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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
A package of over twenty mass spectrometry-based tools primarily geared toward proteomic data analysis and database mining. It can be run from the command line, but is primarily used through a web browser, and there is a public website that allows anyone to use the software without local installation. Tandem mass spectrometry analysis tools are used for database searching and identification of peptides, including post-translationally modified peptides and cross-linked peptides. Support for isotope and label-free quantification from this type of data is provided. MS-Viewer software allows sharing and displaying of annotated spectra from many different tandem mass spectrometry data analysis packages. Other tools include software for analyzing peptide mass fingerprinting data (MS-Fit); prediction of theoretical fragmentation of peptides (MS-Product); theoretical chemical or enzymatic digestion of proteins (MS-Digest); and theoretical modeling of the isotope distribution of any chemical, including peptides (MS-Isotope). Searches using amino acid sequence can be used to identify homologous peptides in a database (MS-Pattern); the use of the combination of amino acid sequence and masses can be used for homologous peptide and protein identification using MS-Homology. Tandem mass spectrometry peak list files can be filtered for the presence of certain peaks or neutral losses using MS-Filter. Given a list of proteins, MS-Bridge can report all potential cross-linked peptide combinations of a specified mass. Given a precursor peptide mass and information about known amino acid presence, absence, or modifications, MS-Comp can report all amino acid combinations that could lead to the observed mass.
Proper citation: Protein Prospector (RRID:SCR_014558) Copy
https://github.com/bionitio-team/bionitio
Open source software tool to provide template for command line bioinformatics tools in various programming languages. Program reads one or more input FASTA files, computes variety of statistics on each file, and prints tabulated output. Used as basis for learning and as foundation for starting new projects.
Proper citation: Bionitio (RRID:SCR_017259) Copy
https://github.com/smajidian/phaseme
Software tool set to assess quality of per read phasing information and help to reduce errors during this process.
Proper citation: PhaseME (RRID:SCR_018739) Copy
https://github.com/smithlabcode/riborex
Software R package for identification of differential translation from Ribo-seq data. Computational tool for mapping genome wide differences in translation efficiency.
Proper citation: riborex (RRID:SCR_019104) Copy
https://github.com/anuprulez/galaxy_tool_recommendation
Software developed by analyzing workflows composed by researchers on European Galaxy server, using deep learning approach. Used to recommend tools in Galaxy. Gated recurrent units neural network.
Proper citation: Tool recommender system in Galaxy (RRID:SCR_018491) Copy
https://github.com/DReichLab/AdmixTools
Software package that supports formal tests of whether admixture occurred, and makes it possible to infer admixture proportions and dates.
Proper citation: ADMIXTOOLS (RRID:SCR_018495) Copy
https://hoohm.github.io/CITE-seq-Count/
Software python package that allows to count antibody TAGS from CITE-seq and/or cell hashing experiment. Software tool that allows to get UMI counts from single cell protein assay. Used to count (UMI counts) antibody-derived-tags (ADTs) or Cell Hashing tags (HTOs) in raw sequencing reads and build count matrix.
Proper citation: CITE-seq-Count (RRID:SCR_019239) Copy
Software Python package enabling Biological Expression Language to act as semantic integration layer for multi modal and multi scale data sets in life sciences. Used for integrating biological databases and structured data sources in BEL. Has ability to support curation of pathway mappings, integration of pathway databases, and machine learning applications.
Proper citation: Bio2BEL (RRID:SCR_017659) Copy
https://bioconductor.org/packages/EpiDISH/
Software R package provides tools to infer proportions of priori known cell-types present in sample representing mixture of such cell-types. Comparison of reference based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies.
Proper citation: EpiDISH R package (RRID:SCR_018004) Copy
Curated protein-protein and genetic interaction repository of raw protein and genetic interactions from major model organism species, with data compiled through comprehensive curation efforts.
Proper citation: Biological General Repository for Interaction Datasets (BioGRID) (RRID:SCR_007393) Copy
Database on transcriptional regulation in Escherichia coli K-12 containing knowledge manually curated from original scientific publications, complemented with high throughput datasets and comprehensive computational predictions. Graphic and text-integrated environment with friendly navigation where regulatory information is always at hand. They provide integrated views to understand as well as organized knowledge in computable form. Users may submit data to make it publicly available.
Proper citation: RegulonDB (RRID:SCR_003499) Copy
http://diseases.jensenlab.org/
Database that integrates evidence on disease-gene associations from automatic text mining, manually curated literature, cancer mutation data, and genome-wide association studies. It also assigns confidence scores that facilitate comparison of the different types and sources of evidence.
Proper citation: DISEASES (RRID:SCR_015664) Copy
http://img.jgi.doe.gov/cgi-bin/m/main.cgi
Resource for analysis and annotation of genome and metagenome datasets in comprehensive comparative context. IMG provides users with tools for analyzing publicly available genome datasets and metagenome datasets.
Proper citation: IMG System (RRID:SCR_002965) Copy
A curated database that provides comprehensive integrated biological information for Saccharomyces cerevisiae along with search and analysis tools to explore these data. SGD allows researchers to discover functional relationships between sequence and gene products in fungi and higher organisms. The SGD also maintains the S. cerevisiae Gene Name Registry, a complete list of all gene names used in S. cerevisiae which includes a set of general guidelines to gene naming. Protein Page provides basic protein information calculated from the predicted sequence and contains links to a variety of secondary structure and tertiary structure resources. Yeast Biochemical Pathways allows users to view and search for biochemical reactions and pathways that occur in S. cerevisiae as well as map expression data onto the biochemical pathways. Literature citations are provided where available.
Proper citation: SGD (RRID:SCR_004694) Copy
A database of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Users can analyze protein sequences for Pfam matches, view Pfam family annotation and alignments, see groups of related families, look at the domain organization of a protein sequence, find the domains on a PDB structure, and query Pfam by keywords. There are two components to Pfam: Pfam-A and Pfam-B. Pfam-A entries are high quality, manually curated families that may automatically generate a supplement using the ADDA database. These automatically generated entries are called Pfam-B. Although of lower quality, Pfam-B families can be useful for identifying functionally conserved regions when no Pfam-A entries are found. Pfam also generates higher-level groupings of related families, known as clans (collections of Pfam-A entries which are related by similarity of sequence, structure or profile-HMM).
Proper citation: Pfam (RRID:SCR_004726) Copy
http://www.uniprot.org/taxonomy/
NEWT is the taxonomy database maintained by the UniProt group. It integrates taxonomy data compiled in the NCBI database and data specific to the UniProt Knowledgebase. Browse by hierarchy, List all, or Complete proteomes. Organisms are classified in a hierarchical tree structure. Our taxonomy database contains every node (taxon) of the tree. UniProtKB taxonomy data is manually curated: next to manually verified organism names, we provide a selection of external links, organism strains and viral host information. Species with protein sequences stored in the UniProt Knowledgebase are named according to UniProt nomenclature. We endeavour to maintain a list of manually curated species names for which protein sequence data is available. In particular, we have adopted a systematic convention for naming viral and bacterial strains and isolates. Links to external sites are chosen by the UniProt taxonomy team and show pictures and various scientific data of interest (taxonomy, biology, physiology,...).
Proper citation: NEWT (RRID:SCR_004477) Copy
Database of positive selection based on a rigorous branch-site specific likelihood test. Positive selection is detected using CODEML on all branches of animal gene trees.
Proper citation: Selectome: a Database of Positive Selection (RRID:SCR_004542) Copy
http://www.ebi.ac.uk/biosamples/
Database that aggregates sample information for reference samples (e.g. Coriell Cell lines) and samples for which data exist in one of the EBI''''s assay databases such as ArrayExpress, the European Nucleotide Archive or PRoteomics Identificates DatabasE. It provides links to assays for specific samples, and accepts direct submissions of sample information. The goals of the BioSample Database include: # recording and linking of sample information consistently within EBI databases such as ENA, ArrayExpress and PRIDE; # minimizing data entry efforts for EBI database submitters by enabling submitting sample descriptions once and referencing them later in data submissions to assay databases and # supporting cross database queries by sample characteristics. The database includes a growing set of reference samples, such as cell lines, which are repeatedly used in experiments and can be easily referenced from any database by their accession numbers. Accession numbers for the reference samples will be exchanged with a similar database at NCBI. The samples in the database can be queried by their attributes, such as sample types, disease names or sample providers. A simple tab-delimited format facilitates submissions of sample information to the database, initially via email to biosamples (at) ebi.ac.uk. Current data sources: * European Nucleotide Archive (424,811 samples) * PRIDE (17,001 samples) * ArrayExpress (1,187,884 samples) * ENCODE cell lines (119 samples) * CORIELL cell lines (27,002 samples) * Thousand Genome (2,628 samples) * HapMap (1,417 samples) * IMSR (248,660 samples)
Proper citation: BioSample Database at EBI (RRID:SCR_004856) Copy
http://www.ncbi.nlm.nih.gov/Structure/ibis/ibis.cgi
A web server and database that organizes, analyzes and predicts interactions between proteins and other biomolecules. For a given protein sequence or structure query, it reports protein-protein, protein-small molecule, protein nucleic acids and protein-ion interactions observed in experimentally-determined structural biological assemblies. It also infers/predicts interacting partners and binding sites by homology, by inspecting the protein complexes formed by close homologs of a given query. To ensure biological relevance of inferred binding sites, the IBIS algorithm clusters binding sites formed by homologs based on binding site sequence and structure conservation.
Proper citation: IBIS: Inferred Biomolecular Interactions Server (RRID:SCR_004886) Copy
A clade oriented, community curated database containing genomic, genetic, phenotypic and taxonomic information for plant genomes. Genomic information is presented in a comparative format and tied to important plant model species such as Arabidopsis. SGN provides tools such as: BLAST searches, the SolCyc biochemical pathways database, a CAPS experiment designer, an intron detection tool, an advanced Alignment Analyzer, and a browser for phylogenetic trees. The SGN code and database are developed as an open source project, and is based on database schemas developed by the GMOD project and SGN-specific extensions.
Proper citation: SGN (RRID:SCR_004933) Copy
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