The power of protein interaction networks for associating genes with diseases

http://bioinformatics.oxfordjournals.org/cgi/content/full/26/8/1057

The power of protein interaction networks for associating genes with diseases
Saket Navlakha and Carl Kingsford *

Center for Bioinformatics and Computational Biology, Institute for Advanced Computer Studies and Department of Computer Science, University of Maryland College Park, College Park, MD 20742, USA

Motivation: Understanding the association between genetic diseases and their causal genes is an important problem concerning human health. With the recent influx of high-throughput data describing interactions between gene products, scientists have been provided a new avenue through which these associations can be inferred. Despite the recent interest in this problem, however, there is little understanding of the relative benefits and drawbacks underlying the proposed techniques.


DATA AND TEXT MINING

David C. Trudgian, Benjamin Thomas, Simon J. McGowan, Benedikt M. Kessler, Mogjiborahman Salek, and Oreste Acuto
CPFP: a central proteomics facilities pipeline
Bioinformatics Advance Access published on February 25, 2010
Bioinformatics 2010 26: 1131-1132; doi:10.1093/bioinformatics/btq081 [Abstract] [Full Text] [Print PDF]

DATABASES AND ONTOLOGIES

Nobuhiko Tanaka, Kazunori Waki, Hideki Kaneda, Tomohiro Suzuki, Ikuko Yamada, Tamio Furuse, Kimio Kobayashi, Hiromi Motegi, Hideaki Toki, Maki Inoue, Osamu Minowa, Tetsuo Noda, Keizo Takao, Tsuyoshi Miyakawa, Aki Takahashi, Tsuyoshi Koide, Shigeharu Wakana, and Hiroshi Masuya
SDOP-DB: a comparative standardized-protocol database for mouse phenotypic analyses
Bioinformatics Advance Access published on March 1, 2010
Bioinformatics 2010 26: 1133-1134; doi:10.1093/bioinformatics/btq095

http://nar.oxfordjournals.org/cgi/content/full/33/suppl_1/D358
Nucleic Acids Research, Vol. 33, Database issue © Oxford University Press 2005; all rights reserved
The Candida Genome Database (CGD), a community resource for Candida albicans gene and protein information
Martha B. Arnaud*, Maria C. Costanzo, Marek S. Skrzypek, Gail Binkley, Christopher Lane, Stuart R. Miyasato and Gavin Sherlock

Department of Genetics, Stanford University School of Medicine, CCSR 2255, 269 Campus Drive, Stanford, CA 94305-5120, USA

The Candida Genome Database (CGD) is a new database that contains genomic information about the opportunistic fungal pathogen Candida albicans. CGD is a public resource for the research community that is interested in the molecular biology of this fungus. CGD curators are in the process of combing the scientific literature to collect all C.albicans gene names and aliases; to assign gene ontology terms that describe the molecular function, biological process, and subcellular localization of each gene product; to annotate mutant phenotypes; and to summarize the function and biological context of each gene product in free-text description lines. CGD also provides community resources, including a reservation system for gene names and a colleague registry through which Candida researchers can share contact information and research interests. CGD is publicly funded (by NIH grant R01 DE15873-01 from the NIDCR) and is freely available at http://www.candidagenome.org/.