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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   

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http://www.mitomap.org/

Database of polymorphisms and mutations of the human mitochondrial DNA. It reports published and unpublished data on human mitochondrial DNA variation. All data is curated by hand. If you would like to submit published articles to be included in mitomap, please send them the citation and a pdf.

Proper citation: MITOMAP - A human mitochondrial genome database (RRID:SCR_002996) Copy   

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http://www.netpath.org/

A manually curated resource of signal transduction pathways in humans. All pathways are freely available for download in BioPAX level 3.0, PSI-MI version 2.5 and SBML version 2.1 formats. The slim pathway models representing only core reactions in each pathway are available at NetSlim. All the NetPath pathway models are also submitted to WikiPathways., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NetPath (RRID:SCR_003567) Copy   

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http://exac.broadinstitute.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. An aggregated data platform for genome sequencing data created by a coalition of investigators seeking to aggregate and harmonize exome sequencing data from a variety of large-scale sequencing projects, and to make summary data available for the wider scientific community. The data set provided on this website spans 61,486 unrelated individuals sequenced as part of various disease-specific and population genetic studies. They have removed individuals affected by severe pediatric disease, so this data set should serve as a useful reference set of allele frequencies for severe disease studies. All of the raw data from these projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects. They ask that you not publish global (genome-wide) analyses of these data until after the ExAC flagship paper has been published, estimated to be in early 2015. If you''re uncertain which category your analyses fall into, please email them. The aggregation and release of summary data from the exomes collected by the Exome Aggregation Consortium has been approved by the Partners IRB (protocol 2013P001477, Genomic approaches to gene discovery in rare neuromuscular diseases).

Proper citation: ExAc (RRID:SCR_004068) Copy   

•   Source: SciCrunch Registry

http://channelpedia.epfl.ch/

An information management framework for comprehensive ion channel information. It is a knowledge base system centered on genetically expressed ion channel models and it encourages researchers of the field to contribute, build and refine the information through an interactive wiki-like interface. It is web-based, freely accessible and currently contains 187 annotated ion channels with 50 Hodgkin-Huxley models (September 2014). Channelepdia provides an ideal platform to collectively build ion channel knowledge base by accommodating both structured and unstructured data. The current version of Channelpedia contains the following sections : Introduction, Genes, Ontologies, Interactions, Structure, Expression, Distribution, Function, Kinetics and Models. Newly published literature related to ion channels is automatically queried every week from PubMed and added to respective categories. Currently, Channelpedia contains ~180,000 abstracts related to ion channels from Pubmed.

Proper citation: ChannelPedia (RRID:SCR_003807) Copy   

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http://www.inmex.ca./INMEX/

A web-based tool to support meta-analysis of multiple gene-expression data sets, as well as to enable integration of data sets from gene expression and metabolomics experiments. INMEX contains three functional modules. The data preparation module supports flexible data processing, annotation and visualization of individual data sets. The statistical analysis module allows researchers to combine multiple data sets based on P-values, effect sizes, rank orders and other features. The significant genes can be examined in functional analysis module for enriched Gene Ontology terms or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, or expression profile visualization. INMEX has built-in support for common gene/metabolite identifiers (IDs), as well as 45 popular microarray platforms for human, mouse and rat. Complex operations are performed through a user-friendly web interface in a step-by-step manner.

Proper citation: INMEX (RRID:SCR_004173) Copy   

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http://www.flytf.org/

A database of genomic and protein data for Drosophila site-specific transcription factors.

Proper citation: FlyTF.org (RRID:SCR_004123) Copy   

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https://scicrunch.org/scicrunch/data/source/nlx_154697-4/search?q=*

Virtual database indexing brain region gene expression data from mice from: Gene Expression Nervous System Atlas (GENSAT), Allen Mouse Brain Atlas, and Mouse Genome Institute (MGI).

Proper citation: Integrated Brain Gene Expression (RRID:SCR_004197) Copy   

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http://www.nephromine.org/

THIS RESOURCE IS NO LONGER IN SERVICE; REPLACED BY NEPHROSEQ; A growing database of publicly available renal gene expression profiles, a sophisticated analysis engine, and a powerful web application designed for data mining and visualization of gene expression. It provides unique access to datasets from the Personalized Molecular Nephrology Research Laboratory incorporating clinical data which is often difficult to collect from public sources and mouse data.

Proper citation: Nephromine (RRID:SCR_003813) Copy   

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http://life.ccs.miami.edu/life/

LIFE search engine contains data generated from LINCS Pilot Phase, to integrate LINCS content leveraging semantic knowledge model and common LINCS metadata standards. LIFE makes LINCS content discoverable and includes aggregate results linked to Harvard Medical School and Broad Institute and other LINCS centers, who provide more information including experimental conditions and raw data. Please visit LINCS Data Portal.

Proper citation: LINCS Information Framework (RRID:SCR_003937) Copy   

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http://www.broadinstitute.org/mmgp/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. Database providing access and limited analysis to the MMGP portal data sets. These include the MMRC funded reference array comparative genomic hybridization (aCGH) and gene expression data and additional public multiple myeloma datasets. The MMGP will be updated with new features such as additional data and analysis tools as they become available.

Proper citation: Multiple Myeloma Genomics Portal (RRID:SCR_003722) Copy   

•   Source: SciCrunch Registry

http://www.hgsc.bcm.tmc.edu/content/hapmap-3-and-encode-3

Draft release 3 for genome-wide SNP genotyping and targeted sequencing in DNA samples from a variety of human populations (sometimes referred to as the HapMap 3 samples). This release contains the following data: * SNP genotype data generated from 1184 samples, collected using two platforms: the Illumina Human1M (by the Wellcome Trust Sanger Institute) and the Affymetrix SNP 6.0 (by the Broad Institute). Data from the two platforms have been merged for this release. * PCR-based resequencing data (by Baylor College of Medicine Human Genome Sequencing Center) across ten 100-kb regions (collectively referred to as ENCODE 3) in 712 samples. Since this is a draft release, please check this site regularly for updates and new releases. The HapMap 3 sample collection comprises 1,301 samples (including the original 270 samples used in Phase I and II of the International HapMap Project) from 11 populations, listed below alphabetically by their 3-letter labels. Five of the ten ENCODE 3 regions overlap with the HapMap-ENCODE regions; the other five are regions selected at random from the ENCODE target regions (excluding the 10 HapMap-ENCODE regions). All ENCODE 3 regions are 100-kb in size, and are centered within each respective ENCODE region. The HapMap 3 and ENCORE 3 data are downloadable from the ftp site.

Proper citation: HapMap 3 and ENCODE 3 (RRID:SCR_004563) Copy   

•   Source: SciCrunch Registry

http://integromedb.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016. Search engine that integrates over 100 curated and publicly contributed data sources and provides integrated views on the genomic, proteomic, transcriptomic, genetic and functional information currently available. Information featured in the database includes gene function, orthologies, gene expression, pathways and protein-protein interactions, mutations and SNPs, disease relationships, related drugs and compounds.

Proper citation: IntegromeDB (RRID:SCR_004620) Copy   

•   Source: SciCrunch Registry

http://www.yeastgenome.org/

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   

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https://reich.hms.harvard.edu/software

Software application that finds skews in ancestry that are potentially associated with disease genes in recently mixed populations like African Americans. It can be downloaded for either UNIX or Linux.

Proper citation: Ancestrymap (RRID:SCR_004353) Copy   

•   Source: SciCrunch Registry

http://selectome.unil.ch/

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   

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http://pbil.univ-lyon1.fr/databases/homolens.php

Database of homologous genes from Ensembl organisms, structured under ACNUC sequence database management system. It allows to select sets of homologous genes among species, and to visualize multiple alignments and phylogenetic trees. It is possible to search for orthologous genes in a wide range of taxons. HOMOLENS is particularly useful for comparative sequence analysis, phylogeny and molecular evolution studies. More generally, HOMOLENS gives an overall view of what is known about a peculiar gene family. Note that HOMOLENS is split into two databases on this server: HOMOLENS contains the protein sequences while HOMOLENSDNA contains the nucleotide sequences. Protein sequences of HOMOLENS have been generated by translating the CDS of HOMOLENSDNA and using associated cross-references to generate the annotations.

Proper citation: Homologous Sequences in Ensembl Animal Genomes (RRID:SCR_008356) Copy   

•   Source: SciCrunch Registry

http://polygenicpathways.blogspot.com/

A blog concerning the relationships between genes, risk factors and immunity in Alzheimer's disease, autism, Bipolar disorder, multiple sclerosis, Parkinson's disease, schizophrenia and chronic fatigue.

Proper citation: PolygenicBlog (RRID:SCR_008789) Copy   

•   Source: SciCrunch Registry

http://gostat.wehi.edu.au

GOstat is a tool that allows you to find statistically overrepresented Gene Ontologies within a group of genes. The Gene-Ontology database (GO: http://www.geneontology.org) provides a useful tool to annotate and analyze the function of large numbers of genes. Modern experimental techniques, as e.g. DNA microarrays, often result in long lists of genes. To learn about the biology in this kind of data it is desirable to find functional annotation or Gene-Ontology groups which are highly represented in the data. This program (GOstat) should help in the analysis of such lists and will provide statistics about the GO terms contained in the data and sort the GO annotations giving the most representative GO terms first. Run GOstat: * Go to search form - Computes GO statistics of a list of genes selected from a microarray. * GOstat Display - You can store results from a previously run and view them here, either by uploading them as a file or putting them on a selected URL. * Upload Custom GO Annotations - This allows you to upload your own GO annotation database and use it with GOstat. Variants of GOstat: * Rank GOstat - Takes input from all genes on microarray instead of using a fixed cutoff and uses ranks using a Wilcoxon test or either ranks or pvalues to score GOs using Kolmogorov-Smirnov statistics. * Gene Abundance GOstats - Takes input from all genes on microarray and sums up the gene abundances for each GO to compute statistics. * Two list GOstat - Compares GO statistics in two independent lists of genes, not necessarily one of them being the complete list the other list is sampled from. Platform: Online tool, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GOstat (RRID:SCR_008535) Copy   

•   Source: SciCrunch Registry