[hpc-announce] HiCOMB 2021 (IPDPS Workshop) - Deadline Extended to February 5th, 2021

[Alba Cristina Magalhaes Alves De Melo]

We apologize if you receive this email multiple times.

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HiCOMB 2021 Call For Papers
18th IEEE International Workshop on High Performance Computational Biology
May 17, 2021
To be held in conjunction with IPDPS’21
Portland, OR (now Virtual)
http://www.hicomb.org/


Paper submission:                      February 5, 2021 by 11:59pm AoE (*Extended*)
Author notification:                    February 28, 2021
Final camera-ready papers due: March 12, 2021
Workshop:                                  May 17, 2021

Submission types:
* regular papers (up to 10 pages)
* short papers (up to 4 pages)
* extended abstracts (1 page)
Submitted manuscripts may not exceed ten (10) single-spaced double-column pages using a 10-point size font on 8.5x11 inch pages (IEEE conference style), including figures, tables, and references (see IPDPS Call for Papers for more details). All papers will be reviewed by three or more referees.

Proceedings option:
This year, the authors of the accepted papers will be given a choice on whether to have the paper appear in the IPDPSW Proceedings (which will be digitally indexed and archived as part of the IEEE Xplore Digital Library). If the authors choose not to make it part of the proceedings, then the paper will not be considered archival. In either case, all accepted papers will be posted online on the workshop website, and all accepted papers (archived or not) will have an oral presentation slot at the workshop by one of the authors of the paper.
To submit a paper, please upload a PDF file through the HiCOMB 2021 submission link, which is available on the HiCOMB website.

Topics:
The size and complexity of genomic and biomedical big data continue to grow at a furious pace, and the analysis of these complex, noisy, data sets demands efficient algorithms and high performance computing architectures. Hence, high-performance computing (HPC) has become an integral part of research and development in bioinformatics, computational biology, and medical and health informatics. The goal of the HiCOMB workshop is to showcase novel HPC research and technologies to solve data- and compute-intensive problems arising from all areas of computational life sciences. The workshop will feature contributed papers as well as invited talks from reputed researchers in the field.

For peer-reviewed papers, we invite authors to submit original and previously unpublished work that are at the intersection of the "pillars" of modern day computational life sciences and HPC.  More specifically, we encourage submissions from all areas of biology that can benefit from HPC, and from all areas of HPC that need new development to address the class of computational problems that originate from biology.

Areas of interest within computational life sciences include (but not limited to):
- Biological sequence analysis (genome assembly, long/short read data structures, read mapping, clustering, variant analysis, error correction, genome annotation)
- Computational structural biology (protein structure, RNA structure)
- Functional genomics (transcriptomics, RNAseq/microarrays, single cell analysis,  proteomics, phospho-proteomics)
- Systems biology and networks (biological network analysis, gene regulatory networks, metabolomics, molecular pathways)
- Tools for integrated multi-omics and biological databases (network construction, modeling, link inference)
- Computational modeling and simulation of biological systems (molecular dynamics, protein structure/docking, dynamic models)
- Phylogeny (phylogenetic tree reconstruction, molecular evolution)
- Microbes and microbiomes (taxonomical binning, metagenomics, classification, clustering, annotation)
- Biomedical health analytics and biomedical imaging (electronic health records, precision medicine, image analysis)
- Biomedical literature mining (text mining, ontology, natural language processing)
- Computational epidemiology (infectious diseases, diffusion mechanisms)
- Phenomics and precision agriculture (IoT technologies, feature extraction)
- Visualization of large-scale biomedical data and patient trajectories

Areas of interest within HPC include (but are not limited to):
- Parallel and distributed algorithms (scalable machine learning, parallel graph/sequence analytics, combinatorial pattern matching, optimization, parallel data structures, compression)
- Data-intensive computing techniques (communication-avoiding/synchronization-reducing techniques, locality-preserving techniques, big data streaming techniques)
- Parallel architectures (multicore, manycore, CPU/GPU, FPGA, system-on-chip, hardware accelerators, energy-aware architectures, hardware/software co-design)
- Memory and storage technologies (processing-in-memory, NVRAM, burst buffers, 3D RAM, parallel/distributed I/O)
- Parallel programming models (libraries, domain specific languages, compiler/runtime systems)
- Scientific workflows (data management, data wrangling, automated workflows, productivity)
- Scientific computing (numerical analysis, optimization)
- Empirical evaluations (performance modeling, case-studies)

Program Chair:
Mehmet Koyuturk, Case Western Reserve University

General Chairs:
Alba Cristina M. A. Melo, University of Brasilia
Ananth Kalyanaraman, Washington State University

For Program Committee and program details please refer to the workshop webpage: http://www.hicomb.org/
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