Finding motifs in biological sequences is one of the most intriguing problems for string algorithms designers due to, on the one hand, the numerous applications of this problem in...
Our group has previously used machine learning techniques to develop computational systems to automatically analyse fluorescence microscope images and classify the location of the ...
Abstract. We apply the concept of subset seeds proposed in [1] to similarity search in protein sequences. The main question studied is the design of efficient seed alphabets to con...
Mikhail A. Roytberg, Anna Gambin, Laurent No&eacut...
We study the problem of structured motif search in DNA sequences. This is a fundamental task in bioinformatics which contributes to better understanding of genome characteristics a...
The Edinburgh Mouse Atlas aims to capture in-situ gene expression patterns in a common spatial framework. In this study, we construct a grammar to define spatial regions by combina...
Abstract. This paper presents a SVM-based local search (SVM-LS) approach to the problem of gene selection and classification of microarray data. The proposed approach is highlighte...