Life 2017 - Workshop on Clusters, Clouds and Grids for Life Sciences (CCGrid ? Life 2017)

Today, biomedicine and bioinformatics rely heavily on large scale computational resources, as they typically employ data- and compute- intensive methods. Omics, biomedical imaging and computational models quickly reach data volumes of terabytes and petabytes, data analysis may need teraflops or petaflops of computing power. New challenges arise from complex analysis of distributed heterogeneous data, for example in translational medicine.
Distributed IT-systems, such as Grids, Clouds and recently Big Data environments, are used for to speed-up large experiments and development time for new algorithms. Distributed systems also allow for better availability of new computational methods for supporting large-scale multi-centric collaborations. However, specific challenges in the employment of such systems for biomedical applications, such as security, reliability and user-friendliness, often impede wide-range adoption of prototype solutions.
This workshop aims at bringing together developers of bioinformatics and biomedical applications and researchers in the field of distributed IT systems. The goals of the workshop are to exchange and discuss existing solutions and latest developments in both fields, in particular for identified gaps and roadblocks. The workshop further intends to collaboratively explore new approaches to successfully apply distributed IT-systems in translational research, clinical intervention, and decision-making.
Topics of Interest
Contributions are expected but not restricted to the following topics:
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
Service and/or algorithm design and implementation applicable to medical and bioinformatic applications
Improved energy consumption of bioinformatic applications using clouds
Modeling and simulation of complex biological processes
Genomics and Molecular Structure evolution
Molecular Dynamics
Clouds for big data manipulation in bioinformatics and medicine
Ontologies and biomedical text mining
Biological data mining and visualization
Error handling and fault tolerance
Distributed and heterogeneous bioinformatic and medical data management
Big Medical and Bioinformatic Data applications and solutions
Data privacy, security and access control
Development environments 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
Success stories and show stoppers