Prioritization of genes for translation: a computational approach.
Expert Rev Proteomics
; 21(4): 125-147, 2024 Apr.
Article
en 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.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Biología Computacional
/
Aprendizaje Automático
Límite:
Humans
Idioma:
En
Revista:
Expert Rev Proteomics
Asunto de la revista:
BIOQUIMICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Canadá
Pais de publicación:
Reino Unido