Prioritization of genes for translation: a computational approach.
Expert Rev Proteomics
; 21(4): 125-147, 2024 Apr.
Article
em En
| MEDLINE
| ID: mdl-38563427
ABSTRACT
INTRODUCTION:
Gene identification for genetic diseases is critical for the development of new diagnostic approaches and personalized treatment options. Prioritization of gene translation is an important consideration in the molecular biology field, allowing researchers to focus on the most promising candidates for further investigation. AREAS COVERED In this paper, we discussed different approaches to prioritize genes for translation, including the use of computational tools and machine learning algorithms, as well as experimental techniques such as knockdown and overexpression studies. We also explored the potential biases and limitations of these approaches and proposed strategies to improve the accuracy and reliability of gene prioritization methods. Although numerous computational methods have been developed for this purpose, there is a need for computational methods that incorporate tissue-specific information to enable more accurate prioritization of candidate genes. Such methods should provide tissue-specific predictions, insights into underlying disease mechanisms, and more accurate prioritization of genes. EXPERT OPINION Using advanced computational tools and machine learning algorithms to prioritize genes, we can identify potential targets for therapeutic intervention of complex diseases. This represents an up-and-coming method for drug development and personalized medicine.Palavras-chave
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Biologia Computacional
/
Aprendizado de Máquina
Limite:
Humans
Idioma:
En
Revista:
Expert Rev Proteomics
Assunto da revista:
BIOQUIMICA
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Canadá