[PDF][PDF] Machine learning in bioinformatics
This article reviews machine learning methods for bioinformatics. It presents modelling
methods, such as supervised classification, clustering and probabilistic graphical models for …
methods, such as supervised classification, clustering and probabilistic graphical models for …
A Bayesian Belief Network model of organizational factors for improving safe work behaviors in Thai construction industry
B Jitwasinkul, BHW Hadikusumo, AQ Memon - Safety science, 2016 - Elsevier
Organizational factors and human factors are intimately related and intermingled with each
other. Therefore, development of the implications for improving work safety behaviors is …
other. Therefore, development of the implications for improving work safety behaviors is …
[图书][B] Handbook of computational molecular biology
S Aluru - 2005 - taylorfrancis.com
The enormous complexity of biological systems at the molecular level must be answered
with powerful computational methods. Computational biology is a young field, but has seen …
with powerful computational methods. Computational biology is a young field, but has seen …
Soft computing methods for the prediction of protein tertiary structures: A survey
AE Márquez-Chamorro, G Asencio-Cortés… - Applied Soft …, 2015 - Elsevier
The problem of protein structure prediction (PSP) represents one of the most important
challenges in computational biology. Determining the three dimensional structure of proteins …
challenges in computational biology. Determining the three dimensional structure of proteins …
Hidden Markov models that use predicted local structure for fold recognition: alphabets of backbone geometry
An important problem in computational biology is predicting the structure of the large
number of putative proteins discovered by genome sequencing projects. Fold‐recognition …
number of putative proteins discovered by genome sequencing projects. Fold‐recognition …
Probabilistic multi-class multi-kernel learning: on protein fold recognition and remote homology detection
T Damoulas, MA Girolami - Bioinformatics, 2008 - academic.oup.com
Motivation: The problems of protein fold recognition and remote homology detection have
recently attracted a great deal of interest as they represent challenging multi-feature multi …
recently attracted a great deal of interest as they represent challenging multi-feature multi …
Using rotation forest for protein fold prediction problem: An empirical study
Recent advancement in the pattern recognition field has driven many classification
algorithms being implemented to tackle protein fold prediction problem. In this paper, a …
algorithms being implemented to tackle protein fold prediction problem. In this paper, a …
pyProGA—a PyMOL plugin for protein residue network analysis
The field of protein residue network (PRN) research has brought several useful methods and
techniques for structural analysis of proteins and protein complexes. Many of these are ripe …
techniques for structural analysis of proteins and protein complexes. Many of these are ripe …
Twin removal in genetic algorithms for protein structure prediction using low-resolution model
This paper presents the impact of twins and the measures for their removal from the
population of genetic algorithm (GA) when applied to effective conformational searching. It is …
population of genetic algorithm (GA) when applied to effective conformational searching. It is …
Graphical models for statistical inference and data assimilation
In data assimilation for a system which evolves in time, one combines past and current
observations with a model of the dynamics of the system, in order to improve the simulation …
observations with a model of the dynamics of the system, in order to improve the simulation …