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RECOMB
2002
Springer
14 years 4 months ago
From promoter sequence to expression: a probabilistic framework
We present a probabilistic framework that models the process by which transcriptional binding explains the mRNA expression of different genes. Our joint probabilistic model unifie...
Eran Segal, Yoseph Barash, Itamar Simon, Nir Fried...
BMCBI
2006
203views more  BMCBI 2006»
13 years 4 months ago
Genome-wide prediction of transcriptional regulatory elements of human promoters using gene expression and promoter analysis dat
Background: A complete understanding of the regulatory mechanisms of gene expression is the next important issue of genomics. Many bioinformaticians have developed methods and alg...
Seon-Young Kim, YongSung Kim
ISMB
2000
13 years 5 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
ISMB
1997
13 years 5 months ago
Functional Prediction of B. subtilis Genes from Their Regulatory Sequences
In bacterial cells, gene expression is regulated by multiple sigma factors, each of which has its promoter specificity, according to their conditions. Thus, if we can discriminate...
Tetsushi Yada, Yasushi Totoki, Takahiro Ishii, Ken...
ISB
2002
140views more  ISB 2002»
13 years 4 months ago
Computer system "Gene Discovery" for promoter structure analysis
Data Mining and Knowledge Discovery techniques proved to be efficient tools for variety of complex tasks in biology including DNA research. This paper presents implementation of th...
Eugenii E. Vityaev, Yuri L. Orlov, Oleg V. Vishnev...