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The Gene database provides detailed information for known and predicted genes defined by nucleotide sequence or map position. Gene supplies gene-specific connections in the nexus of map, sequence, expression, structure, function, citation, and homology data. Unique identifiers are assigned to genes with defining sequences, genes with known map positions, and genes inferred from phenotypic information. These gene identifiers are used throughout NCBI's databases and tracked through updates of annotation. Gene includes genomes represented by NCBI Reference Sequences (or RefSeqs) and is integrated for indexing and query and retrieval from NCBI's Entrez and E-Utilities systems.
>>>!!!<<< Noticed 26.08.2020: The NCI CBIIT instance of the CGAP no longer exist on this website. The Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer has a new home at the NCI-funded Institute for Systems Biology Cancer Genomics Cloud available at the following location: https://mitelmandatabase.isb-cgc.org >>>!!!<<<
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>>>!!! <<< 2021-09-01: repository is offline >>>!!!<<< Background: Many studies have been conducted to detect quantitative trait loci (QTL) in dairy cattle. However, these studies are diverse in terms of their differing resource populations, marker maps, phenotypes, etc, and one of the challenges is to be able to synthesise this diverse information. This web page has been constructed to provide an accessible database of studies, providing a summary of each study, facilitating an easier comparison across studies. However, it also highlights the need for uniform reporting of results of studies, to facilitate more direct comparisons being made. Description: Studies recorded in this database include complete and partial genome scans, single chromosome scans, as well as fine mapping studies, and contain all known reports that were published in peer-reviewed journals and readily available conference proceedings, initially up to April 2005. However, this data base is being added to, as indicated by the last web update. Note that some duplication of results will occur, in that there may be a number of reports on the same resource population, but utilising different marker densities or different statistical methodologies. The traits recorded in this map are milk yield, milk composition (protein yield, protein %, fat yield, fat %), and somatic cell score (SCS).