BIOSG 2017 : IEEE BIBM Workshop on High Throughput Computing in Bioinformatics and Biomedicine using Open Science Grid
Call For Papers
IEEE BIBM Workshop on High Throughput Computing in Bioinformatics and Biomedicine Using Open Science Grid (OSG), http://sbbi-panda.unl.edu/bibm2017, is one-day workshop held on Monday, November 13th, in Kansas City, Missouri, in conjunction with the IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2017. IEEE BIBM 2017 (http://muii.missouri.edu/bibm2017) is a premier research conference in bioinformatics and biomedicine that brings together academic and industrial scientists from all over the world to exchange cutting edge research ideas in bioinformatics and health informatics.
Call For Papers
Recent advances in next-generation sequencing technologies has led to a proliferation of genomic data in biomedical research. Analyzing and understanding this vast amount of genomic data is a time consuming and computationally intensive process, which can be even more challenging with limited computing resources. While some bioinformatics and biomedical applications are non-modular and non-trivial to partition, others are granular and can be split into many smaller independent tasks. These smaller tasks can be distributed to multiple computing resources in parallel. High-throughput computing (HTC) significantly reduces the computation time of workflows composed of independent tasks by distributing the tasks to numerous resources. The Open Science Grid (OSG) provides a highly-efficient and user-friendly HTC service to accomplish this.
The goal of this workshop is to bring together scientists in the fields of bioinformatics, biomedical sciences and high-throughput computing to discuss the challenges of omics applications and the benefits of using distributed computing for divisible workloads. With this workshop, we aim to encourage and motivate researchers to develop efficient scientific workflows, analysis pipelines and algorithms that can utilize OSG. This workshop will feature contributed papers as well as invited talks from recognized researchers in the field.
We welcome both theoretical and application researchers to submit papers on unpublished and original data-centric work in bioinformatics and biomedicine, with particular emphasis on, but not limited to:
- High-throughput computing workflow development in bioinformatics and biomedicine
- High-throughput computing scientific workflows for next-generation sequencing data analysis
- Distributed processing of bio-signals
- High-throughput computing workflow development for data sharing and analytic collaboration
- Large-scale biological and biomedical data analysis using distributed computing
- High-throughput computing workflows for data mining, visualization, and interpretation
- Drug design and modeling using distributed computing
- High-throughput computing workflow development for visualization and analysis of data in neuroscience
- Modeling and simulation of complex biological processes in distributed environments
- High-throughput computing workflows for biomedical image processing
- Protein docking and modeling using distributed environments
- Workshop papers submission due: October 06, 2017
- Author notification: October 13, 2017
- Camera-ready of accepted papers: October 25, 2017
- Workshop: November 13, 2017
- Please submit a full-length paper (up to 8 pages 2-column format) through the workshop online submission system,
https://wi-lab.com/cyberchair/2017/bibm17/scripts/ws_submit.php. Your paper should be formatted according to the IEEE Computer Society Proceedings Manuscript Formatting Guideline, http://www.ieee.org/conferences_events/conferences/publishing/templates.html. Electronic submissions (in PDF or Postscript format) are required. All papers will be reviewed, and the accepted papers will be included in the Workshop Proceedings published by the IEEE Computer Society Press. Additionally, selected papers will have their extended versions published in special issues in highly respected journals.
- Juan Cui, University of Nebraska - Lincoln, USA
- David Swanson, University of Nebraska - Lincoln, USA