David Kreil (TBC)

CAMDA, an open-ended data analysis challenge of complex data sets-

The increasing relevance of Big Data forms one of the grand challenges in modern life sciences. Analysing large data sets is consequently emerging to be one of the scientific key techniques in the post genomic era. Recently, the growing need for the analysis of massive data has further accelerated by the advent and fast development of high-throughput next-generation sequencing technologies and the necessarily increasing cohort size of biomedical studies. Still the data analysis bottleneck limits the rate with which technological advances in genome-scale experimental platforms can actually provide new medical and biological insights. The Critical Assessment of Massive Data Analysis (CAMDA) has a track record as a well-recognized annual conference going back to the year 2000. It soon received considerable attention from high impact journals like Nature ( 411:885, 2001; 424:610, 2003) and was featured in an editorial in Nature Methods in 2008 (Nat. Meth. 5, 659). CAMDA focuses on the analysis of massive data in the life sciences. It introduces and evaluates new approaches and solutions to the Big Data challenge. The conference presents new techniques in the field of bioinformatics, data analysis, and statistics for the handling and processing of large data sets, the combination of multiple data sources, and effective computational inference. An essential part of CAMDA is its open-ended data analysis challenge of complex data sets, often featuring novel technological platforms, exceptionally large cohorts, and heterogeneous data sources and types.