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https://compbio.dfci.harvard.edu/predictivenetworks//

A flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these ''known'' interactions together with gene expression data to infer robust gene networks. The regression-based network inference algorithm creates a graph of gene interactions in which cycles may be present (but no self-loops). Based on information-theoretic techniques, a causal gene interaction network is inferred from both prior knowledge (interactions extracted from biomedical literature and structured biological databases) and gene expression data. A prediction model is fitted for each gene, given its parents, enabling assessment of the predictive ability of the network model.

Proper citation: Predictive Networks (RRID:SCR_006110) Copy   

•   Source: SciCrunch Registry

https://pb.apf.edu.au/phenbank/homePage.html

The NHMRC Australian PhenomeBank (APB) is a non-profit repository of mouse strains used in Medical Research. The database allows you to search for murine strains, housed or archived in Australia, carrying mutations in particular genes, strains with transgenic alterations and for mice with particular phenotypes. 1876 publicly available strains, 922 genes, 439 transgenes The APB has two roles: Provide and maintain a central database of genetically modified mice held in Australia either live or as cryopreserved material; Establish and maintain a mouse strain archive. Strains are archived as cryopreserved sperm or embryos.

Proper citation: NHMRC Australian PhenomeBank (RRID:SCR_006149) Copy   

•   Source: SciCrunch Registry

http://www.fimre.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 7, 2022. Federation of International Mouse Resources (FIMRe) is a collaborating group of Mouse Repository and Resource Centers worldwide whose collective goal is to archive and provide strains of mice as cryopreserved embryos and gametes, ES cell lines, and live breeding stock to the research community. Goals of the Federation of International Mouse Resources: * Coordinate repositories and resource centers to: ** archive valuable genetically defined mice and ES cell lines being created worldwide ** meet research demand for these genetically defined mice and ES cell lines * Establish consistent, highest quality animal health standards in all resource centers * Provide genetic verification and quality control for genetic background and mutations * Provide resource training to enhance user ability to utilize cryopreserved resources

Proper citation: Federation of International Mouse Resources (RRID:SCR_006137) Copy   

•   Source: SciCrunch Registry

http://202.38.126.151:8080/SDisease/

Curated database of experimentally supported data of RNA Splicing mutation and disease. The RNA Splicing mutations include cis-acting mutations that disrupt splicing and trans-acting mutations that affecting RNA-dependent functions that cause disease. Information such as EntrezGeneID, gene genomic sequence, mutation (nucleotide substitutions, deletions and insertions), mutation location within the gene, organism, detailed description of the splicing mutation and references are also given. Users are able to submit new entries to the database. This 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, they 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. They 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, they give direct links of the entry to the respective position/region in the genome browser.

Proper citation: SpliceDisease (RRID:SCR_006130) Copy   

•   Source: SciCrunch Registry

http://www.mousephenotype.org/impress

Contains standardized phenotyping protocols essential for the characterization of mouse phenotypes. IMPReSS holds definitions of the phenotyping Pipelines and mandatory and optional Procedures and Parameters carried out and data collected by international mouse clinics following the protocols defined. This allows data to be comparable and shareable and ontological annotations permit interspecies comparison which may help in the identification of phenotypic mouse-models of human diseases. The IMPC (International Mouse Phenotyping Consortium) core pipeline describes the phenotype pipeline that has been agreed by the research institutions. IMPReSS has a SOAP web service machine interface. The WSDL can be accessed here: http://www.mousephenotype.org/impress/soap/server?wsdl

Proper citation: Impress (RRID:SCR_006160) Copy   

•   Source: SciCrunch Registry

http://www.cafevariome.org/

Clearinghouse and exchange portal for gene variant (mutation) data produced by diagnostics laboratories, offering users a portal through which to announce, discover and acquire a comprehensive listing of observed neutral and disease-causing gene variants in patients and unaffected individuals. Cafe Variome is not a ''''database'''' for the hosting/display/release of data, but a shop window for finding data. As such, it holds only core info for each record, and uses this merely to enable holistic searching across resources. Diagnostics laboratories routinely assess DNA samples from patients with various inherited disorders, and so produce a great wealth of data on the genetic basis of disease. Unfortunately, those data are not usually shared with others. To address this gross deficiency, a novel system has been developed that aims to facilitate the automated transfer of diagnostic laboratory data to the wider community, via an internet based Cafe for routinely exchanging genetic variation data. The flow of research data concerning the genetic basis of health and disease is critical to understanding and developing treatments for a range of genetic diseases. Overall, the project aims to lower the barriers and provide incentives for a willing community to share data, and thereby facilitate the broader exploitation of diagnostic laboratory data. Cafe Variome aims to address the above data flow problems by: # Minimizing the effort required to publish variant data # Ensuring attribution for data creators working in diagnostic laboratories Key elements of the project strategy are: * Data publication will be automated by endowing standard analysis tools used by laboratories with an online data submission function. Submissions will be received by a central Internet depot, which will serve as a place where published datasets are advertised, and subsequently discovered by diverse 3rd parties. * Each dataset will be unambiguously linked with the data submitter''''s identity, and systems devised to facilitate citation of published variant datasets so they can be cited in the literature. Data creators will thus be credited for their contributions. Data submitters can use Cafe Variome to simply announce or publicize their data to the world. To enable this, only core, non-identifiable data is submitted to the central repository, enabling users to search and discover records of interest in the source repository. The data are not automatically handed on to the user (unless intended by the submitters). Hence, the concept is used to deal with the challenge of maximally sharing data whilst fully respecting ethico-legal considerations.

Proper citation: cafe variome (RRID:SCR_006162) Copy   

•   Source: SciCrunch Registry

http://kobas.cbi.pku.edu.cn/

Web server to identify statistically enriched pathways, diseases, and GO terms for a set of genes or proteins, using pathway, disease, and GO knowledge from multiple famous databases. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). A standalone command line version is also available, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: KOBAS (RRID:SCR_006350) Copy   

•   Source: SciCrunch Registry

http://www.genepattern-notebook.org/

Interactive analysis notebook environment that streamlines genomics research by interleaving text, multimedia, and executable code into unified, sharable, reproducible “research narratives.” It integrates the dynamic capabilities of notebook systems with an investigator-focused, simple interface that provides access to hundreds of genomic tools without the need to write code.

Proper citation: GenePattern Notebook (RRID:SCR_015699) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://portals.broadinstitute.org/cmap/

Collection of genome-wide transcriptional expression data from cultured human cells treated with bioactive small molecules and simple pattern-matching algorithms. camp aims to enable the discovery of functional connections between drugs, genes and diseases through the transitory feature of common gene-expression changes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Connectivity Map 02 (RRID:SCR_015674) Copy   

•   Source: SciCrunch Registry

https://funricegenes.github.io/

Dataset of functionally characterized rice genes and members of different gene families. The dataset was created by integrating data from available databases and reviewing publications of rice functional genomic studies.

Proper citation: funRiceGenes (RRID:SCR_015778) Copy   

•   Source: SciCrunch Registry

http://apps.cytoscape.org/apps/cluepedia

Data analysis software and search tool for new markers potentially associated to pathways. CluePedia calculates linear and non-linear statistical dependencies from experimental data and investigates interrelations within each pathway to reveal associations through gene/protein/miRNA enrichments.

Proper citation: CluePedia Cytoscape plugin (RRID:SCR_015784) Copy   

•   Source: SciCrunch Registry

https://ukbec.wordpress.com

Consortium studying the regulation and alternative splicing of gene expression in multiple tissues from human brains. The UKBEC dataset comprises of brains from individuals free of neurodegenerative disorders.

Proper citation: UK Brain Expression Consortium (RRID:SCR_015889) Copy   

•   Source: SciCrunch Registry

http://www.vicbioinformatics.com/software.barrnap.shtml

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software to predict the location of ribosomal RNA genes in genomes. It supports bacteria, archaea, mitochondria, and eukaryotes. It takes FASTA DNA sequence as input, writes GFF3 as output, and supports multithreading., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Barrnap (RRID:SCR_015995) Copy   

•   Source: SciCrunch Registry

https://github.com/harry-thorpe/piggy

Pipeline for analyzing intergenic regions in bacteria. It is designed to be used in conjunction with Roary (https://github.com/sanger-pathogens/Roary).

Proper citation: Piggy (RRID:SCR_015941) Copy   

•   Source: SciCrunch Registry

http://www.genetherapyreview.com/gene-therapy-research

The National Gene Vector Laboratories (NGVL) was established as a cooperative national effort to produce and distribute vectors for human gene transfer studies.

Proper citation: National Gene Vector Laboratories (RRID:SCR_015944) Copy   

•   Source: SciCrunch Registry

http://baderlab.org/Software/EnrichmentMap

Source code of a Cytoscape plugin for functional enrichment visualization. It organizes gene-sets, such as pathways and Gene Ontology terms, into a network to reveal which mutually overlapping gene-sets cluster together.

Proper citation: EnrichmentMap (RRID:SCR_016052) Copy   

•   Source: SciCrunch Registry

https://github.com/alesssia/YAMP

Software for processing and analysis of sequencing data. It has a strong focus on quality control, timely processing, functional annotation, and portability.

Proper citation: YAMP (RRID:SCR_016236) Copy   

•   Source: SciCrunch Registry

http://www.fishbrowser.org/software/LR_Gapcloser/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 18th, 2023. Software that uses long reads to close gaps in the assemblies.

Proper citation: LR Gapcloser (RRID:SCR_016194) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/l1000fwd/

Web application that provides interactive visualization of drug and small-molecule induced gene expression signatures. L1000FWD enables coloring of signatures by different attributes such as cell type, time point, concentration, as well as drug attributes such as MOA and clinical phase.

Proper citation: L1000 Fireworks Display (RRID:SCR_016175) Copy   

•   Source: SciCrunch Registry