HiCOMB 2019 - 2019 18th IEEE International Workshop on High Performance Computational Biology

The size and complexity of genome- and proteome-scale data sets in bioinformatics continues to grow at a furious pace, and the analysis of these complex, noisy, data sets demands efficient algorithms and high performance computer architectures. Hence high-performance computing has become an integral part of research and development in bioinformatics, computational biology, and medical and health informatics. 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: (a) parallel and distributed algorithms, (b) memory-efficient algorithms, (c) large scale data mining techniques including approaches for big data and cloud computing, (d) algorithms on multicores and accelerators such as GPUs and FPGAs, and (e) design of high-performance software and hardware for biological applications. Works representing novel use of HPC tools on emerging technologies and applications within computational biology (e.g., precision medicine/agriculture, long reads, microbiome, synthetic biology) are particularly encouraged.
The workshop will feature contributed papers as well as invited talks from reputed researchers in the field.
Topics of interest include but are not limited to:
Bioinformatics databases
Computational genomics and metagenomics
Computational proteomics and metaproteomics
Scalable genome assembly, clustering and read mapping
Scalable transcriptomic analysis with RNASeq and microarrays
Parallel biological sequence analysis
Biological network analysis
Scaling machine learning applications in bioinformatics
HPC solutions for biomedical image analysis
Parallel algorithms for evolutionary and phylogenetic reconstruction
High performance algorithms and big data solutions for systems biology
Protein structure prediction and modeling
Parallel algorithms in chemical genetics and chemical informatics
Parallel architectures for biological applications
Cloud-enabled solutions for computational biology
Energy-aware high performance biological applications