In Silico Functional Assessment of Sequence Variations: Predicting Phenotypic Functions of Novel Variations
Genomics & Informatics
;
: 166-172, 2008.
Artigo
em Inglês
| WPRIM
| ID: wpr-203277
ABSTRACT
A multitude of protein-coding sequence variations (CVs) in the human genome have been revealed as a result of major initiatives, including the Human Variome Project, the 1000 Genomes Project, and the International Cancer Genome Consortium. This naturally has led to debate over how to accurately assess the functional consequences of CVs, because predicting the functional effects of CVs and their relevance to disease phenotypes is becoming increasingly important. This article surveys and compares variation databases and in silico prediction programs that assess the effects of CVs on protein function. We also introduce a combinatorial approach that uses machine learning algorithms to improve prediction performance.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Fenótipo
/
Simulação por Computador
/
Genoma Humano
/
Genoma
/
Substituição de Aminoácidos
/
Mutação de Sentido Incorreto
/
Aprendizado de Máquina
Tipo de estudo:
Estudo prognóstico
Limite:
Humanos
Idioma:
Inglês
Revista:
Genomics & Informatics
Ano de publicação:
2008
Tipo de documento:
Artigo
Similares
MEDLINE
...
LILACS
LIS