@inproceedings{73420eb1153e4348b50835274c23b2fb,
title = "A probabilistic graphical model for ab initio folding",
abstract = "Despite significant progress in recent years, ab initio folding is still one of the most challenging problems in structural biology. This paper presents a probabilistic graphical model for ab initio folding, which employs Conditional Random Fields (CRFs) and directional statistics to model the relationship between the primary sequence of a protein and its three-dimensional structure. Different from the widely-used fragment assembly method and the lattice model for protein folding, our graphical model can explore protein conformations in a continuous space according to their probability. The probability of a protein conformation reflects its stability and is estimated from PSI-BLAST sequence profile and predicted secondary structure. Experimental results indicate that this new method compares favorably with the fragment assembly method and the lattice model.",
keywords = "Ab initio folding, Conditional random fields (CRFs), Directional statistics, Fragment assembly, Lattice model, Protein structure prediction",
author = "Feng Zhao and Jian Peng and {De Bartolo}, Joe and Freed, {K. F.} and Sosnick, {Tobin R.} and Jinbo Xu",
year = "2009",
doi = "10.1007/978-3-642-02008-7_5",
language = "English (US)",
isbn = "9783642020070",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "59--73",
booktitle = "Research in Computational Molecular Biology - 13th Annual International Conference, RECOMB 2009, Proceedings",
note = "13th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2009 ; Conference date: 18-05-2009 Through 21-05-2009",
}