Many problems in bioinformatics and statistical analysis use
what are considered “greedy” algorithms to fit parameters to data – that is,
they settle on a nearby collection of
parameters as the solution and potentially miss a global best solution. This
problem is well-known in the computer science community for toy problems like bin
packing or the knapsack
problem. In human genetics,
related problems are partitioning complex pedigrees or selecting maximally
unrelated individuals from a dataset, and can also appear when maximizing
likelihood equations.
EvoBIO focuses on using biologically-inspired algorithms
(like genetic algorithms) to improve performance for many bioinformatics
tasks. For example, Stephen and I have
both applied these methods for analysis of genetic data using neural networks, and for forward-time
genetic data simulation (additional details here).
EvoBIO is very pleased to be sponsored by BMC Biodata
Mining, a natural partner for this conference. I recently wrote a blog post for BioMed Central about EvoBIO as well. Thanks to their sponsorship, the winner of the EvoBIO best paper award will receive free publication in Biodata Mining, and runners-up will receive 25% discount off the article processing charge.
So, if you are in the mood for a new conference and would like to see and influence some of these creative approaches to data analysis, consider attending EvoSTAR -- We'd love to see you there!
So, if you are in the mood for a new conference and would like to see and influence some of these creative approaches to data analysis, consider attending EvoSTAR -- We'd love to see you there!
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