[Comp-neuro] FLAIRS, Daytona Beach, May 19, Special Tracks on Data Mining or Bioinformatics

d bisant bisant at umbc.edu
Wed Aug 5 01:35:48 CEST 2009


Here are calls for 2 tracks which may be of interest to list members.

FLAIRS 2010, Daytona Beach, FL,  May 19-21, 2010
Conference URL: http://www.flairs-23.info/

Submission Due Date:  November 23, 2009

Call For Papers:  FLAIRS-2010 Special Track on Bioinformatics
and Computational Biology

Track URL:  http://userpages.umbc.edu/~bisant/gl/CFP2010BIO.htm

Papers are being solicited for a special track on Bioinformatics and
Computational Biology at the 23rd International FLAIRS Conference
(FLAIRS-2010). The special track will be devoted to bioinformatics
and computational biology with the aim of presenting new and important
contributions in this area. The areas include, but are not limited to,
the following: applications such as genomics, bioinformatics, protein
modeling, sequence analysis, population modeling, computational biology,
biological database mining; modeling algorithms such as hidden Markov,
neural networks, statistical methods, or probabilistic methods; case
studies in areas of application, or over different algorithms and
approaches; feature presentation , extraction, and selection such as
molecular fingerprinting; post-processing techniques such as visualization,
summarization, or trending;  or other biological research which is related
to artificial intelligence.

Questions regarding the track should be addressed to: David Bisant at
bisant at umbc.edu or Taghi Khoshgoftaar   taghi at cse.fau.edu


Call For Papers:  FLAIRS-2010 Special Track on Data Mining

Track URL:  http://userpages.umbc.edu/~bisant/gl/CFP2010DM.htm 

Papers are being solicited for a special track on Data Mining at the
23rd International FLAIRS Conference (FLAIRS-2010). The special track
will be devoted to data mining with the aim of presenting new and
important contributions in this area. The areas include, but are not
limited to, the following: applications such as Intelligence analysis,
medical and health applications, text, video, and multi-media mining,
E-commerce and web data, financial data analysis, intrusion detection,
remote sensing, earth sciences, and astronomy; modeling algorithms such
as hidden Markov, decision trees, neural networks, statistical methods,
or probabilistic methods; case studies in areas of application, or over
different algorithms and approaches; feature extraction and selection;
post-processing techniques such as visualization, summarization, or
trending; preprocessing and data reduction; data engineering or
warehousing;  or other data mining research which is related to
artificial intelligence.

Questions regarding the track should be addressed to: David Bisant at
bisant at umbc.edu or Bill Eberle at weberle at tntech.edu.






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