Towards a Probabilistic Recognition Code for Protein-DNA Interactions: The Phage Display Approach.

[摘要] We are investigating the rules that govern protein-DNA interactions, using a statistical mechanics baaed formalism that is related to the Boltzmann Machine of the neural net literature. Our approach is data-driven, in which a probabilistic algorithm, SAMIE (Statistical Algorithm for Modeling Interaction Energies), is used to model protein-DNA interactions. SELEX and phage display data can be used for the training. For the current report, SAMIE was trained on phage display experimental data, collected from the literature, according to the one-to-one model of interactions (i.e. one amino acid contacts one base). We tested the prediction capabilities of the trained model on its own training set and on independent data. In all cases, the predictions using SAMIE are better than that of methods existing in the literature. However, our methodology offers the potential to capitalise on quantitative detail, as well as to be used to explore more general model of interactions, given availability of data.

[发布机构] Technical Information Center Oak Ridge Tennessee

[学科分类] 工程和技术（综合）

[关键词] Protein structure;Dna;Interactions;Phage display