CAMDA - What is CAMDA?

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 actually can provide new medical and biological insights.

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 which focuses on big complex data sets, often featuring heterogeneous data sources and types. Academic and industrial researchers worldwide alike are invited to take the CAMDA challenge. Accepted contributions are presented in short talks (30 mins), and the results of analyses are discussed and compared at the CAMDA conference. Both contestants and other interested researchers are welcome at the meeting. Posters can provide an additional opportunity of presenting and discussing work. All individuals and groups from both academic and commercial entities are invited to join the award competition.

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 (ref. 1, 2) and was featured in an editorial in Nature Methods in 2008 (ref. 3). Recently called the 'Olympics for Genomics', this allusion indicates the ambitious and wide-ranging nature of the contest. The meeting has regularly been supported by high-profile organizations like FDA, and the NIST.

As in past years, contest presentations are complemented by high profile keynotes. Recent keynote speakers include Benjamin Blencowe (Toronto), Sandrine Dudoit (Berkeley), Mark Gerstein (Yale), Jelle Goeman (Leiden Univ. Medical Centre), Martin Morgan (Hutchinson Cancer Research Center), Wei Pan (Minnesota), John Quackenbush (Dana Farber Cancer Institute, Harvard Medical School), Eran Segal (Weizmann Institute), Terry Speed (WEHI), John Storey (Princeton), Weida Tong (NCTR/FDA), Olga Troyanskaya (Princeton), Ernst Wit (Groningen), Atul Butte (Stanford), and Nikolaus Rajewsky (Max-Delbrück-Center).

Come join us this year, we look forward to your participation!


There are two mailing lists associated with this conference, a low-volume announcements mailing list, and an open forum for participants' free discussions relating to the contest data sets.


References:

  1. Johnson, K.F. and Lin, S.M. (2001). Call to work together on microarray data analysis. Nature 411, 885.
  2. Tilstone, C. (2003). Vital Statistics. Nature 424, 610 (link to journal)
  3. Editorial feature (2008). Going for algorithm gold, Nature Methods 5, 659. (link to journal, link to article)

CAMDA publications

This section contains a compendium of links, abstracts, papers, slides, programs, and tools that supplements the papers found in the proceedings.

Links to earlier CAMDA conferences