Special Issue on Clusters, Cloud and Grid on Life Sciences 

Future Generation Computer Systems

In the last 20 years, computational methods have become an important part of developing emerging technologies for the field of bioinformatics and biomedicine. Research areas such as biomodelling, molecular dynamics, genomics, neuroscience, cancer models, evolutionary biology, medical biology, biochemistry, biophysics, biotechnology, cell biology, nanobiotechnology, biological engineering, pharmacology, genetics therapy, or automatic diagnosis, rely heavily on large scale computational resources as they need to manage Tbytes or Pbytes of data with large-scale structural and functional relationships, TFlops or PFlops of computing power for simulating highly complex models, or many-task processes and workflows for processing and analyzing data. 

This new situation demands appropriate IT-infrastructures, where b ioinformatic and medical data can be processed within an acceptable timespan – reaching from minutes in health-care applications to days in large-scale research projects. Large-scale distributed IT-systems such as Grids, Clouds and Big-Data-Environments are promising to address research, clinical and medical research community requirements. They allow for significant reduction of computational time for running large experiments, for speeding-up the development time for new algorithms, for increasing the availability of new methods for the research community, and for supporting large-scale multi-centric collaborations. However, specific challenges in the employment of such systems for bioinformatic applications such as security, reliability and user-friendliness, often impede straightforward adoption of existing solutions from other application domains. 

Areas of interest for this special issue include, but are not limited to:

• Detailed application use-cases highlighting achievements and roadblocks
• Exploitation of distributed IT resources for Life Sciences, HealthCare and research applications, for example medical imaging, disease modeling, bioinformatics, Public health informatics, drug discovery, clinical trials
• Improved energy consumption of bioinformatic applications
• Modeling and simulation of complex biological processes
• Ontologies and biomedical text mining
• Biological data mining and visualization
• Error handling and fault tolerance
• Distributed and heterogeneous bioinformatic and medical data management
• Data privacy, security and access control
• Development envir onments for distributed bioinformatic applications
• Programming paradigms and tools for bioinformatic applications
• Scientific gateways and user environments targeting distributed medical and bioinformatic applications
• Dedicated distributed infrastructures and HPC systems
• Interoperability for exchanging data, algorithms and analysis pipelines

Submission Guidelines

Original, high quality contributions that are not yet published or that are not currently under review by other journals or peer-reviewed conferences are sought. Exceptions are extended high-quality papers presented at CCGrid-Life 2015. These must have at least 30% difference from the original conference papers. Papers will be peer reviewed by independent reviewers and selected based on originality, scientific quality and relevance to this Special Issue. The journal editors will make final decisions on the acceptance of the papers.

Authors should prepare their manuscript according to the Guide for Authors available from the online submission page of the Future Generation Computer Systems at www.ees.elsevier.com/fgcs/. Authors should select “SI: CCGrid-Life” when they reach the “Article Type” step in the submission process.

Important Dates

Paper submission due: July 31, 2015
First-round acceptance notification: October 31, 2015
Revision submission: December 14, 2015
Notification of final decision: January 31, 2016 
Submission of final paper: March 31, 2016
Publication date: June 30, 2016 (Planned)

Guest Editors

Sandra Gesing, University of Notre Dame, USA
sandra.gesing@nd.edu

Johan Montagnat, CNRS, France
johan.montagnat@cnrs. fr

Jesus Carretero, Universidad Carlos III de Madrid, Spain
jesus.carretero@uc3m.es

Javier Garcia Blas, Universidad Carlos III de Madrid, Spain
fjblas@inf.uc3m.es