High–performance computing is an integral part of research and development in bioinformatics/computational biology and medical and health informatics. The large size and complexity of biological data sets, and inherent complexity of the underlying biological problems have collectively resulted in large run–time and memory requirements. The goal of this workshop is to provide a forum for discussion of latest research in developing high–performance computing solutions to data– and compute–intensive problems arising from all areas of computational life sciences. We are especially interested in parallel and distributed algorithms, memory–efficient algorithms, large scale data mining techniques, including approaches for big data and cloud computing, algorithms on multicores, manycores and GPUs, and design of high–performance software and hardware for biological applications.<br>The workshop will feature contributed papers as well as invited talks from reputed researchers in the field.<br>Topics of interest include but are not limited to:<br>Bioinformatic databases<br>Computational genomics and metagenomics<br>Computational proteomics and metaproteomics<br>DNA assembly, clustering, and mapping<br>Gene expression analysis with RNASeq and microarrays<br>Gene identification and annotation<br>Parallel algorithms for biological sequence analysis<br>Parallel architectures for biological applications<br>Molecular evolution and phylogenetic reconstruction algorithms<br>Protein structure prediction and modeling<br>Parallel algorithms in chemical genetics and chemical informatics<br>High performance algorithms for systems biology<br>Big data solutions for systems biology<br>Cloud–enabled solutions for computational biology<br>Energy–aware high performance biological applications<br>
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HiCOMB
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City
Chicago
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United States
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