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CAMDA - What is CAMDA?

Currently, the Big Data explosion is the grand challenge in life sciences. Analysing large data sets is emerging to one of the scientific key techniques in the post genomic era. Still the data analysis bottleneck prevents new biotechnologies from providing new medical and biological insights in a larger scale. This trend towards the need for analysing massive data sets is further accelerated by novel high throughput sequencing technologies and the increasing size of biomedical studies. CAMDA focuses on the analysis of the massive data sets in life sciences. It provides new approaches and solutions to the big data problem, presents new techniques in the field of bioinformatics, data analysis, and statistics for handling and processing large data sets.

CAMDA is run as an open-ended data analysis challenge and focuses on big heterogeneous data sets – rather than being a closed-form contest, focusing on a particular data type, or covering implementation / hardware issues. Academic and industrial researchers worldwide 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 meeting going back to the year 2000. It obtained considerable attention by high impact journals like Nature already in 2001 and 2003 (1,2). It was featured in an editorial in Nature Methods in 2008 (3), and was recently called the 'Olympics for Genomics', indicating the ambitious and wide-ranging nature of the contest. The contest has been supported by organization including the FDA, the NIST, and EMERALD.

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
  3. Editorial feature (2008). Going for algorithm gold, Nature Methods 5, 569. (link to journal)

what_is_camda.1350661822.txt.gz · Last modified: 2012/10/19 17:50 by okko
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