BigLS 2014 - ACM International Workshop on Big Data in Life Sciences

The ever-growing volume and diversity of biological and biomedical data collections continues to pose new challenges and increasing demands on computing and data management. The inherent complexity of this Big Data forces us to rethink how we collect, store, combine and analyze it. BigLS, pronounced "Beagles", is a workshop dedicated to the broad theme of Big Data in life sciences. The goal of the workshop is to bring together leading researchers and practitioners working on a diverse range of Big Data problems relating to biology and medicine, and engage them in a discussion about current Big Data problems, the state of computational tools and analytics, the challenges and the future trends within life sciences. In this context, the workshop focus is on, yet is not limited to, the following broad themes:
Scalable algorithms and techniques for Big Data analytics in molecular biology
Statistical and integrative approaches to Big Data biology and informatics
High performance computing methods and software for Big Data biology
Scientific workflows and platforms for Big Data in life sciences
Software and hardware solutions for managing Big Data in biomedical informatics
In addition to regular papers catering to the above spectrum of topics, we also invite "position papers" to highlight some of the grand challenge scientific problems from a biological standpoint, existing or emerging, that require Big Data analytics, along with related challenges and advances. The workshop will feature contributed papers as well as invited talks from reputed researchers in the field.
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Submission Guidelines
Submitted manuscripts should not exceed 10 pages in the ACM template on 8.5 x 11 inch paper. All submissions will be evaluated based on their originality, technical soundness, significance, presentation, and interest to the workshop attendees. All accepted papers of registered authors will be included in the ACM BCB proceedings published by the ACM Digital Library. Details for electronic submission can be found on the ACM BCB conference web portal.