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http://www.nematodes.org/nematodegenomes/index.php/Main_Page

A collaborative wiki that collates information on completed, ongoing and planned genome and transcriptome sequencing projects on species from phylum Nematoda. The intention is to encourage genome sequencing across the diversity of the phylum Nematoda. Wiki includes: * Published complete nematode genomes: A dynamically generated table of all species for which the genome is published. * Nematode species with genomes in progress: A dynamically generated table of all species for which a genome project is underway. Users may add species to the list * Proposed nematode genome projects: To propose a species for genome sequencing, edit its species page, and set the genome project status to proposed. * BLAST server: Search a number of the nematode-genomes-in-progress with genes of your choice. Currently there are 12 draft genomes available... * Genomes with Data available: Genomes with data available for download. Users may add more data URLs to strain pages or update the URLs.

Proper citation: 959 Nematode Genomes (RRID:SCR_006068) Copy   

•   Source: SciCrunch Registry

http://mmdb.iab.keio.ac.jp/

MMMDB, Mouse Multiple tissue Metabolome DataBase, is a freely available metabolomic database containing a collection of metabolites measured from multiple tissues from single mice. The datases are collected using a single instrument and not integrated from literatures, which is useful for capturing the holistic overview of large metabolomic pathway. Currently data from cerabra, cerebella, thymus, spleen, lung, liver, kidney, heart, pancreas, testis, and plasma are provided. Non-targeted analyses were performed by capillary electropherograms time-of-flight mass spectrometry (CE-TOFMS) and, therefore, both identified metabolites and unknown (without matched standard) peaks were uploaded to this database. Not only quantified concentration but also processed raw data such as electropherogram, mass spectrometry, and annotation (such as isotope and fragment) are provided.

Proper citation: MMMDB - Mouse Multiple tissue Metabolome DataBase (RRID:SCR_006064) Copy   

•   Source: SciCrunch Registry

http://biodev.cea.fr/interevol/

InterEvol database is designed for the analysis of co-evolution events at the interface of known structures of hetero- and homo-oligomers. The database can be search and analyzed through 3 interconnected levels of analysis: * From a Keyword or the PDB entry of a complex, you can browse: ** structural homologs for every chain in other complexes ** structural interologs for every interface ** retrieve pre-computed sequence alignments in diverse species * From 1 or 2 sequences of interacting partners: ** build 2 multiple sequence alignments with the same species ordered in each ** query the InterEvol database with alignments using profile-profile comparison method * Visualize structure vs sequence alignment at the complex interface ** A dedicated Pymol plugin is provided ** Alignment views in Pymol are interactively restricted to the residues selected at the interface

Proper citation: InterEvol database (RRID:SCR_006054) Copy   

•   Source: SciCrunch Registry

http://www.umd.be/BRCA1/

The UMD-BRCA1/BRCA2 databases have been set up in a joined national effort through the network of 16 diagnostic laboratories to provide up-to-date information about mutations of the BRCA1 and BRCA2 genes identified in patients with breast and/or ovarian cancer. These databases currently contain published and unpublished information about the BRCA1/BRCA2 mutations reported in French diagnostic laboratories. This database includes 28 references and 5530 mutations (1440 different mutations and 786 protein variants) The databases of BRCA1 and BRCA2 mutations were built using the Universal Mutation Database tool. For each mutation, information is provided at several levels: * at the gene level: exon and codon number, wild type and mutant codon, mutation event, mutation name and, * at the protein level: wild type and mutant amino acid, binding domain, affected domain. If you want to submit a mutation, please contact R. Lidereau., S. Caputo. or E. Rouleau.

Proper citation: UMD-BRCA1/ BRCA2 databases (RRID:SCR_006128) Copy   

•   Source: SciCrunch Registry

https://github.com/stamatak/standard-RAxML

Software program for phylogenetic analyses of large datasets under maximum likelihood.

Proper citation: RAxML (RRID:SCR_006086) Copy   

•   Source: SciCrunch Registry

http://ogeedb.embl.de/#summary

Online GEne Essentiality database containing genes that were tested experimentally for essentiality and their features; it also provides a set of tools to systematically explore and analyze these data. The main purpose of this project is to better understand gene essentiality by facilitating the comparisons of the differences and similarities between essential and non-essential genes. This is achieved by collecting not only experimentally tested essential and non-essential genes, but also associated gene features such as expression profiles, duplication status, conservation across species, evolutionary origins and involvement in embryonic development. We focus on large-scale experiments and complement our data with text-mining results. Genes are organized into data sets according to their sources. Genes with variable essentiality status across data sets are tagged as conditionally essential, highlighting the complex interplay between gene functions and environments. Linked tools allow the user to compare gene essentiality among different gene groups, or compare features of essential genes to non-essential genes, and visualize the results. Why is it different from existing databases? * we included both essential and non-essential genes so that we could better understand the gene essentiality by comparing the similarities and differences between the two gene sets; * we compiled a list of features for each gene, including whether they are duplicates or involved in development, the number of other homologous genes in the same genome, as well as their earliest expression stages during development. These features are keys to understand the essentiality of genes; * we also provide a set of tools to explore our data and visualize the results. For example, users can simply divide genes into two groups according to whether they are duplicates, calculate the proportion of essential genes (PE%) in each group and then visualize the results in a bar plot; or they can classify genes into multiple groups according to their earliest expression stages during evolution, compare the essentiality of genes that were expressed earlier with those were latter, and plot the results in a line chart.

Proper citation: OGEE - Online GEne Essentiality database (RRID:SCR_006080) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/bioinformatics/PRED-GPCR/

A prediction tool for GPCR Family Classification from sequence alone based on a probabilistic method that uses family-specific profile Hidden Markov Models. The PRED-GPCR system is based on a probabilistic method that uses family specific profile HMMs in order to determine to which GPCR family a query sequence belongs or resembles. The approach proposed in this method exploits the descriptive power of profile HMMs along with an exhaustive discrimination assessment method to select only highly selective and sensitive profiles, for each family. The collection of these profiles constitutes a signature library, which is scanned, for significant matches with a given query sequence. The output report for a query sequence consists of two sections: * A ranked list of the profile HMM matches, below the selected individual motif E-value cutoff, along with their corresponding family. * A ranked list of the Combined P-values, E-values as well as the number of profiles matched for each family. To cross-evaluate your results you can browse through Swiss-Prot, Trembl, Pfam and Prosite family related entries.

Proper citation: PRED-GPCR (RRID:SCR_006196) Copy   

•   Source: SciCrunch Registry

http://db-mml.sjtu.edu.cn/ICEberg/

ICEberg is an integrated database that provides comprehensive information about integrative and conjugative elements (ICEs) found in bacteria. ICEs are conjugative self-transmissible elements that can integrate into and excise from a host chromosome. An ICE contains three typical modules, integration and excision, conjugation, and regulation modules, that collectively promote vertical inheritance and periodic lateral gene flow. Many ICEs carry likely virulence determinants, antibiotic-resistant factors and/or genes coding for other beneficial traits. ICEberg offers a unique, highly organized, readily explorable archive of both predicted and experimentally supported ICE-relevant data. It currently contains details of 428 ICEs found in representatives of 124 bacterial species, and a collection of >400 directly related references. A broad range of similarity search, sequence alignment, genome context browser, phylogenetic and other functional analysis tools are readily accessible via ICEberg. ICEberg will facilitate efficient, multidisciplinary and innovative exploration of bacterial ICEs and be of particular interest to researchers in the broad fields of prokaryotic evolution, pathogenesis, biotechnology and metabolism. The ICEberg database will be maintained, updated and improved regularly to ensure its ongoing maximum utility to the research community.

Proper citation: ICEberg (RRID:SCR_006026) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

•   Source: SciCrunch Registry

http://www.mged.org/mage-tab/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 27,2023. A simple tab-delimited, spreadsheet-based format which will become a part of the MAGE microarray data standard that can be used for annotating and communicating microarray data in a MIAME compliant fashion. MAGE-TAB will enable laboratories without bioinformatics experience or support to manage, exchange and submit well-annotated microarray data in a standard format using a spreadsheet. The MAGE-TAB format is self-contained, and does not require an understanding of MAGE-ML or XML.

Proper citation: MAGE-TAB (RRID:SCR_003222) Copy   

•   Source: SciCrunch Registry

http://bibiserv.techfak.uni-bielefeld.de/rnahybrid/

Software tool for finding the minimum free energy hybridization of a long and a short RNA. The hybridization is performed in a kind of domain mode, i.e., the short sequence is hybridized to the best fitting part of the long one. The tool is primarily meant as a means for microRNA target prediction.

Proper citation: RNAhybrid (RRID:SCR_003252) Copy   

•   Source: SciCrunch Registry

https://planttfdb.gao-lab.org/

Comprehensive plant transcription factor database. Interface to allow users to search the database by IDs or free texts, to make sequence similarity search against TFs of all or individual species, and to download TF sequences for local analysis.PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors

Proper citation: PLANTTFDB (RRID:SCR_003362) Copy   

•   Source: SciCrunch Registry

http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/

Software R package for weighted correlation network analysis. WGCNA is also available as point-and-click application. Unfortunately this application is not maintained anymore. It is known to have compatibility problems with R-2.8.x and newer, and the methods it implements are not all state of the art., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Weighted Gene Co-expression Network Analysis (RRID:SCR_003302) Copy   

•   Source: SciCrunch Registry

http://www.qgene.org/

A free, open-source, computationally efficient Java program for comparative analyses of QTL mapping data and population simulation that runs on any computer operating system. (entry from Genetic Analysis Software) It is written with a plug-in architecture for ready extensibility. The software accommodates line-cross mating designs consisting of any arbitrary sequence of selfing, backcrossing, intercrossing and haploid-doubling steps that includes map, population, and trait simulators; and is scriptable. Source code is available on request.

Proper citation: QGene (RRID:SCR_003209) Copy   

•   Source: SciCrunch Registry

http://www.xenbase.org/

Data collection for Xenopus laevis and Xenopus tropicalis biology and genomics.

Proper citation: Xenbase (RRID:SCR_003280) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/genomation/

Software R package for simplfiying common tasks in genomic feature analysis. Toolkit to summarize, annotate and visualize genomic intervals. Provides functions for reading BED and GFF files as GRanges objects, summarizing genomic features over predefined windows so users can make average enrichment of features over defined regions or produce heatmaps. Can annotate given regions with other genomic features such as exons,introns and promoters.

Proper citation: genomation (RRID:SCR_003435) Copy   

•   Source: SciCrunch Registry

http://biorxiv.org/

A free archive and distribution service for unpublished preprints in the life sciences allowing authors to make their findings immediately available to the scientific community and receive feedback on draft manuscripts before they are submitted to journals. An article may be posted prior to, or concurrently with, submission to a journal but should not be posted if it has already been published. Once an article is published in a journal, bioRxiv will update the preprint with a link to the published version.

Proper citation: bioRxiv (RRID:SCR_003933) Copy   

•   Source: SciCrunch Registry

http://git-scm.com/

A free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. Git is easy to learn and has a tiny footprint with lightning fast performance. It outclasses SCM tools like Subversion, CVS, Perforce, and ClearCase with features like cheap local branching, convenient staging areas, and multiple workflows.

Proper citation: Git (RRID:SCR_003932) Copy   

•   Source: SciCrunch Registry

http://pubchem.ncbi.nlm.nih.gov/

Collection of information about chemical structures and biological properties of small molecules and siRNA reagents hosted by the National Center for Biotechnology Information (NCBI).

Proper citation: PubChem (RRID:SCR_004284) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/pdbe/

The European resource for the collection, organization and dissemination of data on biological macromolecular structures. In collaboration with the other worldwide Protein Data Bank (wwPDB) partners - the Research Collaboratory for Structural Bioinformatics (RCSB) and BioMagResBank (BMRB) in the USA and the Protein Data Bank of Japan (PDBj) - they work to collate, maintain and provide access to the global repository of macromolecular structure data. The main objectives of the work at PDBe are: * to provide an integrated resource of high-quality macromolecular structures and related data and make it available to the biomedical community via intuitive user interfaces. * to maintain in-house expertise in all the major structure-determination techniques (X-ray, NMR and EM) in order to stay abreast of technical and methodological developments in these fields, and to work with the community on issues of mutual interest (such as data representation, harvesting, formats and standards, or validation of structural data). * to provide high-quality deposition and annotation facilities for structural data as one of the wwPDB deposition sites. Several sophisticated tools are also available for the structural analysis of macromolecules.

Proper citation: PDBe - Protein Data Bank in Europe (RRID:SCR_004312) Copy   

•   Source: SciCrunch Registry