Well, I'm sorry for this confusion, you're naturally right. The problem is that any bioinformatics textbook (e.g., basic, but one of the very best is http://www.bioalgorithms.info/) introduces these algorithms, so as time goes by, my perspective becomes somewhat limited ;-) The best way would really be to extend appropriate libraries (string & math algorithms), and create that bionf library with really bioinf-specific content. Thank you all for your responses in this matter, this is the help I was hoping for. Robert -----Original Message----- From: boost-bounces@lists.boost.org [mailto:boost-bounces@lists.boost.org] On Behalf Of Beman Dawes Sent: Tuesday, December 05, 2006 19:52 To: boost@lists.boost.org Subject: Re: [boost] Bioinformatics algorithms in boost? Robert Goldwein wrote:
Hello all,
for my thesis, I'll be developing a self-contained framework for algorithms used in bioinformatics. This will include algorithms such as Hamming distance, Levenshtein distance or Longest common subsequence algorithms, gene prediction algorithms, 2D and 3D scoring matrices, alignment problems, etc.
Would be there - in some near future - any interest in such library?
Yes, as others have also indicated. The real question is why you think of these as "bioinformatics algorithms" rather than just plain "algorithms"? Have they been restricted in some way that prevents them from being used for general purposes? I've used Levenshtein distance variants a great deal in geographic name processing applications. For real-world applications, there has to be a way to recognize additional distances (i.e. costs) in various cases. I expect the same refinements apply to many problem domains. Wouldn't the same apply to the bioinformatics domain? --Beman _______________________________________________ Unsubscribe & other changes: http://lists.boost.org/mailman/listinfo.cgi/boost