Conferences
1–3 June 2015, Reykjavík, Iceland
BBC 2015 : 8th Workshop on Biomedical and Bioinformatics Challenges for Computer Science - BBC2015
Emerging technologies in genomics, transcriptomics, metagenomics and other life science areas are generating an increasing amount of complex data and information.
In order to tackle the growing complexity associated with emerging and future life science challenges, bioinformatics and computational biology researchers and developers
need to explore, develop and apply novel computational concepts, methods, tools and systems. Many of these new approaches are likely to involve advanced and large-scale
computing techniques, computational approaches, technologies and infrastructures such as:
* High-performance architectures and systems (e.g., multicore, GPU);
* Distributed computing (e.g. grid, cloud, peer-to-peer, Web services, e-infrastructures);
* Computational simulation (mechanistic, stochastic, multi-model);
* Algorithms (theoretical and experimental aspects);
* Applied bioinformatics (analysis pipelines, tools, applications);
* Artificial and computational intelligence (machine learning, agents, evolutionary techniques, bio-inspired methods).
In order to tackle the growing complexity associated with emerging and future life science challenges, bioinformatics and computational biology researchers and developers
need to explore, develop and apply novel computational concepts, methods, tools and systems. Many of these new approaches are likely to involve advanced and large-scale
computing techniques, computational approaches, technologies and infrastructures such as:
* High-performance architectures and systems (e.g., multicore, GPU);
* Distributed computing (e.g. grid, cloud, peer-to-peer, Web services, e-infrastructures);
* Computational simulation (mechanistic, stochastic, multi-model);
* Algorithms (theoretical and experimental aspects);
* Applied bioinformatics (analysis pipelines, tools, applications);
* Artificial and computational intelligence (machine learning, agents, evolutionary techniques, bio-inspired methods).
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