Tools   Select Another Resource Report Type

http://wpicr.wpic.pitt.edu/WPICCompGen/fdr/

Software application (entry from Genetic Analysis Software)

Proper citation: WEIGHTED FDR (RRID:SCR_013442) Copy   

•   Source: SciCrunch Registry

http://cuke.hort.ncsu.edu/cucurbit/wehner/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. SAS software program to estimate genetic effects and heritabilities of quantitative traits in breeding populations consisting of six related generations (entry from Genetic Analysis Software)

Proper citation: SASQUANT (RRID:SCR_013122) Copy   

•   Source: SciCrunch Registry

http://www.aps.uoguelph.ca/~msargol/qmsim/

Software application designed to simulate a wide range of genetic architectures and population structures in livestock. Large scale genotyping data and complex pedigrees can be efficiently simulated. QMSim is a family based simulator, which can also take into account predefined evolutionary features, such as LD, mutation, bottlenecks and expansions. The simulation is basically carried out in two steps: In the first step, a historical population is simulated to establish mutation-drift equilibrium and, in the second step, recent population structures are generated, which can be complex. QMSim allows for a wide range of parameters to be incorporated in the simulation models in order to produce appropriate simulated data. (entry from Genetic Analysis Software)

Proper citation: QMSIM (RRID:SCR_013123) Copy   

•   Source: SciCrunch Registry

https://imdevsoftware.wordpress.com/imdev/

A software application of RExcel that integrates R into Excel as an embedded additon for omics tasks and analysis. It can be used specifically for tasks concerning multivariate data visualization, exploration, and analysis. imDev has interactive modules for dimensional reduction, prediction, feature selection, analysis of correlation, and generation of networked structures, all of which provide an integrated environment for systems level analysis of multivariate data.

Proper citation: imDEV (RRID:SCR_014674) Copy   

•   Source: SciCrunch Registry

http://prospector.ucsf.edu

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   

•   Source: SciCrunch Registry

http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/

Database to store and display somatic mutation information and related details and contains information relating to human cancers. The mutation data and associated information is extracted from the primary literature. In order to provide a consistent view of the data a histology and tissue ontology has been created and all mutations are mapped to a single version of each gene. The data can be queried by tissue, histology or gene and displayed as a graph, as a table or exported in various formats.
Some key features of COSMIC are:
* Contains information on publications, samples and mutations. Includes samples which have been found to be negative for mutations during screening therefore enabling frequency data to be calculated for mutations in different genes in different cancer types.
* Samples entered include benign neoplasms and other benign proliferations, in situ and invasive tumours, recurrences, metastases and cancer cell lines.

Proper citation: COSMIC - Catalogue Of Somatic Mutations In Cancer (RRID:SCR_002260) Copy   

•   Source: SciCrunch Registry

http://www.ecoli-york.org/

A database that curates new experimental and bioinformatic information about the genes and gene products of the model bacterium Escherichia coli K-12 strain MG1655. It has been created to integrate information from post-genomic experiments into a single resource with the aim of providing functional predictions for the 1500 or so gene products for which we have no knowledge of their physiological function. While EchoBASE provides a basic annotation of the genome, taken from other databases, its novelty is in the curation of post-genomic experiments and their linkage to genes of unknown function. Experiments published on E. coli are curated to one of two levels. Papers dealing with the determination of function of a single gene are briefly described, while larger dataset are actually included in the database and can be searched and manipulated. This includes data for proteomics studies, protein-protein interaction studies, microarray data, functional genomic approaches (looking at multiple deletion strains for novel phenotypes) and a wide range of predictions that come out of in silico bioinformatic approaches. The aim of the database is to provide hypothesis for the functions of uncharacterized gene products that may be used by the E. coli research community to further our knowledge of this model bacterium.

Proper citation: EchoBASE (RRID:SCR_002430) Copy   

•   Source: SciCrunch Registry

http://www.tanpaku.org/autophagy/

Database that provides basic, up-to-date information on relevant literature, and a list of autophagy-related proteins and their homologs in eukaryotes.

Proper citation: Autophagy Database (RRID:SCR_002671) Copy   

•   Source: SciCrunch Registry

http://domine.utdallas.edu

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13,2026. Database of known and predicted protein domain (domain-domain) interactions containing interactions inferred from PDB entries, and those that are predicted by 8 different computational approaches using Pfam domain definitions. DOMINE contains a total of 26,219 domain-domain interactions (among 5,410 domains) out of which 6,634 are inferred from PDB entries, and 21,620 are predicted by at least one computational approach. Of the 21,620 computational predictions, 2,989 interactions are high-confidence predictions (HCPs), 2,537 interactions are medium-confidence predictions (MCPs), and the remaining 16,094 are low-confidence predictions (LCPs). (May 2014)

Proper citation: DOMINE: Database of Protein Interactions (RRID:SCR_002399) Copy   

•   Source: SciCrunch Registry

http://viperdb.scripps.edu/

Database for icosahedral virus capsid structures. The emphasis of the resource is on providing data from structural and computational analyses on these systems, as well as high quality renderings for visual exploration. In addition, all virus capsids are placed in a single icosahedral orientation convention, facilitating comparison between different structures. The web site includes powerful search utilities , links to other relevant databases, background information on virus capsid structure, and useful database interface tools. It is an information source for the analysis of high resolution virus structures. VIPERdb is a one-stop site dedicated to helping users around the world examine the many icosahedral virus structures contained within the Protein Data Bank (PDB) by providing them with an easy to use database containing current data and a variety of analytical tools. Sponsors: VIPERdb is funded by the NIH., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: VIPERdb (RRID:SCR_002853) Copy   

•   Source: SciCrunch Registry

http://hgc.rockefeller.edu/

An interactive web server that enables researchers to prioritize any list of genes by their biological proximity to defined core genes (i.e. genes that are known to be associated with the phenotype), and to predict novel gene pathways.

Proper citation: Human Gene Connectome Server (RRID:SCR_002627) Copy   

•   Source: SciCrunch Registry

http://ndbserver.rutgers.edu/

A database of three-dimensional structural information about nucleic acids and their complexes. In addition to primary data, it contains derived geometric data, classifications of structures and motifs, standards for describing nucleic acid features, as well as tools and software for the analysis of nucleic acids. A variety of search capabilities are available, as are many different types of reports. NDB maintains the macromolecular Crystallographic Information File (mmCIF).

Proper citation: Nucleic Acid Database (RRID:SCR_003255) Copy   

•   Source: SciCrunch Registry

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

Collection of curated, non-redundant genomic DNA, transcript RNA, and protein sequences produced by NCBI. Provides a reference for genome annotation, gene identification and characterization, mutation and polymorphism analysis, expression studies, and comparative analyses. Accessed through the Nucleotide and Protein databases.

Proper citation: RefSeq (RRID:SCR_003496) Copy   

•   Source: SciCrunch Registry

http://mutdb.org/

Database with annotations for human variation data with protein structural information and other functionally relevant information, if available. The mutations are organized by gene.

Proper citation: MutDB (RRID:SCR_003251) Copy   

•   Source: SciCrunch Registry

http://webdocs.cs.ualberta.ca/~bioinfo/PA/Sub/

Web server specialized to predict the subcellular localization of proteins using established machine learning techniques.

Proper citation: Proteome Analyst Specialized Subcellular Localization Server (RRID:SCR_003143) Copy   

•   Source: SciCrunch Registry

http://compbio.uthsc.edu/miRSNP/

Database of naturally occurring DNA variations in microRNA (miRNA) seed regions and miRNA target sites. MicroRNAs pair to the transcripts of protein-coding genes and cause translational repression or mRNA destabilization. SNPs and INDELs in miRNAs and their target sites may affect miRNA-mRNA interaction, and hence affect miRNA-mediated gene repression. The PolymiRTS database was created by scanning 3'UTRs of mRNAs in human and mouse for SNPs and INDELs in miRNA target sites. Then, the potential downstream effects of these polymorphisms on gene expression and higher-order phenotypes are identified. Specifically, genes containing PolymiRTSs, cis-acting expression QTLs, and physiological QTLs in mouse and the results of genome-wide association studies (GWAS) of human traits and diseases are linked in the database. The PolymiRTS database also includes polymorphisms in target sites that have been supported by a variety of experimental methods and polymorphisms in miRNA seed regions.

Proper citation: PolymiRTS (RRID:SCR_003389) Copy   

•   Source: SciCrunch Registry

http://nar.oxfordjournals.org/content/34/suppl_2/W635.long

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 9, 2016. A web server that allows users to efficiently identify and prioritize high-risk SNPs according to their phenotypic risks and putative functional effects. A unique feature is that the functional effect information used for SNP prioritization is always up-to-date, because FASTSNP extracts the information from 11 external web servers at query time using a team of web wrapper agents. Moreover, FASTSNP is extendable by deploying more Web wrapper agents. FASTSNP provides three options for users to submit requests. If users already have some candidate SNPs on a candidate gene, they may use Query by Candidate Gene to select the specific SNPs on the gene to perform prioritization. If users have a specified SNP or a list of SNP rsid's needs to be prioritized, they can use Query by SNP option and upload the SNP list in an Excel-format file. Finally, if users have a novel SNP sequence, FASTSNP provides Novel SNP analysis. FASTSNP will generate a SNP Function Report for each SNP. Users can export SNP data to an excel file for further genotyping processes. Other features of FASTSNP include SNP quality checking and haplotype LD information.

Proper citation: FastSNP (RRID:SCR_003140) Copy   

•   Source: SciCrunch Registry

http://www.phi-base.org/

Database that catalogs experimentally verified pathogenicity, virulence and effector genes from fungal, Oomycete and bacterial pathogens, which infect animal, plant, fungal and insect hosts. It is an invaluable resource in the discovery of genes in medically and agronomically important pathogens, which may be potential targets for chemical intervention. In collaboration with the FRAC team, it also includes antifungal compounds and their target genes. Each entry is curated by domain experts and is supported by strong experimental evidence (gene disruption experiments, STM etc), as well as literature references in which the original experiments are described. Each gene is presented with its nucleotide and deduced amino acid sequence, as well as a detailed description of the predicted protein's function during the host infection process. To facilitate data interoperability, genes have been annotated using controlled vocabularies and links to external sources (Gene Ontology terms, EC Numbers, NCBI taxonomy, EMBL, PubMed and FRAC).

Proper citation: PHI-base (RRID:SCR_003331) Copy   

•   Source: SciCrunch Registry

http://www.t-profiler.org

One of the key challenges in the analysis of gene expression data is how to relate the expression level of individual genes to the underlying transcriptional programs and cellular state. The T-profiler tool hosted on this website uses the t-test to score changes in the average activity of pre-defined groups of genes. The gene groups are defined based on Gene Ontology categorization, ChIP-chip experiments, upstream matches to a consensus transcription factor binding motif, and location on the same chromosome, respectively. If desired, an iterative procedure can be used to select a single, optimal representative from sets of overlapping gene groups. A jack-knife procedure is used to make calculations more robust against outliers. T-profiler makes it possible to interpret microarray data in a way that is both intuitive and statistically rigorous, without the need to combine experiments or choose parameters. Currently, gene expression data from Saccharomyces cerevisiae and Candida albicans are supported. Users can submit their microarray data for analysis by clicking on one of the two organism-specific tabs above. Platform: Online tool

Proper citation: T-profiler (RRID:SCR_003452) Copy   

•   Source: SciCrunch Registry

http://dire.dcode.org

Web server based on the Enhancer Identification (EI) method, to determine the chromosomal location and functional characteristics of distant regulatory elements (REs) in higher eukaryotic genomes. The server uses gene co-expression data, comparative genomics, and combinatorics of transcription factor binding sites (TFBSs) to find TFBS-association signatures that can be used for discriminating specific regulatory functions. DiRE's unique feature is the detection of REs outside of proximal promoter regions, as it takes advantage of the full gene locus to conduct the search. DiRE can predict common REs for any set of input genes for which the user has prior knowledge of co-expression, co-function, or other biologically meaningful grouping. The server predicts function-specific REs consisting of clusters of specifically-associated TFBSs, and it also scores the association of individual TFs with the biological function shared by the group of input genes. Its integration with the Array2BIO server allows users to start their analysis with raw microarray expression data.

Proper citation: Distant Regulatory Elements (RRID:SCR_003058) Copy   

•   Source: SciCrunch Registry