iEnhancer-MFGBDT: Identifying enhancers and their strength by fusing multiple features and gradient boosting decision tree
Enhancer is a non-coding DNA fragment that can be bound with proteins to activate transcription of a gene, hence play an important role in regulating gene expression. Enhancer identification is very challenging and more complicated than other genetic factors due to their position variation and free...
Guardado en:
Autores principales: | Yunyun Liang, Shengli Zhang, Huijuan Qiao, Yinan Cheng |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
AIMS Press
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/16255e1ecfdb4bcc9d4ab534177f7a41 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Factors Influencing Pile Friction Bearing Capacity: Proposing a Novel Procedure Based on Gradient Boosted Tree Technique
por: Chia Yu Huat, et al.
Publicado: (2021) -
Predicting S-nitrosylation proteins and sites by fusing multiple features
por: Wang-Ren Qiu, et al.
Publicado: (2021) -
Application of gradient tree boosting regressor for the prediction of scour depth around bridge piers
por: B. M. Sreedhara, et al.
Publicado: (2021) -
Mapping Population Distribution Based on XGBoost Using Multisource Data
por: Xin Zhao, et al.
Publicado: (2021) -
Mothers Matter: Using Regression Tree Algorithms to Predict Adolescents’ Sharing of Drunk References on Social Media
por: Sebastian Kurten, et al.
Publicado: (2021)