Introduction


Computing systems are rapidly changing with multicore, GPUs, clusters, volunteer systems, clouds, and grids offering a confusing dazzling array of opportunities. New programming paradigms such as MapReduce and Many Task Computing have joined the traditional repertoire of workflow and parallel computing for the highest performance systems. Meanwhile the Life Sciences are continuing to expand in data generated with continuing improvement in the instruments for high throughput analysis. This “fourth paradigm” (observationally driven science) is joined by complex systems or biocomplexity that can build phenomenological models of biological systems and processes. This workshop juxtaposes these trends seeking those computational methods that will enhance scientific discovery.


The purpose of this the workshop is to provide the opportunity for researchers, scientists, engineers, and students to discuss and share the latest research in parallel and distributed high performance systems applied to Life Science problems. It aims to offer an interactive environment for investigators working on novel “computational thinking” for (Systems) Biology, Bioinformatics, Biocomplexity and Cheminformatics, so that future activities and collaborations will be initiated, as ell as fostering discussions about the utilization of HPDC systems in their respective research initiatives. Selected papers will be published in a special issue of Journal Concurrency and Computation: Practice and Experience. Information about ECMLS2010 workshop can be found here.


     Topics of interests include (but not limited to)


  • Application of Information Theory in life sciences
  • Applications of GPU and Multicore architectures
  • Applications of cloud computing
  • Architectures and data management techniques for the life sciences
  • Bio Statistics and its application in biology
  • Bioinformatics databases
  • Biological Data Mining
  • Biological Data Visualization
  • Biological Databases & Data Integration
  • Biological Informatics and Computing
  • Biomedical Databases & Information Systems
  • Biomedical Imagery
  • Biomedical Intelligence and Data Warehousing
  • Comparison and alignment methods
  • Complex Systems and Biocomplexity
  • Computational Biomodeling
  • Computational Drug Discovery
  • Computational genomics and proteomics
  • Computational Systems Biology
  • Data Deluge in Biology
  • Dimension Reduction
  • Genetic Algorithms
  • Grid Computing and Grid technologies for the life sciences
  • Grid, Cluster and Internet Computing
  • High Performance Bio-Computing
  • Knowledge Discovering techniques and Data Mining
  • Life sciences ontologies
  • MapReduce and its enhancements applied to life sciences
  • Many Task Computing and Life Sciences
  • Multimedia Biomedical Databases and Biomedical Knowledge Discovery
  • Parallel algorithms for biological analysis
  • Parallel architectures for biological applications
  • Parallel Stochastic simulation
  • Parallel visualization algorithms
  • Semantic web for  the life sciences
  • Multiple Sequence Alignment
  • System tools that support large scale high-performance bio-computing
  • Text Mining, Information Extraction, and Language Processing
  • Web-mining of Biological data

  •     List of related workshops