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第三十届中国控制会议

作者： GAO Qinghui~1,JIA Yingmin~(1,2),CHENG Changfang~3,YU Fashan~4 1.The Seventh Research Division and the Department of Systems and Control,Beihang University(BUAA),Beijing 100191,P.R.China 2.Key Laboratory of Mathematics,Informatics and Behavioral Semantics(LMIB),Ministry of Education,SMSS,Beihang University (BUAA),Beijing 100191,P.R.China 3.The Seventh Research Division and the Department of Systems and Control,Beihang University(BUAA),Beijing 100191,P.R.China 4.School of Electrical Engineering and Automation,Henan Polytechnic University,Jiaozuo 454000,Henan,P.R.China

＜正＞In this paper,we present a model to elaborate the sources of randomness in multiple tiling array *** also propose a new probe score system which integrate the intensity information of a probe and its *** new score system is obtained by using slide window and median polish *** strategies firstly unify probe affect across probes and the array effect across arrays based on the region-specific fixed values interpreting the transcription levels of regions in probes,then unite these unified information into the region-specific fixed *** this united information become a new standard to evaluate that probes are or aren’t in transcriptional *** to median method,our method is a way that integrate the information from multiple arrays in the analysis stage rather than the results stage.A classical hidden Markov model（HMM） is used to model the distribution of tilling array probe scores in transcribed and non-transcribed regions and then to predict the transcribed *** priority of the proposed score system is illustrated based on Affymetrix’s RNA tiling array data.

关键词： tiling arrays Slide window Median polish Probe effect Array effect

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TAAPP: tiling Array Analysis Pipeline for Prokaryotes

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Genomics, Proteomics & Bioinformatics 2011年第1期9卷 56-62页

作者： Ranjit Kumar Shane C. Burgess Mark L. Lawrence Bindu Nanduri College of Veterinary Medicine Mississippi State University Mississippi 39762 USA Institute for Genomics Biocomputing and Biotechnology Mississippi State University Mississippi 39762 USA Mississippi Agriculture and Forestry Experiment Station Mississippi State University Mississippi 39762 USA

High-density tiling arrays provide closer view of transcription than regular microarrays and can also be used for annotating functional elements in genomes. The identified transcripts usually have a complex overlapping architecture when compared to the existing genome annotation. Therefore, there is a need for customized tiling array data analysis tools. Since most of the initial tiling arrays were conducted in eukaryotes, data analysis methods are well suited for eukaryofic genomes. For using whole-genome tiling arrays to identify previously unknown transcriptional elements like small RNA and antisense RNA in prokaryotes, existing data analysis tools need to be tailored for prokaryotic genome architecture. Furthermore, automation of such custom data analysis workflow is necessary for biologists to apply this powerful platform for knowledge discovery. Here we describe TAAPP, a web-based package that consists of two modules for prokaryotic tiling array data analysis. The transcript generation module works on normalized data to generate transcriptionally active regions （TARs）. The feature extraction and annotation module then maps TARs to existing genome annotation. This module further categorizes the transcription profile into potential novel non-coding RNA, antisense RNA, gene expression and operon structures. The implemented workflow is microarray platform independent and is presented as a web-based service. The web interface is freely available for acedemic use at http：//***/TAAPP-HTML/.

关键词： transcriptomics small RNA operon prokaryotes tiling arrays

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