genic SNP can be annotated to a gene if it is in LD with variation in the gene). # Functional annotation where SNPs are classified according to their effects on expression levels, i.e. whether they are expression quantitative trait loci (eQTLs) for that gene. SCAN can be utilized in several ways including: (i) queries of the SNP and gene databases; (ii) analysis using the attached tools and algorithms; (iii) downloading files with SNP annotation for various GWA platforms. . eQTL files and reported GWAS from NHGRI may be downloaded., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SCAN (RRID:SCR_005185) Copy   

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http://gila.bioengr.uic.edu/snp/toposnp

A topographic database for analyzing non-synonymous SNPs (nsSNPs) that can be mapped onto known 3D structures of proteins. These include disease- associated nsSNPs derived from the Online Mendelian Inheritance in Man (OMIM) database and other nsSNPs derived from dbSNP, a resource at the National Center for Biotechnology Information that catalogs SNPs. TopoSNP further classifies each nsSNP site into three categories based on their geometric location: those located in a surface pocket or an interior void of the protein, those on a convex region or a shallow depressed region, and those that are completely buried in the interior of the protein structure. These unique geometric descriptions provide more detailed mapping of nsSNPs to protein structures. It also includes relative entropy of SNPs calculated from multiple sequence alignment as obtained from the Pfam database (a database of protein families and conserved protein motifs) as well as manually adjusted multiple alignments obtained from ClustalW. These structural and conservational data can be useful for studying whether nsSNPs in coding regions are likely to lead to phenotypic changes. TopoSNP includes an interactive structural visualization web interface, as well as downloadable batch data.

Proper citation: TopoSNP (RRID:SCR_005572) Copy   

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http://biogps.org/

An extensible and customizable gene annotation portal that emphasizes community extensibility and user customizability. It is a complete resource for learning about gene and protein function. Community extensibility reflects a belief that any BioGPS user should be able to add new content to BioGPS using the simple plugin interface, completely independently of the core developer team. User customizability recognizes that not all users are interested in the same set of gene annotation data, so the gene report layouts enable each user to define the information that is most relevant to them. Currently, BioGPS supports eight species: Human (Homo sapiens), Mouse (Mus musculus), Rat (Rattus norvegicus), Fruitfly (Drosophila melanogaster), Nematode (Caenorhabditis elegans), Zebrafish (Danio rerio), Thale-cress (Arabidopsis thaliana), Frog (Xenopus tropicalis), and Pig (Sus scrofa). BioGPS presents data in an ortholog-centric format, which allows users to display mouse plugins next to human ones. Our data for defining orthologs comes from NCBI's HomoloGene database.

Proper citation: BioGPS: The Gene Portal Hub (RRID:SCR_006433) Copy   

•   Source: SciCrunch Registry