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http://t3db.org/

Database that combines detailed toxin data with comprehensive toxin target information. The database currently houses 3,053 toxins described by 32,276 synonyms, including pollutants, pesticides, drugs, and food toxins, which are linked to 1,670 corresponding toxin target records. Altogether there are 37,084 toxin, toxin target associations. (March 2014) Each toxin record (ToxCard) contains over 50 data fields and holds information such as chemical properties and descriptors, toxicity values, molecular and cellular interactions, and medical information. This information has been extracted from over 5,454 sources sources, which include other databases, government documents, books, and scientific literature. The focus of the T3DB is on providing mechanisms of toxicity and target proteins for each toxin. This dual nature of the T3DB, in which toxin and toxin target records are interactively linked in both directions, makes it unique from existing databases. It is also fully searchable and supports extensive text, sequence, chemical structure, and relational query searches

Proper citation: T3DB (RRID:SCR_002672) Copy   

•   Source: SciCrunch Registry

http://hint.yulab.org/

A database of high-quality protein-protein interactions in different organisms.

Proper citation: HINT (RRID:SCR_002762) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/gene

Database for genomes that have been completely sequenced, have active research community to contribute gene-specific information, or that are scheduled for intense sequence analysis. Includes nomenclature, map location, gene products and their attributes, markers, phenotypes, and links to citations, sequences, variation details, maps, expression, homologs, protein domains and external databases. All entries follow NCBI's format for data collections. Content of Entrez Gene represents result of curation and automated integration of data from NCBI's Reference Sequence project (RefSeq), from collaborating model organism databases, and from many other databases available from NCBI. Records are assigned unique, stable and tracked integers as identifiers. Content is updated as new information becomes available.

Proper citation: Entrez Gene (RRID:SCR_002473) Copy   

•   Source: SciCrunch Registry

http://dbtss.hgc.jp/

Database of transcriptional start sites (TSSs) representing exact positions in the genome based on a unique experimentally validated TSS sequencing method, TSS Seq. A major part of human adult and embryonic tissues are covered. DBTSS contains 491 million TSS tag sequences collected from a total of 20 tissues and 7 cell cultures. Also integrated is generated RNA-seq data of subcellular- fractionated RNAs and ChIP Seq data of histone modifications, RNA polymerase II and several transcriptional regulatory factors in cultured cell lines. Also included is external epigenomic data, such as chromatin map of the ENCODE project. They associated those TSS information with public and original SNV data, in order to identify single nucleotide variations (SNVs) in the regulatory regions.

Proper citation: DBTSS: Database of Transcriptional Start Sites (RRID:SCR_002354) Copy   

•   Source: SciCrunch Registry

http://pir.georgetown.edu/resid/

A comprehensive collection of annotations and structures for protein modifications including amino-terminal, carboxyl-terminal and peptide chain cross-link post-translational modifications. It provides: systematic and alternate names, atomic formulas and masses, enzyme activities generating the modifications, keywords, literature citations, Gene Ontology cross-references, Protein Information Resource (PIR) and SWISS-PROT protein sequence database feature table annotations, structure diagrams and molecular models. Each RESID Database entry presents a chemically unique modification and shows how that modification is currently annotated in the protein sequence databases, Swiss-Prot and the Protein Information Resource (PIR). The RESID Database provides a table of corresponding equivalent feature annotations that is used in the UniProt project, an international effort to combine the resources of the Swiss-Prot, TrEMBL and PIR. As an annotation tool, the RESID Database is used in standardizing and enhancing modification descriptions in the feature tables of Swiss-Prot entries.

Proper citation: RESID (RRID:SCR_003505) Copy   

•   Source: SciCrunch Registry

http://blocks.fhcrc.org/codehop.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.Service to design PCR primers from protein multiple sequence alignments. NOTICE: This version of CODEHOP is no longer maintained.

Proper citation: CODEHOP (RRID:SCR_002898) Copy   

•   Source: SciCrunch Registry

http://bibiserv.techfak.uni-bielefeld.de/genefisher2/

A web-based program for designing degenerate primers. The procedure leads to isolation of genes in a target organism using multiple alignments of related genes from different organisms. The term gene fishing refers to the technique where PCR is used to isolate a postulated but unknown target sequence from a pool of DNA.

Proper citation: GeneFisher (RRID:SCR_003060) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/IPI

IPI provides a top level guide to the main databases (UniProtKB/Swiss-Prot, UniProtKB/TrEMBL, RefSeq, Ensembl, TAIR, H-InvDB, Vega) that describe the proteomes of higher eukaryotic organisms. IPI: :1. effectively maintains a database of cross references between the primary data sources :2. provides minimally redundant yet maximally complete sets of proteins for featured species (one sequence per transcript) :3. maintains stable identifiers (with incremental versioning) to allow the tracking of sequences in IPI between IPI releases. IPI is updated monthly in accordance with the latest data released by the primary data sources. As previously announced, the closure of IPI has been proposed for some time. Replacement data sets are now available through UniProt for human and mouse; sets for the other species contained within IPI are expected to be included as part of the UniProt release 2011_07. To allow users time to transition to using the new UniProt data sets, IPI releases will continue to be produced throughout the summer. The final release will be made in September 2011. Thereafter, the IPI website will cease to be maintained, although previous releases of the dataset will continue to be available from the FTP site. We would like to thank our users for their support and interest in this service.

Proper citation: IPI (RRID:SCR_003012) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/ipd/

A set of specialist databases related to the study of polymorphic genes in the immune system. The IPD project works with specialist groups or nomenclature committees who provide and curate individual sections before they are submitted to IPD for online publication. The IPD project stores all the data in a set of related databases. IPD currently consists of four databases: * IPD-KIR, contains the allelic sequences of Killer-cell Immunoglobulin-like Receptors, * IPD-MHC, is a database of sequences of the Major Histocompatibility Complex of different species; * IPD-human platelet antigens, alloantigens expressed only on platelets and * IPD-ESTDAB, which provides access to the European Searchable Tumour cell-line database, a cell bank of immunologically characterized melanoma cell lines.

Proper citation: IPD - Immuno Polymorphism Database (RRID:SCR_003004) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/tools/epcr/

Web tool that identifies sequence tagged sites (STSs) within DNA sequences. Using e-PCR, you can search for sub-sequences that closely match the PCR primers and have the correct order, orientation, and spacing. The software may also be downloaded to run locally.

Proper citation: e-PCR (RRID:SCR_003082) Copy   

•   Source: SciCrunch Registry

https://netbio.bgu.ac.il/labwebsite/software/responsenet/

WebServer that identifies high-probability signaling and regulatory paths that connect input data sets. The input includes two weighted lists of condition-related proteins and genes, such as a set of disease-associated proteins and a set of differentially expressed disease genes, and a molecular interaction network (i.e., interactome). The output is a sparse, high-probability interactome sub-network connecting the two sets that is biased toward signaling pathways. This sub-network exposes additional proteins that are potentially involved in the studied condition and their likely modes of action. Computationally, it is formulated as a minimum-cost flow optimization problem that is solved using linear programming.

Proper citation: ResponseNet (RRID:SCR_003176) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/intenz

IntEnz (Integrated relational Enzyme database) is a freely available resource focused on enzyme nomenclature. IntEnz is created in collaboration with the Swiss Institute of Bioinformatics (SIB). This collaboration is responsible for the production of the ENZYME resource. IntEnz contains the recommendations of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB) on the nomenclature and classification of enzyme-catalysed reactions.

Proper citation: IntEnz- Integrated relational Enzyme database (RRID:SCR_002992) Copy   

•   Source: SciCrunch Registry

http://www-stat.stanford.edu/~tibs/SAM/

Software for genomic expression data mining using a statistical technique for finding significant genes in a set of microarray experiments.

Proper citation: SAM (RRID:SCR_010951) Copy   

•   Source: SciCrunch Registry

http://bioen-compbio.bioen.illinois.edu/FusionHunter/

Software for identifying fusion transcripts using paired-end RNA-seq.

Proper citation: FusionHunter (RRID:SCR_011895) Copy   

•   Source: SciCrunch Registry

https://gitlab.com/kyrgyzov/lsa_slurm

Software tool to implement pre-assembly binning scheme leveraging sparse dictionary learning and matrix factorization to solve sparse decomposition problems arising in field of metagenomics.

Proper citation: lsa_slurm (RRID:SCR_018134) Copy   

•   Source: SciCrunch Registry

https://www.integromics.com/omicsoffice-for-ngs/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 18,2025. Software for secondary and tertiary analysis of Next Generation Sequencing (NGS) data.

Proper citation: OmicsOffice for NGS SeqSolve (RRID:SCR_001222) Copy   

•   Source: SciCrunch Registry

http://www.bioinfor.com/zoom/general/overview.html

Software to map the Illumina/Solexa reads of 15x coverage of a human genome to the reference human genome in one CPU-day, allowing two mismatches, at full sensitivity.

Proper citation: ZOOM (RRID:SCR_002175) Copy   

•   Source: SciCrunch Registry

http://segway.hoffmanlab.org/

The free Segway software package contains a novel method for analyzing multiple tracks of functional genomics data. The method uses a dynamic Bayesian network (DBN) model, which enables it to analyze the entire genome at 1-bp resolution even in the face of heterogeneous patterns of missing data. This method is the first application of DBN techniques to genome-scale data and the first genomic segmentation method designed for use with the maximum resolution data available from ChIP-seq experiments without downsampling. Segway uses the Graphical Models Toolkit (GMTK) for efficient DBN inference. The software has extensive documentation and was designed from the outset with external users in mind.

Proper citation: Segway - a way to segment the genome (RRID:SCR_004206) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://broadinstitute.github.io/picard/

Java toolset for working with next generation sequencing data in the BAM format.

Proper citation: Picard (RRID:SCR_006525) Copy   

•   Source: SciCrunch Registry

http://www.biopieces.org

A collection of bioinformatics tools that can be pieced together in a very easy and flexible manner to perform both simple and complex tasks. The Biopieces work on a data stream in such a way that the data stream can be passed through several different Biopieces, each performing one specific task: modifying or adding records to the data stream, creating plots, or uploading data to databases and web services. The Biopieces are executed in a command line environment where the data stream is initialized by specific Biopieces which read data from files, databases, or web services, and output records to the data stream that is passed to downstream Biopieces until the data stream is terminated at the end of the analysis. The advantage of the Biopieces is that a user can easily solve simple and complex tasks without having any programming experience. Moreover, since the data format used to pass data between Biopieces is text based, different developers can quickly create new Biopieces in their favorite programming language - and all the Biopieces will maintain compatibility. Finally, templates exist for creating new Biopieces in Perl and Ruby. There are currently ~190 Biopieces (March 2014).

Proper citation: Biopieces (RRID:SCR_005783) Copy   

•   Source: SciCrunch Registry