Prediction of transcription and genomic sequences

被引:1
|
作者
Martin, D [1 ]
Ghattas, B [1 ]
Thieffry, D [1 ]
机构
[1] Univ Mediterranee, Lab Genet & Physiol Dev, LGPD, IBDM,CNRS,Case 907, F-13288 Marseille 9, France
来源
M S-MEDECINE SCIENCES | 2004年 / 20卷 / 11期
关键词
D O I
10.1051/medsci/200420111036
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Technological developments have enhanced DNA sequencing at genomic scale. On the basis of the resulting sequences, computational biologists now attempt to localise the most important functional regions, starting with genes, but also importantly the regulatory motifs and conditions controlling their expression. In a recent paper published in Cell, M.A. Beer and S. Tavazoie report the results obtained by combining statistical classifications (clustering) of transcriptome data (DNA chips), software for the discovery of cis-regulatory patterns, together with a probabilistic learning method to infer regulatory rules tentatively accounting for the observed transcriptional profiles.
引用
收藏
页码:1036 / 1040
页数:5
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