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Updated: Jul 7, 2026

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy
Published on: February 7, 2019
A parametric joint model of DNA-protein binding, gene expression and DNA sequence data to detect target genes of a
Wei Pan1, Peng Wei, Arkady Khodursky
1Division of Biostatistics, School of Public Health, University of Minnesota, USA.
Abstract:
This paper concerns with predicting the regulatory targets of a transcription factor (TF). We propose and study a joint model that combines the use of DNA-protein binding, gene expression and DNA sequence data simultaneously; a parametric mixture model is used to realize unsupervised learning, which however can be extended to semi-supervised learning too. We applied the methods to an E coli dataset to identify the target genes of LexA, which, along with applications to simulated data, demonstrated potential gains of jointly modeling multiple types of data over using only one type of data.
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