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» A graphical model for protein secondary structure prediction
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94
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BMCBI
2008
137views more  BMCBI 2008»
14 years 10 months ago
A dynamic Bayesian network approach to protein secondary structure prediction
Background: Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful informatio...
Xin-Qiu Yao, Huaiqiu Zhu, Zhen-Su She
109
Voted
JCB
2000
146views more  JCB 2000»
14 years 10 months ago
Bayesian Segmentation of Protein Secondary Structure
We present a novel method for predicting the secondary structure of a protein from its amino acid sequence. Most existing methods predict each position in turn based on a local wi...
Scott C. Schmidler, Jun S. Liu, Douglas L. Brutlag
JCB
2006
215views more  JCB 2006»
14 years 10 months ago
Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs)
Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e., segmentation con...
Yan Liu 0002, Jaime G. Carbonell, Peter Weigele, V...
BMCBI
2010
98views more  BMCBI 2010»
14 years 10 months ago
Prediction of protein structural classes for low-homology sequences based on predicted secondary structure
Background: Prediction of protein structural classes (a, b, a + b and a/b) from amino acid sequences is of great importance, as it is beneficial to study protein function, regulat...
Jian-Yi Yang, Zhen-Ling Peng, Xin Chen
83
Voted
DMKD
2003
ACM
110views Data Mining» more  DMKD 2003»
15 years 3 months ago
Weave amino acid sequences for protein secondary structure prediction
Given a known protein sequence, predicting its secondary structure can help understand its three-dimensional (tertiary) structure, i.e., the folding. In this paper, we present an ...
Xiaochun Yang, Bin Wang