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TCBB-ACCBIO 2014 : IEEE/ACM Transactions on Computational Biology and Bioinformatics. Special Section on: ADVANCED PARALLEL COMPUTING SYSTEMS TO ACCELERATE BIOINFORMATICS

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Link: http://arco.unex.es/tcbb
 
When N/A
Where N/A
Submission Deadline Jun 1, 2014
Notification Due Oct 1, 2014
Final Version Due Dec 1, 2014
Categories    bioinformatics   FPGA   gpu   parallel computing
 

Call For Papers

Special Section on: ADVANCED PARALLEL COMPUTING SYSTEMS TO ACCELERATE BIOINFORMATICS
IEEE/ACM Transactions on Computational Biology and Bioinformatics

IEEE Computer Society, Association for Computing Machinery, IEEE Computational Intelligence Society, and the IEEE Engineering in Medicine and Biology Society.
ISSN: 1545-5963.
Editor-in-Chief: Ying Xu (Univ. of Georgia, USA). Associate Editor-in-Chief: Dong Xu (Univ. of Missouri, USA).
Impact factor (2012): 1.616 (Q1, MATHEMATICS, INTERDISCIPLINARY APPLICATIONS).

Aims and Scope:
==============
Emerging hardware-based computing systems characterized by exploiting from fine to coarse grain parallelism are being applied as a main resource to accelerate many algorithms and efficiently manage loads of data. Multi-CPU, GPU and FPGA-accelerated computer systems, data center supercomputers and cloud computing are nowadays an efficient alternative to usual computer systems whose resources are not always able to meet the demand of fast execution of complex algorithms or massive data processing in biological and biochemical systems. In this sense, there are many well-known and novel problems in Bioinformatics that involve intensive computation to supply the solution as soon as possible, even in real time. Faster execution time can either be achieved by designing special-purpose processors exploiting the intrinsic parallelism that hardware provides, using low power consumption or by applying high-performance computing systems that can manage and process big data. Any of these computing systems may use different configurations, architectures and technologies according to the specific problem to be tackled, combining different parallelism levels. Therefore, the usage and design of advanced parallel computing systems are a challenge that opens new possibilities to accelerate Bioinformatics problems, taking into account the problem features, the algorithms that can solve it and the constraints of the technology on which it is executed. Pursuing these possibilities, there are many trends and open issues that deserve to be investigated. In this special section, we seek original, high-quality articles, clearly focused on theoretical or practical aspects of the design, implementation and efficient application of hardware architectures to accelerate Bioinformatics problems, including but not limited to the topics shown below.

Topics of Interest:
==================
* Hardware accelerators in Bioinformatics.
* System, processor, multiprocessor and network on chip.
* Architectures based on graphical processing units.
* Reconfigurable hardware technology: FPGAs, embedded microprocessors, and system-on-chip.
* High-performance computing, cluster and supercomputers.
* Grid and cloud computing.
* Low-power hardware designs.
* Application cases, user studies and experiences.

Papers must be related to the design of advanced parallel computing systems to accelerate Bioinformatics. The editors maintain the right to reject papers they deem to be out of scope of this special section. Only original unpublished contributions will be considered for the section.

Important Dates:
===============
CFP launch: January 1st, 2014.
Submission deadline: June 1st, 2014.
Notification: October 1st, 2014.
Final Papers: December 1st, 2014.

Guest Editors:
=============
Dr. Juan A. Gomez-Pulido
Dept. of Computers and Communications
University of Extremadura, Spain
http://arco.unex.es/jangomez
E-mail: jangomez@unex.es

Dr. Wu Feng
Synergy Laboratory
Virginia Tech, USA
http://www.cs.vt.edu/~feng
E-mail: feng@cs.vt.edu

Dr. Bertil Schmidt
Institut für Informatik
University of Mainz, Germany
http://www.informatik.uni-mainz.de/groups/parallel-and-distributed-architectures/people-parallel/bertil.schmidt
E-mail: bertil.schmidt@uni-mainz.de

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