Zobrazeno 1 - 10 of 57 pro vyhledávání: '"Shoudong, Bi"'
1
Akademický článek
MTDeepM6A-2S: A two-stage multi-task deep learning method for predicting RNA N6-methyladenosine sites of Saccharomyces cerevisiae
Autor: Hong Wang, Shihao Zhao, Yinchu Cheng, Shoudong Bi, Xiaolei Zhu
Publikováno v: Frontiers in Microbiology, Vol 13 (2022)
N6-methyladenosine (m6A) is one of the most important RNA modifications, which is involved in many biological activities. Computational methods have been developed to detect m6A sites due to their high efficiency and low costs. As one of the most wid
Externí odkaz: https://doaj.org/article/b24c03b9f3aa42ada165c6c621f4e4b0
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2
Akademický článek
Aboveground biomass estimation in forests with random forest and Monte Carlo-based uncertainty analysis
Autor: Zizhao Li, Shoudong Bi, Shuang Hao, Yuhuan Cui
Publikováno v: Ecological Indicators, Vol 142, Iss , Pp 109246- (2022)
Estimates of aboveground biomass (AGB) in forests and the associated uncertainty are important pieces of information outlined in the United Nations Framework Convention on Climate Change. Traditional integrated surveying methods require high inputs o
Externí odkaz: https://doaj.org/article/ba9c33718c1c4c429952711c8632891f
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3
Akademický článek
m5CPred-SVM: a novel method for predicting m5C sites of RNA
Autor: Xiao Chen, Yi Xiong, Yinbo Liu, Yuqing Chen, Shoudong Bi, Xiaolei Zhu
Publikováno v: BMC Bioinformatics, Vol 21, Iss 1, Pp 1-21 (2020)
Abstract Background As one of the most common post-transcriptional modifications (PTCM) in RNA, 5-cytosine-methylation plays important roles in many biological functions such as RNA metabolism and cell fate decision. Through accurate identification o
Externí odkaz: https://doaj.org/article/f28b60d57b1c48d0a5ee21855ffc5729
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4
Akademický článek
BERT-Kgly: A Bidirectional Encoder Representations From Transformers (BERT)-Based Model for Predicting Lysine Glycation Site for Homo sapiens
Autor: Yinbo Liu, Yufeng Liu, Gang-Ao Wang, Yinchu Cheng, Shoudong Bi, Xiaolei Zhu
Publikováno v: Frontiers in Bioinformatics, Vol 2 (2022)
As one of the most important posttranslational modifications (PTMs), protein lysine glycation changes the characteristics of the proteins and leads to the dysfunction of the proteins, which may cause diseases. Accurately detecting the glycation sites
Externí odkaz: https://doaj.org/article/45c6d42a638a456c970902e4c94e8218
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7
A brief review of machine learning methods for RNA methylation sites prediction
Autor: Hong, Wang, Shuyu, Wang, Yong, Zhang, Shoudong, Bi, Xiaolei, Zhu
Publikováno v: Methods. 203:399-421
Thanks to the tremendous advancement of deep sequencing and large-scale profiling, epitranscriptomics has become a rapidly growing field. As one of the most important parts of epitranscriptomics, ribonucleic acid (RNA) methylation has been focused on
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6e22a149fb81741351821bf22648053
https://doi.org/10.1016/j.ymeth.2022.03.001
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