M6A-GSMS: Computational identification of N6-methyladenosine sites with GBDT and stacking learning in multiple species
Author:
Affiliation:
1. School of Mathematics and Statistics, Xidian University, Xi’an, P. R. China
2. School of Science, Xi’an Polytechnic University, Xi’an, P. R. China
Funder
National Natural Science Foundation of China
Natural Science Basic Research Program of Shaanxi
Fundamental Research Funds for the Central Universities
Publisher
Informa UK Limited
Subject
Molecular Biology,General Medicine,Structural Biology
Link
https://www.tandfonline.com/doi/pdf/10.1080/07391102.2021.1970628
Reference66 articles.
1. iMethyl-STTNC: Identification of N6-methyladenosine sites by extending the idea of SAAC into Chou's PseAAC to formulate RNA sequences
2. A CNN-Based RNA N6-Methyladenosine Site Predictor for Multiple Species Using Heterogeneous Features Representation
3. Further studies on the chromatographic behaviour of dinucleoside monophosphates
4. Application of high-dimensional feature selection: evaluation for genomic prediction in man
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