title: Lecture notes: 2010 and beyond, the decade of high-performance computing for the next-generation sequence analysis.
abstract: Effective analysis of the next-generation sequence relies on the intelligent algorithms for handling the meta-genome, epigenetic and disease genome, as well as immune-genome, viral profiling, transcriptome profiling, and de novo genome sequencing data, therefore, next-generation sequence analysis is a very important but challenging task in bioinformatics due to extremely large-scale 'noisy' datasets. We focus mainly on the development of high-performance genetic algorithms based on multi-core technology as an example and open to fast-moving competing platforms to be emerged.
authors.affiliation: Department of Health and Human Services, Oak Ridge, DOE, United States National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20852, USA. yangma@mail.NIH.gov
authors.forename: Mary Qu
authors.initials: MQ
authors.lastname: Yang
authors.forename: Jack Y
authors.initials: JY
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D017421:Sequence Analysis / Q000379:methods*