[hpc-announce] CFP: Special issue on High Performance Computing for Biological Data Analysis and Molecular Dynamics

[Liu, Yongchao]

================================ CALL FOR PAPERS ===================================== 
BioMed Research International 
Special issue on High Performance Computing for Biological Data Analysis and Molecular Dynamics 
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http://www.hindawi.com/journals/bmri/si/149743/cfp 
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Propelled by real-world challenging biological problems such as searching large-scale, ever-increasing biological databases, and tackling the flood of next generation sequencing data, computing has become an integral part of the research and development in bioinformatics and computational biology. These biological problems are usually compute-intensive, memory-intensive, or data-intensive and have therefore established strong needs for powerful hardware computing architectures and sophisticated high performance algorithms in order for efficient data management and analysis. 


Moreover, molecular dynamics methods are an established mechanism for determining the equilibrium and transport properties of a classical many-body system. Today, molecular dynamics techniques are being used to simulate larger and more complex biological systems, in areas such as disease, vaccine, and drug research. This places increasing demands on high performance computing (HPC) resources. 


We invite authors to submit original research and review articles that target biological data analysis and molecular dynamics problems. Papers must be related to the design and implementation of high performance algorithms and parallel computing systems for bioinformatics and computational biology. 


Potential topics include, but are not limited to: 
Bioinformatics databases 
Computational genomics and metagenomics 
Gene expression analysis with RNA-Seq and microarrays 
Gene identification and annotation 
Molecular evolution and phylogeny inference 
Molecular dynamics simulation of biomolecules 
Next generation sequencing (NGS) 
Protein structure prediction and modeling 
Big data solutions to biological applications 
Cluster, grid, and cloud computing 
Hardware accelerators such as GPUs, FPGAs, x86/SSE, and Xeon Phis 
Energy-aware high performance biological applications 
High performance algorithms for systems biology 
Parallel algorithms and HPC architectures for biological applications 


BioMed Research International is published using an open access publication model, meaning that all interested readers are able to freely access the journal online at http://www.hindawi.com/journals/bmri/contents/ without the need for a subscription. All published articles will be made available on PubMed Central and indexed in PubMed at the time of publication. The most recent Impact Factor for BioMed Research International is 2.706 according to 2013 Journal Citation Reports released by Thomson Reuters (ISI) in 2014. 


Authors can submit their manuscripts via the Manuscript Tracking System at http://mts.hindawi.com/submit/journals/bmri/computational.biology/hpca and the call-for-papers PDF file can be downloaded from http://downloads.hindawi.com/journals/bmri/si/149743.pdf. 


Manuscript Due Friday, 24 July 2015 
First Round of Reviews Friday, 16 October 2015 
Publication Date Friday, 11 December 2015 


Lead Guest Editor 
Yongchao Liu, University of Mainz, Mainz, Germany 

Guest Editors 
Bertil Schmidt, Johannes Gutenberg University Mainz, Mainz, Germany 
Weiguo Liu, Shandong University, Shandong, China 
Jan Schröder, Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
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