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

DE2001766381

Publication Date	2000
Personal Author	Benos, P. V.
Page Count	16
Abstract	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.
Keywords	Protein structure Dna Interactions Phage display
Source Agency	Technical Information Center Oak Ridge Tennessee
NTIS Subject Category	57 - Medicine & Biology
Corporate Authors	Los Alamos National Lab., NM.; Department of Energy, Washington, DC.
Document Type	Conference Proceedings
NTIS Issue Number	200123
Contract Number	W-7405-ENG-36

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

Towards a Probabilistic Recognition Code for Protein-DNA Interactions: The Phage Display Approach.
DE2001766381

Publication Date	2000
Personal Author	Benos, P. V.
Page Count	16
Abstract	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.
Keywords	Protein structure Dna Interactions Phage display
Source Agency	Technical Information Center Oak Ridge Tennessee
NTIS Subject Category	57 - Medicine & Biology
Corporate Authors	Los Alamos National Lab., NM.; Department of Energy, Washington, DC.
Document Type	Conference Proceedings
NTIS Issue Number	200123
Contract Number	W-7405-ENG-36