Motivation: Existing methods for protein sequence analysis are generally firstorder and inherently assume that each position is independent. We develop a general framework for int...
Martin Madera, Ryan Calmus, Grant Thiltgen, Kevin ...
Background: Amino acid sequence probability distributions, or profiles, have been used successfully to predict secondary structure and local structure in proteins. Profile models ...
Background: Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio...
Gianluca Pollastri, Alberto J. M. Martin, Catherin...
Background: Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful informatio...
Background: The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algor...