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Found 12 result(s)

Human protein-protein interaction network database search

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<<<!!!<<< This repository is no longer available. >>>!!!>>> A human interactome map. The sequencing of the human genome has provided a surprisingly small number of genes, indicating that the complex organization of life is not reflected in the gene number but, rather, in the gene products – that is, in the proteins. These macromolecules regulate the vast majority of cellular processes by their ability to communicate with each other and to assemble into larger functional units. Therefore, the systematic analysis of protein-protein interactions is fundamental for the understanding of protein function, cellular processes and, ultimately, the complexity of life. Moreover, interactome maps are particularly needed to link new proteins to disease pathways and the identification of novel drug targets.

BeetleBase

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<<<!!!<<< This database doesn't exist anymore. 2017-09-05 >>>!!!>>>

Reactome

a curated pathway database

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Reactome is a manually curated, peer-reviewed pathway database, annotated by expert biologists and cross-referenced to bioinformatics databases. Its aim is to share information in the visual representations of biological pathways in a computationally accessible format. Pathway annotations are authored by expert biologists, in collaboration with Reactome editorial staff and cross-referenced to many bioinformatics databases. These include NCBI Gene, Ensembl and UniProt databases, the UCSC and HapMap Genome Browsers, the KEGG Compound and ChEBI small molecule databases, PubMed, and Gene Ontology.

Broad GDAC Firehose

Genome Data Analysis Center

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Born of the desire to systematize analyses from The Cancer Genome Atlas pilot and scale their execution to the dozens of remaining diseases to be studied, GDAC Firehose now sits atop terabytes of analysis-ready TCGA data and reliably executes thousands of pipelines per month. More information: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/

MozAtlas

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MozAtlas provides gene expression data of adult male and female mosquitoes as tables, expressions, trees and models. MozAtlas also provides sequence orthology relationships with data provided by FlyBase, Vectorbase, Beetlebase, BeeBase, and WormBase.

Genomes OnLine Database

GOLD

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GOLD is currently the largest repository for genome project information world-wide. The accurate and efficient genome project tracking is a vital criterion for launching new genome sequencing projects, and for avoiding significant overlap between various sequencing efforts and centers.

Cancer Genomics Hub

CGHub

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>>>>!!!!<<<< The Cancer Genomics Hub mission is now completed. The Cancer Genomics Hub was established in August 2011 to provide a repository to The Cancer Genome Atlas, the childhood cancer initiative Therapeutically Applicable Research to Generate Effective Treatments and the Cancer Genome Characterization Initiative. CGHub rapidly grew to be the largest database of cancer genomes in the world, storing more than 2.5 petabytes of data and serving downloads of nearly 3 petabytes per month. As the central repository for the foundational genome files, CGHub streamlined team science efforts as data became as easy to obtain as downloading from a hard drive. The convenient access to Big Data, and the collaborations that CGHub made possible, are now essential to cancer research. That work continues at the NCI's Genomic Data Commons. All files previously stored at CGHub can be found there. The Website for the Genomic Data Commons is here: https://gdc.nci.nih.gov/ >>>>!!!!<<<< The Cancer Genomics Hub (CGHub) is a secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects. Access to CGHub Data: All researchers using CGHub must meet the access and use criteria established by the National Institutes of Health (NIH) to ensure the privacy, security, and integrity of participant data. CGHub also hosts some publicly available data, in particular data from the Cancer Cell Line Encyclopedia. All metadata is publicly available and the catalog of metadata and associated BAMs can be explored using the CGHub Data Browser.

PANDIT

Protein and Associated Nucleotide Domains with Inferred Trees

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<<<!!!<<< Efforts to obtain renewed funding after 2008 were unfortunately not successful. PANDIT has therefore been frozen since November 2008, and its data are not updated since September 2005 when version 17.0 was released (corresponding to Pfam 17.0). The existing data and website remain available from these pages, and should remain stable and, we hope, useful. >>>!!!>>> PANDIT is a collection of multiple sequence alignments and phylogenetic trees. It contains corresponding amino acid and nucleotide sequence alignments, with trees inferred from each alignment. PANDIT is based on the Pfam database (Protein families database of alignments and HMMs), and includes the seed amino acid alignments of most families in the Pfam-A database. DNA sequences for as many members of each family as possible are extracted from the EMBL Nucleotide Sequence Database and aligned according to the amino acid alignment. PANDIT also contains a further copy of the amino acid alignments, restricted to the sequences for which DNA sequences were found.

SuperTarget

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<<<!!!<<< This repository is no longer available. >>>!!!>>>

Chemical Carcinogenesis Research Information System

CCRIS

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The repository is no longer available. <<<!!!<<< CCRIS information is migrated to PubChem (https://www.ncbi.nlm.nih.gov/pcsubstance?term=%22Chemical%20Carcinogenesis%20Research%20Information%20System%20(CCRIS)%22%5BSourceName%5D%20AND%20hasnohold%5Bfilt%5D) Help for CCRIS Users in PubChem: https://www.nlm.nih.gov/toxnet/Accessing_CCRIS_Content_from_PubChem.html or PDF: https://www.nlm.nih.gov/toxnet/Accessing_CCRIS_Content_from_PubChem.pdf. >>>!!!>>>

Pain Genes Database

PainGenesdb

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<<<!!!<<< The data are no longer accessible. Message: Adobe Flash Player is no longer supported >>>!!!>>>

PSnpBind

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PSnpBind is a large database of protein–ligand complexes covering a wide range of binding pocket mutations and small molecules’ landscape. This database can be used as a source of data for different types of studies, for example, developing machine learning algorithms to predict protein–ligand affinity or mutation's effect on it which requires an extensive amount of data with a wide coverage of mutation types and small molecules. Also, studies of protein-ligand interactions and conformer orientation changes across different mutated versions of a protein can be established using data from PSnpBind.