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Cross-species microarray expression database focusing on high-throughput expression data relevant for germline development, meiosis and gametogenesis as well as the mitotic cell cycle. The database contains a unique combination of information: 1) High-throughput expression data obtained with whole-genome high-density oligonucleotide microarrays (GeneChips). 2) Sample annotation (mouse over the sample name and click on it) using the Multiomics Information Management and Annotation System (MIMAS 3.0). 3) In vivo protein-DNA binding data and protein-protein interaction data (available for selected species). 4) Genome annotation information from Ensembl version 50. 5) Orthologs are identified using data from Ensembl and OMA and linked to each other via a section in the report pages. The portal provides access to the Saccharomyces Genomics Viewer (SGV) which facilitates online interpretation of complex data from experiments with high-density oligonucleotide tiling microarrays that cover the entire yeast genome. The database displays only expression data obtained with high-density oligonucleotide microarrays (GeneChips)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.
Proper citation: GermOnline (RRID:SCR_002807) Copy
http://www.ncbi.nlm.nih.gov/homologene
Automated system for constructing putative homology groups from complete gene sets of wide range of eukaryotic species. Databse that provides system for automatic detection of homologs, including paralogs and orthologs, among annotated genes of sequenced eukaryotic genomes. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences. Reports include homology and phenotype information drawn from Online Mendelian Inheritance in Man, Mouse Genome Informatics, Zebrafish Information Network, Saccharomyces Genome Database and FlyBase.
Proper citation: HomoloGene (RRID:SCR_002924) Copy
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
A database of high-quality protein-protein interactions in different organisms.
Proper citation: HINT (RRID:SCR_002762) Copy
http://www.biocomputing.it/fidea/
A web server for the functional interpretation of differential expression analysis. It can: * Calculate overrepresentation statistics using KEGG, Interpro, Gene Ontology Molecular Function, Gene Ontology Biological Process, Gene Ontology Cellular Component and GoSlim classifications; * Analyze down-regulated and up-regulated DE genes separately or together as a single set; * Provide interactive graphs and tables that can be modified on the fly according to user defined parameters; the user can set a fold change filter and interactively see the effects on the gene set under examination; * Output publication-ready plot of the graph; * Compare the results of several experiments in any combination.
Proper citation: FIDEA (RRID:SCR_004187) Copy
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