iDHS-Deep: an integrated tool for predicting DNase I hypersensitive sites by deep neural network.
Brief Bioinform
; 22(5)2021 09 02.
Article
en En
| MEDLINE
| ID: mdl-33751027
ABSTRACT
DNase I hypersensitive site (DHS) refers to the hypersensitive region of chromatin for the DNase I enzyme. It is an important part of the noncoding region and contains a variety of regulatory elements, such as promoter, enhancer, and transcription factor-binding site, etc. Moreover, the related locus of disease (or trait) are usually enriched in the DHS regions. Therefore, the detection of DHS region is of great significance. In this study, we develop a deep learning-based algorithm to identify whether an unknown sequence region would be potential DHS. The proposed method showed high prediction performance on both training datasets and independent datasets in different cell types and developmental stages, demonstrating that the method has excellent superiority in the identification of DHSs. Furthermore, for the convenience of related wet-experimental researchers, the user-friendly web-server iDHS-Deep was established at http//lin-group.cn/server/iDHS-Deep/, by which users can easily distinguish DHS and non-DHS and obtain the corresponding developmental stage ofDHS.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Oryza
/
Programas Informáticos
/
ADN
/
Arabidopsis
/
Desoxirribonucleasa I
/
Aprendizaje Profundo
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Brief Bioinform
Asunto de la revista:
BIOLOGIA
/
INFORMATICA MEDICA
Año:
2021
Tipo del documento:
Article
País de afiliación:
China