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http://geneseer.com/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Database to access gene information through common names and allows identification of homologs and paralogs for a given gene. This publicly available tool leverages public sequence data, gene metadata information, and other publicly available data to calculate and display orthologous and paralogous gene relationships for all genes from several species, including yeasts, insects, worms, vertebrates, mammals, and primates such as humans.

Proper citation: GeneSeer (RRID:SCR_002626) Copy   

•   Source: SciCrunch Registry

http://genome.ufl.edu/mapper/

A platform composed of three modules: the Database, the Search Engine, and rSNPs, for the computational identification of transcription factor binding sites (TFBSs) in multiple genomes, that combines TRANSFAC and JASPAR data with the search power of profile hidden Markov models (HMMs). The Database contains putative TFBSs found in the upstream sequences of genes from the human, mouse and D.melanogaster genomes. For each gene, they scanned the region from 10,000 base pairs upstream of the transcript start to 50 base pairs downstream of the coding sequence start against all their models. Therefore, the database contains putative binding sites in the gene promoter and in the initial introns and non-coding exons. Information displayed for each putative binding site includes the transcription factor name, its position (absolute on the chromosome, or relative to the gene), the score of the prediction, and the region of the gene the site belongs to. If the selected gene has homologs in any of the other two organisms, the program optionally displays the putative TFBSs in the homologs. The Search Engine allows the identification, visualization and selection of putative TFBSs occurring in the promoter or other regions of a gene from the human, mouse, D.melanogaster, C.elegans or S.cerevisiae genomes. In addition, it allows the user to upload a sequence to query and to build a model by supplying a multiple sequence alignment of binding sites for a transcription factor of interest. rSNPs MAPPER is designed to identify Single Nucleotide Polymorphisms (SNPs) that may have an effect on the presence of one or more TFBSs.

Proper citation: MAPPER - Multi-genome Analysis of Positions and Patterns of Elements of Regulation (RRID:SCR_003077) Copy   

•   Source: SciCrunch Registry

http://sonorus.princeton.edu/hefalmp/

HEFalMp (Human Experimental/FunctionAL MaPper) is a tool developed by Curtis Huttenhower in Olga Troyanskaya's lab at Princeton University. It was created to allow interactive exploration of functional maps. Functional mapping analyzes portions of these networks related to user-specified groups of genes and biological processes and displays the results as probabilities (for individual genes), functional association p-values (for groups of genes), or graphically (as an interaction network). HEFalMp contains information from roughly 15,000 microarray conditions, over 15,000 publications on genetic and physical protein interactions, and several types of DNA and protein sequence analyses and allows the exploration of over 200 H. sapiens process-specific functional relationship networks, including a global, process-independent network capturing the most general functional relationships. Looking to download functional maps? Keep an eye on the bottom of each page of results: every functional map of any kind is generated with a Download link at the bottom right. Most functional maps are provided as tab-delimited text to simplify downstream processing; graphical interaction networks are provided as Support Vector Graphics files, which can be viewed using the Adobe Viewer, any recent version of Firefox, or the excellent open source Inkscape tool.

Proper citation: Human Experimental/FunctionAL MaPper: Providing Functional Maps of the Human Genome (RRID:SCR_003506) 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://bioinformatics.charite.de/synsysnet/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. A curated database for synaptic proteins that provides adequate definitions of pre- and post-synaptic proteins, proteins present in sub-domains of the synapse, e.g. the synaptic vesicle and associated proteins, lipid rafts and postsynaptic density. In addition to data that was and will be gathered from the experiments conducted within SynSys - A European expertise Network on building the synapse, they have extracted and manually curated all relevant data on these proteins from other sources and provided an ontology for these. Novel splice forms are being identified that can be matched with proteomics data. Information on proteins, their 3D structure, binding small molecules Protein-Protein-Interactions (PPIs) and Compound-Protein-Interactions are integrated. Proteins or compounds can be searched and Interactive Networks can be visualized. The point Diseases present neurological diseases, to illustrate the role of SynSysNet in the medication.

Proper citation: SynSysNet (RRID:SCR_003180) Copy   

•   Source: SciCrunch Registry

http://www.lipidmaps.org/data/proteome/LMPD.php

Database of lipid related proteins representing human and mouse proteins involved in lipid metabolism. Collection of lipid related genes and proteins contains data for genes and proteins from Homo sapiens, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae, Caenorhabditis elegans, Escherichia coli, Macaca mulata, Drosophila melanogaster, Arabidopsis thaliana and Danio rerio.

Proper citation: LIPID MAPS Proteome Database (RRID:SCR_003062) 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.proweb.org/coddle/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Web-accessible program that identifies the region(s) of a user-selected gene and of its coding sequence (CDS) where the anticipated point mutations are most likely to result in deleterious effects on the gene's function. CODDLe separately handles 1) the prediction of changes which should truncate the protein and destabilize the RNA - nonsense changes and splice junction changes, and 2) the prediction of missense changes which should alter function of the gene product - those in conserved amino acid blocks in the CDS. Because the region(s) identified will be PCR amplified by the user and that amplicon will be used for polymorphism discovery, the application delivers primer pairs selected by Primer3 (Steve Rozen, Helen J. Skaletsky (1996,1997,1998)Primer3.) After selecting a primer pair, CODDLe returns a window with the selected amplicon and tabulates the effects of all possible polymorphisms which could be detected in that amplicon. CODDLe will not identify the regions of a gene where polymorphisms are most likely to be discovered. Others have shown that naturally occurring SNPs are found more often in the untranslated regions of a gene.

Proper citation: Coddle-Codons Optimized to Discover Deleterious LEsions (RRID:SCR_003003) Copy   

•   Source: SciCrunch Registry

http://xavante.fmrp.usp.br/mammibase/

Database developed to assist the phylogeneticist user in retrieving individual gene sequence alignments for genes in complete mammalian mitochondrial genomes. Data retrieval in MamMiBase requires three stages. At the first stage, the user must select the mammalian species or group that (s)he wishes to study. In the second stage, the user will select the outgroup from a list that included all species selected in the first stage plus Xenopus laevis and Gallus gallus. Finally, at the third stage, the user will select individual mitochondrial gene alignments or a phylogenetic tree that (s)he wishes to download.

Proper citation: Mammalian Mitochondrial Genomics Database (RRID:SCR_003084) Copy   

•   Source: SciCrunch Registry

http://biocomputer.bio.cuhk.edu.hk/T3DB/

Database aimed to annotate all bacterial Type III Secretion System (T3SS) related structure, effector, regulator, and auxiliary genes.

Proper citation: Type-III-Secretion-System related database (RRID:SCR_002941) Copy   

•   Source: SciCrunch Registry

http://ppdb.agr.gifu-u.ac.jp/ppdb/cgi-bin/index.cgi

A plant promoter database that provides information on transcription start sites (TSSs), core promoter structure and regulatory element groups (REGs) as putative and comprehensive transcriptional regulatory elements. Microarray data-based predictions have been appended as REG annotations which inform their putative physiological roles.

Proper citation: PPDB: Plant Promoter Database (RRID:SCR_003395) Copy   

•   Source: SciCrunch Registry

http://integrativebiology.org/

Database for molecular interaction information integrated with various other bio-entity information, including pathways, diseases, gene ontology (GO) terms, species and molecular types. The information is obtained from several manually curated databases and automatic extraction from literature. There are protein-protein interaction, gene/protein regulation and protein-small molecule interaction information stored in the database. The interaction information is linked with relevant GO terms, pathway, disease and species names. Interactions are also linked to the PubMed IDs of the corresponding abstracts the interactions were obtained from. Manually curated molecular interaction information was obtained from BioGRID, IntAct, NCBI Gene, and STITCH database. Pathway related information was obtained from KEGG database, Pathway Interaction database and Reactome. Disease information was obtained from PharmGKB and KEGG database. Gene ontology terms and related information was obtained from Gene Ontology database and GOA database.

Proper citation: Integrated Molecular Interaction Database (RRID:SCR_003546) Copy   

•   Source: SciCrunch Registry

http://150.216.56.64/index.php

Database platform for cotton expressed sequence tag (EST)-related information, covering assembled contigs, function annotation, analysis of GO and KEGG, SNP, miRNA, SSR-related marker information.

Proper citation: Cotton EST Database (RRID:SCR_003301) Copy   

•   Source: SciCrunch Registry

http://babelomics.bioinfo.cipf.es

An integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling. Version 4 of Babelomics integrates primary (normalization, calls, etc.) and secondary (signatures, predictors, associations, TDTs, clustering, etc.) analysis tools within an environment that allows relating genomic data and/or interpreting them by means of different functional enrichment or gene set methods. Such interpretation is made not only using functional definitions (GO, KEGG, Biocarta, etc.) but also regulatory information (from Transfac, Jaspar, etc.) and other levels of regulation such as miRNA-mediated interference, protein-protein interactions, text-mining module definitions and the possibility of producing de novo annotations through the Blast2GO system . Babelomics has been extensively re-engineered and now it includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. In this release GEPAS and Babelomics have integrated into a unique web application with many new features and improvements: * Data input: import and quality control for the most common microarray formats * Normalization and base calling: for the most common expression, tiling and SNP microarrays (Affymetrix and Agilent). * Transcriptomics: diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and time-series analysis. * Genotyping: stratification analysis, association, TDT. * Functional profiling: functional enrichment and gene set enrichment analysis with functional terms (GO, KEGG, Biocarta, etc.), regulatory (Transfac, Jaspar, miRNAs, etc.), text-mining, derived bioentities, protein-protein interaction analysis. * Integrative analysis: Different variables can be related to each other (e.g. gene expression to gnomic copy number) and the results subjected to functional analysis. Platform: Online tool

Proper citation: Babelomics (RRID:SCR_002969) 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.ncbi.nlm.nih.gov/gene/about-generif

A database and annotation tool that provides a simple mechanism to allow scientists to add to the functional annotation of genes described in Gene. To be processed, a valid Gene ID must exist for the specific gene, or the Gene staff must have assigned an overall Gene ID to the species. The latter case is implemented via records in Gene with the symbol NEWENTRY.

Proper citation: Gene Reference into Function (RRID:SCR_003436) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/genbank/tpa/

Database designed to capture experimental or inferential results that support submitter-provided annotation for sequence data that the submitter did not directly determine but derived from GenBank primary data. Records are divided into two categories: * TPA:experimental: Annotation of sequence data is supported by peer-reviewed wet-lab experimental evidence. * TPA:inferential: Annotation of sequence data by inference (where the source molecule or its product(s) have not been the subject of direct experimentation) TPA records are retrieved through the Nucleotide Database and feature information on the sequence, how it was cataloged, and proper way to cite the sequence information.

Proper citation: TPA (RRID:SCR_003593) Copy   

•   Source: SciCrunch Registry

https://www.hsph.harvard.edu/alkes-price/software/

Software application that uses genotyping data from SNP arrays for accurately inferring chromosomal segments of distinct continental ancestry in admixed populations, using dense genetic data. (entry from Genetic Analysis Software)

Proper citation: Hapmix (RRID:SCR_004203) Copy   

•   Source: SciCrunch Registry

http://yasuimac.bio.brandeis.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. Database and atlas of transgenic mouse lines that are generated by random insertion of enhancer trap probes. The trapped lines have highly restricted expression of tet transcription activator (some lines also have Cre DNA recombinase), which enables genetic manipulations in specific cell types.

Proper citation: Enhancer Trap Line Browser (RRID:SCR_003592) Copy   

•   Source: SciCrunch Registry

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

Database of three-dimensional structures of macromolecules that allows the user to retrieve structures for specific molecule types as well as structures for genes and proteins of interest. Three main databases comprise Structure-The Molecular Modeling Database; Conserved Domains and Protein Classification; and the BioSystems Database. Structure also links to the PubChem databases to connect biological activity data to the macromolecular structures. Users can locate structural templates for proteins and interactively view structures and sequence data to closely examine sequence-structure relationships. * Macromolecular structures: The three-dimensional structures of biomolecules provide a wealth of information on their biological function and evolutionary relationships. The Molecular Modeling Database (MMDB), as part of the Entrez system, facilitates access to structure data by connecting them with associated literature, protein and nucleic acid sequences, chemicals, biomolecular interactions, and more. It is possible, for example, to find 3D structures for homologs of a protein of interest by following the Related Structure link in an Entrez Protein sequence record. * Conserved domains and protein classification: Conserved domains are functional units within a protein that act as building blocks in molecular evolution and recombine in various arrangements to make proteins with different functions. The Conserved Domain Database (CDD) brings together several collections of multiple sequence alignments representing conserved domains, in addition to NCBI-curated domains that use 3D-structure information explicitly to define domain boundaries and provide insights into sequence/structure/function relationships. * Small molecules and their biological activity: The PubChem project provides information on the biological activities of small molecules and is a component of NIH''''s Molecular Libraries Roadmap Initiative. PubChem includes three databases: PCSubstance, PCBioAssay, and PCCompound. The PubChem data are linked to other data types (illustrated example) in the Entrez system, making it possible, for example, to retrieve information about a compound and then Link to its biological activity data, retrieve 3D protein structures bound to the compound and interactively view their active sites, and find biosystems that include the compound as a component. * Biological Systems: A biosystem, or biological system, is a group of molecules that interact directly or indirectly, where the grouping is relevant to the characterization of living matter. The NCBI BioSystems Database provides centralized access to biological pathways from several source databases and connects the biosystem records with associated literature, molecular, and chemical data throughout the Entrez system. BioSystem records list and categorize components (illustrated example), such as the genes, proteins, and small molecules involved in a biological system. The companion FLink icon FLink tool, in turn, allows you to input a list of proteins, genes, or small molecules and retrieve a ranked list of biosystems.

Proper citation: NCBI Structure (RRID:SCR_004218) Copy   

•   Source: SciCrunch Registry