Bhave Sanjiv V, Hornbaker Cheryl, Phang Tzu L, Saba Laura, Lapadat Razvan, Kechris Katherina, Gaydos Jeanette, McGoldrick Daniel, Dolbey Andrew, Leach Sonia, Soriano Brian, Ellington Allison, Ellington Eric, Jones Kendra, Mangion Jonathan, Belknap John K, Williams Robert W, Hunter Lawrence E, Hoffman Paula L, Tabakoff Boris
Department of Pharmacology, University of Colorado at Denver and Health Sciences Center, Aurora, CO 80045, USA.
BMC Genet. 2007 Aug 30;8:59. doi: 10.1186/1471-2156-8-59.
With the advent of "omics" (e.g. genomics, transcriptomics, proteomics and phenomics), studies can produce enormous amounts of data. Managing this diverse data and integrating with other biological data are major challenges for the bioinformatics community. Comprehensive new tools are needed to store, integrate and analyze the data efficiently.
The PhenoGen Informatics website http://phenogen.uchsc.edu is a comprehensive toolbox for storing, analyzing and integrating microarray data and related genotype and phenotype data. The site is particularly suited for combining QTL and microarray data to search for "candidate" genes contributing to complex traits. In addition, the site allows, if desired by the investigators, sharing of the data. Investigators can conduct "in-silico" microarray experiments using their own and/or "shared" data.
The PhenoGen website provides access to tools that can be used for high-throughput data storage, analyses and interpretation of the results. Some of the advantages of the architecture of the website are that, in the future, the present set of tools can be adapted for the analyses of any type of high-throughput "omics" data, and that access to new tools, available in the public domain or developed at PhenoGen, can be easily provided.
随着“组学”(如基因组学、转录组学、蛋白质组学和表型组学)的出现,研究能够产生海量数据。管理这些多样的数据并与其他生物学数据整合,是生物信息学界面临的主要挑战。需要全新的综合工具来高效存储、整合和分析数据。
PhenoGen网站提供了可用于高通量数据存储、分析和结果解读的工具。该网站架构的一些优点在于,未来现有的这套工具可适用于任何类型的高通量“组学”数据的分析,并且能够轻松提供对公共领域可用或PhenoGen开发的新工具的访问。