A Bi-Recursive Neural Network Architecture for the Prediction of Protein Coarse Contact Maps

	This Article
	Subscribers, please Login Purchase article: $19 PDF IEEE Xplore Subscribers RSS feed
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/Endnote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Alessandro Vullo Articles by Paolo Frasconi

IEEE Computer Society Bioinformatics Conference (CSB'02)

Stanford, California

August 14-August 16

ISBN: 0-7695-1653-X

	ASCII Text	x
	Alessandro Vullo, Paolo Frasconi, "A Bi-Recursive Neural Network Architecture for the Prediction of Protein Coarse Contact Maps," Computational Systems Bioinformatics Conference, International IEEE Computer Society, pp. 187, IEEE Computer Society Bioinformatics Conference (CSB'02), 2002.

	BibTex	x
	@article{ 10.1109/CSB.2002.1039341, author = {Alessandro Vullo and Paolo Frasconi}, title = {A Bi-Recursive Neural Network Architecture for the Prediction of Protein Coarse Contact Maps}, journal ={Computational Systems Bioinformatics Conference, International IEEE Computer Society}, volume = {0}, year = {2002}, isbn = {0-7695-1653-X}, pages = {187}, doi = {http://doi.ieeecomputersociety.org/10.1109/CSB.2002.1039341}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computational Systems Bioinformatics Conference, International IEEE Computer Society TI - A Bi-Recursive Neural Network Architecture for the Prediction of Protein Coarse Contact Maps SN - 0-7695-1653-X SP EP A1 - Alessandro Vullo, A1 - Paolo Frasconi, PY - 2002 KW - Protein contact maps KW - machine learning KW - recursive neural networks VL - 0 JA - Computational Systems Bioinformatics Conference, International IEEE Computer Society ER -

Alessandro Vullo, University of Florence

Paolo Frasconi, University of Florence

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSB.2002.1039341

Prediction of contact maps may be seen as a strategic step towards the solution of fundamental open problems in structural genomics. In this paper we focus on coarse grained maps that describe the spatial neighborhood relation between secondary structure elements (helices, strands, and coils) of a protein. We introduce a new machine learning approach for scoring candidate contact maps. The method combines a specialized noncausal recursive connectionist architecture and a heuristic graph search algorithm. The network is trained using candidate graphs generated during search. We show how the process of selecting and generating training examples is important for tuning the precision of the predictor.

Index Terms:

Protein contact maps, machine learning, recursive neural networks

Citation:

Alessandro Vullo, Paolo Frasconi, "A Bi-Recursive Neural Network Architecture for the Prediction of Protein Coarse Contact Maps," csb, pp.187, IEEE Computer Society Bioinformatics Conference (CSB'02), 2002

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.