Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article MicroRNA Target Detection and Analysis for Genes Related to Breast Cancer Using MDLcompress | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2007 Article ID 43670 16 pages doi 2007 43670 Research Article MicroRNA Target Detection and Analysis for Genes Related to Breast Cancer Using MDLcompress Scott C. Evans 1 Antonis Kourtidis 2 T. Stephen Markham 1 Jonathan Miller 3 Douglas S. Conklin 2 and Andrew S. Torres1 1 GE Global Research One Research Circle Niskayuna NY 12309 USA 2 Gen NY Sis Center for Excellence in Cancer Genomics University at Albany State University of New York One Discovery Drive Rensselaer NY 12144 USA 3 Human Genome Sequencing Center Baylor College of Medicine One Baylor Plaza Houston TX 77030 USA Received 1 March 2007 Revised 12 June 2007 Accepted 23 June 2007 Recommended by Peter Grunwald We describe initial results of miRNA sequence analysis with the optimal symbol compression ratio OSCR algorithm and recast this grammar inference algorithm as an improved minimum description length MDL learning tool MDLcompress. We apply this tool to explore the relationship between miRNAs single nucleotide polymorphisms SNPs and breast cancer. Our new algorithm outperforms other grammar-based coding methods such as DNA Sequitur while retaining a two-part code that highlights biologically significant phrases. The deep recursion of MDLcompress together with its explicit two-part coding enables it to identify biologically meaningful sequence without needlessly restrictive priors. The ability to quantify cost in bits for phrases in the MDL model allows prediction of regions where SNPs may have the most impact on biological activity. MDLcompress improves on our previous algorithm in execution time through an innovative data structure and in specificity of motif detection compression through improved heuristics. An MDLcompress analysis of 144 over expressed genes from the breast cancer cell line BT474 has identified novel motifs including potential microRNA miRNA binding sites that are candidates for .
