To solve the complicated non-linear mode-sorting problem of protein secondary structure prediction, the chapter proposed a new method based on radial basis function neural networks and learning from evolution. It also discussed the influence of data selection and structure design on the performance of the networks. The results indicate that this method is feasible and effective.To solve the complicated non-linear mode-sorting problem of protein secondary structure prediction, the chapter proposed a new method based on radial basis function neural networks and learning from evolution. It also discussed the influence of data selection and structure design on the performance of the networks. The results indicate that this method is feasible an...
Protein secondary structures prediction (PSSP) is considered as a challenging task in bioinformatics...
Protein structure prediction is very vital to innovative process of discovering new medications base...
This project applied artificial neural networks to the field of secondary structure prediction of pr...
A statical algorithm for protein secondary structure prediction, using a specifically adapted neural...
IEEE23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society --2...
Protein is considered the backbone of any human being. Protein is responsible for many functionaliti...
Neural networks have conventionally been used to predict protein secondary structure. However, they ...
ABSTRACT The paper proposes a neural network based approach to predict secondary structure of prote...
A method for protein secondary structure prediction based on the use of artificial neural networks (...
In this thesis, a novel Hybrid Neural Networks Predictor (HNNP) system for the Protein Secondary Str...
Protein is considered the backbone of any human being. Protein is responsible for many functionaliti...
Abstract — Neural network is one of the successful methods for protein secondary structure predictio...
211 p.This thesis is focused on protein secondary structure (PSS) prediction which is one of the mos...
Today, there are several protein secondary structure predictors; most of them use algorithms such as...
The recent studies indicate that the protein secondary structure provides very important advantages ...
Protein secondary structures prediction (PSSP) is considered as a challenging task in bioinformatics...
Protein structure prediction is very vital to innovative process of discovering new medications base...
This project applied artificial neural networks to the field of secondary structure prediction of pr...
A statical algorithm for protein secondary structure prediction, using a specifically adapted neural...
IEEE23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society --2...
Protein is considered the backbone of any human being. Protein is responsible for many functionaliti...
Neural networks have conventionally been used to predict protein secondary structure. However, they ...
ABSTRACT The paper proposes a neural network based approach to predict secondary structure of prote...
A method for protein secondary structure prediction based on the use of artificial neural networks (...
In this thesis, a novel Hybrid Neural Networks Predictor (HNNP) system for the Protein Secondary Str...
Protein is considered the backbone of any human being. Protein is responsible for many functionaliti...
Abstract — Neural network is one of the successful methods for protein secondary structure predictio...
211 p.This thesis is focused on protein secondary structure (PSS) prediction which is one of the mos...
Today, there are several protein secondary structure predictors; most of them use algorithms such as...
The recent studies indicate that the protein secondary structure provides very important advantages ...
Protein secondary structures prediction (PSSP) is considered as a challenging task in bioinformatics...
Protein structure prediction is very vital to innovative process of discovering new medications base...
This project applied artificial neural networks to the field of secondary structure prediction of pr...