High-performance computing methods for computational genomics

Srinivas Aluru, David Bader, Ananth Kalyanaraman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


The high computational requirements of several applications in computational genomics are aggravated by an exponential growth in biological databases. This tutorial will provide a detailed introduction to high-performance computing methods designed to address various large-scale problems in computational genomics. First, we will describe mpiBLAST and ScalaBLAST, which are parallelizations of the NCBI BLAST suite of programs used for querying against large sequence databases. Next, we will describe PaCE, which is a parallel DNA sequence clustering algorithm with applications to clustering Expressed Sequence Tags and whole genome assembly. Next, we describe GRAPPA, which is a high-performance software suite developed for phylogenetic reconstruction of a collection of organisms or genes. Throughout the tutorial, emphasis will be on scalability and effectiveness in exploiting large-scale state-of-the-art supercomputing technologies.The intended audience are academic and industry researchers, educators, and/or commercial application developers, with a computational background.

Original languageEnglish (US)
Title of host publicationProceedings of the 2006 ACM/IEEE Conference on Supercomputing, SC'06
StatePublished - 2006
Externally publishedYes

Publication series

NameProceedings of the 2006 ACM/IEEE Conference on Supercomputing, SC'06

All Science Journal Classification (ASJC) codes

  • General Computer Science


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