NIDA Neuroproteomics Center
As the number of life science databases and analytic tools increase, the interoperation of such databases and tools has become important. The growing number, heterogeneity, and variety of databases and tools have posed a major interoperability challenge. We tackle this challenge by exploring efficient and innovative approaches involving the use of XML, semantic web, metadata, distributed computing, and high performance computing. We have been collaborating with many faculty members in different departments and core facilities including Genetics, Biology, Computer Science, Biostatistics, Yale Keck Microarray Facility, and Yale Keck Protein Profiling Facility. Our research is carried out in the context of integrating and analyzing: a) microarray data, b) proteomics data including mass spectrometry (MS) data, c) allele frequency data, d) yeast genome data, and e) neuroscience data. Related projects include: a) Yale Microarray Database (YMD), b) Yale Protein Expression Database (YPED), c) Allele Frequency Database (ALFRED), d) YeastHub, and e) SenseLab.
Extensive Research Description
- Yale Microarray Database: An institution-wide database for use by microarray researchers at Yale and outside of Yale
- Yeast transposon-insertion genome project PhenoDB: a database program that manages and analyzes genotype/phenotype data in support of population and pedigree gen
- Ryslik GA, Cheng Y, Cheung KH, Modis Y, Zhao H. (2013) Utilizing protein structure to identify non-random somatic mutations. BMC Bioinformatics 14:190.
- Holford ME, McCusker JP, Cheung KH, Krauthammer M. (2012) A semantic web framework to integrate cancer omics data with biological knowledge. BMC Bioinformatics 13 Suppl 1:S10.
- Cheung KH, Samwald M, Auerbach RK, Gerstein MB. (2010) Structured digital tables on the Semantic Web: toward a structured digital literature. Mol Syst Biol. 6:403.
- Lam H.Y., et al. (2007). AlzPharm: integration of neurodegeneration data using RDF. BMC Bioinformatics 8 (Suppl. 3):S4.
- Cheung, K.H., et al. (2005). YeastHub: a semantic web use case for integrating data in the life sciences domain. Bioinformatics 21(Suppl. 1):i85-96.