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Results: We present a probabilistic approach to predicting operons using Bayesian networks. Our approach exploits diverse evidence sources such as sequence and ...
Nov 11, 2002 · This evidence source is appealing because it requires no additional knowledge beyond gene coordinates and sequence and thus can be used to ...
Results: We present a probabilisitic approach to predicting operons using Bayesian networks. Our approach exploits diverse evidence sources such as sequence and ...
Oct 22, 2024 · In order to understand transcription regulation in a given prokaryotic genome, it is critical to identify operons, the fundamental units of ...
Abstract. Motivation: In order to understand transcription reg- ulation in a given prokaryotic genome, it is critical to identify operons, the fundamental ...
It predicts operons with a high degree of confidence based on the notion that pairs of genes that occur adjacent to one another in multiple organisms are likely ...
TL;DR: This work presents a probabilistic approach to predicting operons using Bayesian networks and evaluates this approach on the Escherichia coli K-12 ...
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1 Introduction. An operon is a set of genes in prokaryotes, which are transcribed to a single mRNA transcript. Although the operon organization has not yet ...
Operon Prediction by DNA Microarray: An Approach with a Bayesian Network Model. Hitoshi Shimizu. Shigeyuki Oba. Shin Ishii [email protected] shige-o ...
In this paper, we present a new method based on SVM (support vector machine) to predict operons at a genomic level in any target bacterial genome.