Abstract of Talk
Linear-time matching of Position Weight Matrices
Abstract: Position Weight Matrices (PWMs) are a popular way of representing variable motifs in genomic sequences. Literally every currently used database containing protein binding and DNA sequence signal information stores this information in the form of PWMs, either exclusively or in combination with other forms of representation. Consequently, PWM matching became the principal mechanism for mining the information contained in these databases. Whereas not inefficient on shorter sequences, the current implementations of PWM matching are too expensive for whole-genome searches, which is now a performance bottleneck in today's genomics.
After an introduction to PWMs and their applications, in this talk we shall present an algorithm we have developed for their efficient matching in long target sequences. After the initial pre-processing of the matrix our method performs in time linear to the size of the genomic segment, which makes it suitable for application on entire chromosomes, and even complete genomes.
Biography: Nikola Stojanovic is an Assistant Professor at the Computer Science and Engineering department at UTA. He has received his BS degree in Mathematics from the University of Belgrade, Yugoslavia, and a PhD in Computer Science and Engineering from Pennsylvania State University.