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http://www.ihop-net.org/UniPub/iHOP/

Information system that provides a network of concurring genes and proteins extends through the scientific literature touching on phenotypes, pathologies and gene function. It provides this network as a natural way of accessing millions of PubMed abstracts. By using genes and proteins as hyperlinks between sentences and abstracts, the information in PubMed can be converted into one navigable resource, bringing all advantages of the internet to scientific literature research. Moreover, this literature network can be superimposed on experimental interaction data (e.g., yeast-two hybrid data from Drosophila melanogaster and Caenorhabditis elegans) to make possible a simultaneous analysis of new and existing knowledge. The network contains half a million sentences and 30,000 different genes from humans, mice, D. melanogaster, C. elegans, zebrafish, Arabidopsis thaliana, yeast and Escherichia coli.

Proper citation: Information Hyperlinked Over Proteins (RRID:SCR_004829) Copy   

•   Source: SciCrunch Registry

http://marrvel.org/

Web tool to search multiple public variant databases simultaneously and provide a unified interface to facilitate the search process. Used for integration of human and model organism genetic resources to facilitate functional annotation of the human genome. Used for analysis of human genes and variants by cross-disciplinary integration of records available in public databases to facilitate clinical diagnosis and basic research.

Proper citation: MARRVEL (RRID:SCR_016871) Copy   

•   Source: SciCrunch Registry

https://bsa4yeast.lcsb.uni.lu

Web application for Quantitative Trait Loci mapping via bulk segregant analysis of yeast sequencing data. Application provides automated data processing, annotations, and web interface to explore identified QTLs.

Proper citation: BSA4Yeast (RRID:SCR_017113) Copy   

•   Source: SciCrunch Registry

http://www.candidagenome.org/

Database of genetic and molecular biological information about Candida albicans. Contains information about genes and proteins, descriptions and classifications of their biological roles, molecular functions, and subcellular localizations, gene, protein, and chromosome sequence information, tools for analysis and comparison of sequences and links to literature information. Each CGD gene or open reading frame has an individual Locus Page. Genetic loci that are not tied to DNA sequence also have Locus Pages. Provides Gene Ontology, GO, to all its users. Three ontologies that comprise GO (Molecular Function, Cellular Component, and Biological Process) are used by multiple databases to annotate gene products, so that this common vocabulary can be used to compare gene products across species. Development of ontologies is ongoing in order to incorporate new information. Data submissions are welcome.

Proper citation: Candida Genome Database (RRID:SCR_002036) Copy   

•   Source: SciCrunch Registry

http://www.chibi.ubc.ca/Gemma

Resource for reuse, sharing and meta-analysis of expression profiling data. Database and set of tools for meta analysis, reuse and sharing of genomics data. Targeted at analysis of gene expression profiles. Users can search, access and visualize coexpression and differential expression results.

Proper citation: Gemma (RRID:SCR_008007) Copy   

•   Source: SciCrunch Registry

http://www.openbioinformatics.org/annovar/

An efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes (including human genome hg18, hg19, as well as mouse, worm, fly, yeast and many others). Given a list of variants with chromosome, start position, end position, reference nucleotide and observed nucleotides, ANNOVAR can perform: 1. gene-based annotation. 2. region-based annotation. 3. filter-based annotation. 4. other functionalities. (entry from Genetic Analysis Software)

Proper citation: ANNOVAR (RRID:SCR_012821) Copy   

•   Source: SciCrunch Registry

http://dip.doe-mbi.ucla.edu/

Database to catalog experimentally determined interactions between proteins combining information from a variety of sources to create a single, consistent set of protein-protein interactions that can be downloaded in a variety of formats. The data were curated, both, manually and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Because the reliability of experimental evidence varies widely, methods of quality assessment have been developed and utilized to identify the most reliable subset of the interactions. This CORE set can be used as a reference when evaluating the reliability of high-throughput protein-protein interaction data sets, for development of prediction methods, as well as in the studies of the properties of protein interaction networks. Tools are available to analyze, visualize and integrate user's own experimental data with the information about protein-protein interactions available in the DIP database. The DIP database lists protein pairs that are known to interact with each other. By interact they mean that two amino acid chains were experimentally identified to bind to each other. The database lists such pairs to aid those studying a particular protein-protein interaction but also those investigating entire regulatory and signaling pathways as well as those studying the organization and complexity of the protein interaction network at the cellular level. Registration is required to gain access to most of the DIP features. Registration is free to the members of the academic community. Trial accounts for the commercial users are also available.

Proper citation: Database of Interacting Proteins (DIP) (RRID:SCR_003167) Copy   

•   Source: SciCrunch Registry

http://www.peptideatlas.org

Multi-organism, publicly accessible compendium of peptides identified in a large set of tandem mass spectrometry proteomics experiments. Mass spectrometer output files are collected for human, mouse, yeast, and several other organisms, and searched using the latest search engines and protein sequences. All results of sequence and spectral library searching are subsequently processed through the Trans Proteomic Pipeline to derive a probability of correct identification for all results in a uniform manner to insure a high quality database, along with false discovery rates at the whole atlas level. The raw data, search results, and full builds can be downloaded for other uses. All results of sequence searching are processed through PeptideProphet to derive a probability of correct identification for all results in a uniform manner ensuring a high quality database. All peptides are mapped to Ensembl and can be viewed as custom tracks on the Ensembl genome browser. The long term goal of the project is full annotation of eukaryotic genomes through a thorough validation of expressed proteins. The PeptideAtlas provides a method and a framework to accommodate proteome information coming from high-throughput proteomics technologies. The online database administers experimental data in the public domain. You are encouraged to contribute to the database.

Proper citation: PeptideAtlas (RRID:SCR_006783) Copy   

•   Source: SciCrunch Registry