Protein Tertiary Structure Prediction
Mostrando 1-12 de 30 artigos, teses e dissertações.
-
1. Homology modeling and epitope prediction of Der f 33
Dermatophagoides farinae (Der f), one of the main species of house dust mites, produces more than 30 allergens. A recently identified allergen belonging to the alpha-tubulin protein family, Der f 33, has not been characterized in detail. In this study, we used bioinformatics tools to construct the secondary and tertiary structures and predict the B and T cel
Braz J Med Biol Res. Publicado em: 15/03/2018
-
2. Função de avaliação dinâmica em algoritmos genéticos aplicados na predição de estruturas tridimensionais de proteínas / Genetic Algorithms with Dynamic Fitness Functions Applied to Tridimensional Protein Structure Prediction
The protein structure prediction can be seen as an optimization problem where given an amino acid sequence, the tertiary protein structure must be found amongst many possible by obtaining energy functions minima. Many researchers have been proposing Evolutionary Computation strategies to find tridimensional structures of proteins; however results are not alw
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 28/09/2012
-
3. Algoritmos evolutivos e modelos simplificados de proteínas para predição de estruturas terciárias / Evolutionary algorithms and simplified models for tertiary protein structure prediction
A predição de estruturas de proteínas (Protein Structure Prediction PSP) é um problema computacionalmente complexo. Para tratar esse problema, modelos simplificados de proteínas, como o Modelo HP, têm sido empregados para representar as conformações e Algoritmos Evolutivos (AEs) são utilizados na busca por soluções adequadas para PSP. Entretanto,
Publicado em: 2010
-
4. Utilização de máquinas de suporte vetorial para predição de estruturas terciárias de proteínas / Support vector machine for tertiary structure prediction
The three-dimensional structure of a protein is directly related to its function. Many projects of genetic sequence analysis accumulate a great number of protein sequences whose primary and secondary structures are known. However, the information on its three-dimensional structures are available only for a small fraction of these proteins. This fact evidence
Publicado em: 2007
-
5. Multi-objective approach to protein tertiary structure prediction / Algoritmo híbrido multi-objetivo para predição de estrutura terciária de proteínas
Muitos problemas de otimização multi-objetivo utilizam os algoritmos evolutivos para encontrar as melhores soluções. Muitos desses algoritmos empregam as fronteiras de Pareto como estratégia para obter tais soluções. Entretando, conforme relatado na literatura, há a limitação da fronteira para problemas com até três objetivos, podendo tornar seu
Publicado em: 2007
-
6. Use of artificial neural networks with Monte Carlo simulation applied to the protein folding problem / Uso de redes neurais artificiais na simulação Monte Carlo aplicado ao problema de dobramento de proteínas
This work proposes a new strategy to optimize the Monte Carlo method (MC) applied to the protein folding problem. This strategy is based on the information obtained from Artificial Neural Networks (ANNs), trained to predict the protein secondary structure. The work presents, initially, background knowledge about proteins and their structure. Follows an intro
Publicado em: 2006
-
7. Evolutionary algorithms, to proteins structures prediction / Algoritmos evolutivos para predição de estruturas de proteínas
A Determinação da Estrutura tridimensional de Proteínas (DEP) a partir da sua seqüência de aminoácidos é importante para a engenharia de proteínas e o desenvolvimento de novos fármacos. Uma alternativa para este problema tem sido a aplicação de técnicas de computação evolutiva. As abordagens utilizando Algoritmos Evolutivos (AEs) tem obtido res
Publicado em: 2006
-
8. Coupled prediction of protein secondary and tertiary structure
The strong coupling between secondary and tertiary structure formation in protein folding is neglected in most structure prediction methods. In this work we investigate the extent to which nonlocal interactions in predicted tertiary structures can be used to improve secondary structure prediction. The architecture of a neural network for secondary structure
National Academy of Sciences.
-
9. PROTINFO: secondary and tertiary protein structure prediction
Information about the secondary and tertiary structure of a protein sequence can greatly assist biologists in the generation and testing of hypotheses, as well as design of experiments. The PROTINFO server enables users to submit a protein sequence and request a prediction of the three-dimensional (tertiary) structure based on comparative modeling, fold gene
Oxford University Press.
-
10. TOUCHSTONE: An ab initio protein structure prediction method that uses threading-based tertiary restraints
The successful prediction of protein structure from amino acid sequence requires two features: an efficient conformational search algorithm and an energy function with a global minimum in the native state. As a step toward addressing both issues, a threading-based method of secondary and tertiary restraint prediction has been developed and applied to ab init
The National Academy of Sciences.
-
11. GeneSilico protein structure prediction meta-server
Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different method
Oxford University Press.
-
12. Toward predicting protein topology: An approach to identifying β hairpins
Although secondary structure prediction methods have recently improved, progress from secondary to tertiary structure prediction has been limited. A promising but largely unexplored route to this goal is to predict structure motifs from secondary structure knowledge. Here we present a novel method for the recognition of β hairpins that combines secondary st
National Academy of Sciences.