Sequence analysis algorithms for bioinformatics applications

In bioinformatics, it is very important to relate common matched parts between DNA or Protein sequences. Gene Tracer algorithm was proposed to perform this function. Gene Tracer based mainly on local sequence alignment. Local alignment determines the common parts between sequences. Gene Tracer extends this function, so it has three equences as inputs. It determines common parts between one of the sequences and each one of the other two sequences. Then it locates common sub strings in each sequence ( The two ancestors and offspring ). Another important application is determining ancestors sequences of an offspring before it is used in any process. Gene Tracer was extended to scan a large biological database to get the nearest two sequences to offspring sequence. Due to database was large, this application was implemented on Graphical Processing Unit ”GPU” to decrease execution time of algorithm. GPU computes alignment for all sequences in database with query in parallel.But CPU executes alignment for all sequences serially. So GPU gives significant reduction of application’s execution time than CPU. Execution time also was decreased by increasing occupancy of GPo. Occupancy of GPU means keeping GPU’s resources as busy as possible.There are 3 contributions for this research work. i) Gene Tracer algorithm was proposed to relate DNA or Protein sequences. ii) Gene Tracer with scanning database using GPU algorithm was proposed to search for offspring’s ancestors. iii) Effect of GPU’s occupancy on execution time was discussed, where execution time of an application was decreased by mcreasmg occupancy.Keywords: Bioinformatics, Gene Tracer algorithm, GPo.