tailieunhanh - Báo cáo hóa học: " Research Article How to Improve Postgenomic Knowledge Discovery Using Imputation"

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 How to Improve Postgenomic Knowledge Discovery Using Imputation | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2009 Article ID717136 14 pages doi 2009 717136 Research Article How to Improve Postgenomic Knowledge Discovery Using Imputation Muhammad Shoaib B. Sehgal 1 2 Iqbal Gondal 3 Laurence S. Dooley 4 and Ross Coppel2 5 1ARC Centre of Excellence in Bioinformatics Institute for Molecular Bioscience IMB University of Queensland St Lucia QLD 4067 Australia 2 Victorian Bioinformatics Consortium Monash University VIC 3800 Australia 3Gippsland School of Information Technology GSIT Faculty of Information Technology Monash University Churchill VIC 3842 Australia 4 Faculty of Mathematics Computing and Technology The Open University Milton Keynes MK7 6BJ UK 5 Department of Microbiology Monash University VIC 3800 Australia Correspondence should be addressed to Iqbal Gondal Received 28 February 2008 Revised 8 September 2008 Accepted 4 November 2008 Recommended by Erchin Serpedin While microarrays make it feasible to rapidly investigate many complex biological problems their multistep fabrication has the proclivity for error at every stage. The standard tactic has been to either ignore or regard erroneous gene readings as missing values though this assumption can exert a major influence upon postgenomic knowledge discovery methods like gene selection and gene regulatory network GRN reconstruction. This has been the catalyst for a raft of new flexible imputation algorithms including local least square impute and the recent heuristic collateral missing value imputation which exploit the biological transactional behaviour of functionally correlated genes to afford accurate missing value estimation. This paper examines the influence of missing value imputation techniques upon postgenomic knowledge inference methods with results for various algorithms consistently corroborating that instead of ignoring missing values recycling microarray data by flexible .