Introduction
Challenges
Call for Papers
Important Dates
Paper submission
Online Registration
Invited Speakers
Workshop Program
Workshop Date and Location
Hosts
Organising Committee
Program Committee
contact
Links
 
 
Introduction

**** Proceedings are available online at http://www.springeronline.com/978-3-540-69841-8 ****

International Workshop Distributed, High-Performance and Grid Computing in Computational Biology - GCCB 2006

Biology and biotechnology encompass research and development in areas such as biophysics, biochemistry, biology, neuroscience, biomedicine, and environmental sciences. A common theme among biology and biotechnology disciplines is the desire to understand the stimuli-response mechanisms of biological entities, systems and processes at different levels of organization (molecular, sub-cellular, cellular, inter-cellular, tissue, organism, population, environment, ecosystem). As natural phenomena are being probed and mapped in ever-greater detail, life scientists and biotechnologists are generating an increasingly growing amount of data and information in electronic format.

To organize, share, integrate and analyze these data and information, and to use them in order to model and simulate the underlying biological systems and processes has become an essential part of modern life science research and development. The conceptual and technical challenges involved in these tasks are considerable, so much that an entire discipline, computational biology and bioinformatics, has emerged to address these challenges. Increasingly, the tasks, applications and computer systems involved are characterized by large and complex-structured data and by considerable requirements for compute power and storage (primary and secondary memory). In addition, since many of the relevant communities, systems, instruments and (computing) resources are geographically widely distributed, it has become necessary to seamlessly share such computing resources through computer networks.

In order to tackle the arising computational challenges, computational biologists and bioinformaticians need to leverage, develop and deploy distributed, high-performance and grid computing technologies. While certain distributed, high-performance and grid computing technologies and methodologies can be used and applied in a context-independent way across many disciplines, the unique features and characteristics encountered in biology and biotechnology poses additional constraints and challenges.

Topics

The workshop is aimed at computational biologists, bioinformaticians, computer scientists and life scientists interested in distributed, high-performance and grid computing technology in the context of computational biology and bioinformatics. The workshop will discuss innovative work in progress and important new directions. Contributions of interest will address topics related to the development, deployment, application and evaluation of distributed, high-performance and grid computing technologies in the context of the following computational biology and bioinformatics areas:

-  Analysis, modeling and simulation of processes like pathways, biological networks, pharmacodynamics, pharmacokinetics, protein-protein interaction, transcription initiation, and whole systems;
-  Computational approaches to biological entities and processes, e.g. to functional genomics, proteomics, metabolomics, epidemiology, epigenetics, biodiversity, ecosystems, neuroscience;
-  Linkage and sequence analysis;
-  Molecule design;
-  Prediction of protein-, DNA-, and RNA-structure, toxicity, AMDE (absorption, distribution, metabolism and excretion), etc.;
-  Protein folding and unfolding;
-  Information retrieval and knowledge discovery including data and text mining;
-  Management and integration of biological data and information;
-  Distributed ontologies and semantic Web/grid approaches;
-  Visualization and image management and processing of biological data;
-  Grid tools for computational biology and bioinformatics;
-  Distributed systems and databases;
-  Development of diagnostic, prognostic and therapeutic (drugs) technologies;
-  Large-scale (storage, computation, components/systems) studies in computational biology and bioinformatics.