Abstract Protein Structure Prediction is a central topic in Structural Bioinformatics. Since
the'60s statistical methods, followed by increasingly complex Machine Learning and recently …

This article reviews machine learning methods for bioinformatics. It presents modelling
methods, such as supervised classification, clustering and probabilistic graphical models for …

Motivation: The accurate prediction of residue–residue contacts, critical for maintaining the
native fold of a protein, remains an open problem in the field of structural bioinformatics …

Background Predicting protein residue-residue contacts is an important 2D prediction task. It
is useful for ab initio structure prediction and understanding protein folding. In spite of steady …

A new de novo protein structure prediction method for transmembrane proteins (FILM3) is
described that is able to accurately predict the structures of large membrane proteins …

Protein contact map prediction is useful for protein folding rate prediction, model selection
and 3D structure prediction. Here we describe NNcon, a fast and reliable contact map …

Machine learning methods are widely used in bioinformatics and computational and
systems biology. Here, we review the development of machine learning methods for protein …

Motivation: Despite the continuing advance in the experimental determination of protein
structures, the gap between the number of known protein sequences and structures …

Motivation: Protein β-sheets play a fundamental role in protein structure, function, evolution,
and bio-engineering. Accurate prediction and assembly of protein β-sheets, however …

Preliminary sequence analysis of Plasmodium falciparum has shown that the proteome of
this organism is enriched in intrinsically unstructured proteins (IUPs), which are either …