Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Hantao Shu"'
Autor:
Peizhuo Wang, Xiao Wen, Han Li, Peng Lang, Shuya Li, Yipin Lei, Hantao Shu, Lin Gao, Dan Zhao, Jianyang Zeng
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-16 (2023)
Abstract Single-cell technologies enable the dynamic analyses of cell fate mapping. However, capturing the gene regulatory relationships and identifying the driver factors that control cell fate decisions are still challenging. We present CEFCON, a n
Externí odkaz:
https://doaj.org/article/5662bd565d8b40ccb9ef6a5dd4db6aa8
Autor:
Peizhuo Wang, Xiao Wen, Han Li, Peng Lang, Shuya Li, Yipin Lei, Hantao Shu, Lin Gao, Dan Zhao, Jianyang Zeng
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/36c7f0196a694cb3b7feb53a7ac0298c
Autor:
Yiyue Ge, Tingzhong Tian, Suling Huang, Fangping Wan, Jingxin Li, Shuya Li, Xiaoting Wang, Hui Yang, Lixiang Hong, Nian Wu, Enming Yuan, Yunan Luo, Lili Cheng, Chengliang Hu, Yipin Lei, Hantao Shu, Xiaolong Feng, Ziyuan Jiang, Yunfu Wu, Ying Chi, Xiling Guo, Lunbiao Cui, Liang Xiao, Zeng Li, Chunhao Yang, Zehong Miao, Ligong Chen, Haitao Li, Hainian Zeng, Dan Zhao, Fengcai Zhu, Xiaokun Shen, Jianyang Zeng
Publikováno v:
Signal Transduction and Targeted Therapy, Vol 6, Iss 1, Pp 1-16 (2021)
Abstract The global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires an urgent need to find effective therapeutics for the treatment of coronavirus disease 2019 (COVID-19). In this study, we developed an integrative dru
Externí odkaz:
https://doaj.org/article/4f3f4d21df9d4b8b88ef95b4b0a08a89
Publikováno v:
Briefings in Bioinformatics. 23
Computational recovery of gene regulatory network (GRN) has recently undergone a great shift from bulk-cell towards designing algorithms targeting single-cell data. In this work, we investigate whether the widely available bulk-cell data could be lev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b797962058410f7bf921610484cd5e1
https://doi.org/10.1093/bib/bbac389
https://doi.org/10.1093/bib/bbac389
Publikováno v:
Nature Computational Science. 1:491-501
Gene regulatory networks (GRNs) encode the complex molecular interactions that govern cell identity. Here we propose DeepSEM, a deep generative model that can jointly infer GRNs and biologically meaningful representation of single-cell RNA sequencing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::414b9e545119855cfafc31e1b2151231
https://doi.org/10.1038/s43588-021-00099-8
https://doi.org/10.1038/s43588-021-00099-8
Autor:
Shenyang Wu, Xiaolong Feng, Jianyang Zeng, Yuanpeng Xiong, Enming Yuan, Wang X, Nian Wu, Dan Zhao, Xiaofan Zhang, Fengcai Zhu, Tingzhong Tian, Peng Lang, Pilong Li, Jingxin Li, Yiyue Ge, Haitao Li, Xiaokun Shen, Weifan Xu, Hantao Shu, Shuya Li
Publikováno v:
Protein & Cell
The nucleus contains diverse phase-separated condensates that compartmentalize and concentrate biomolecules with distinct physicochemical properties. Here, we investigated whether condensates concentrate small-molecule cancer therapeutics such that t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6c4c63224189dfb793b833ac14896fb4
http://europepmc.org/articles/PMC7994959
http://europepmc.org/articles/PMC7994959
Autor:
Wang X, Dan Zhao, Enming Yuan, Yuanpeng Xiong, Shuya Li, Peng Lang, Pilong Li, Xiaolong Feng, Shenyang Wu, Jianyang Zeng, Xiaofan Zhang, Tingzhong Tian, Nian Wu, Weifan Xu, Hantao Shu, Haitao Li, Xiaokun Shen
The ongoing coronavirus disease 2019 (COVID-19) pandemic has raised an urgent need to develop effective therapeutics against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As a potential antiviral drug target, the nucleocapsid (N)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9eb665760de38dfcf756a1e9bfcbc14
https://doi.org/10.1101/2020.10.09.332734
https://doi.org/10.1101/2020.10.09.332734
Autor:
Ligong Chen, Liang Xiao, Chunhao Yang, Ziyuan Jiang, Haidong Tang, Huang S, Xiaokun Shen, Dan Zhao, Lixiang Hong, Fengcai Zhu, Lili Cheng, Hantao Shu, Xiaolong Feng, Xiling Guo, Zeng Li, Lunbiao Cui, Yipin Lei, Fangping Wan, Hui Yang, Jianyang Zeng, Zehong Miao, Enming Yuan, Ying Chi, Tingzhong Tian, J Li, Shuya Li, Yiyue Ge, Hainian Zeng, Nian Wu
The global spread of SARS-CoV-2 requires an urgent need to find effective therapeutics for the treatment of COVID-19. We developed a data-driven drug repositioning framework, which applies both machine learning and statistical analysis approaches to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a2cab450467144bcd7a4cb6305eaa81
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030452568
RECOMB
RECOMB
Background. Computational approaches for inferring the mechanisms of compound-protein interactions (CPIs) can greatly facilitate drug development. Recently, although a number of deep learning based methods have been proposed to predict binding affini
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad5c41186e33c81eb4bb5f950db5a267
https://doi.org/10.1007/978-3-030-45257-5_29
https://doi.org/10.1007/978-3-030-45257-5_29
Computational approaches for inferring the mechanisms of compound-protein interactions (CPIs) can greatly facilitate drug development. Recently, although a number of deep learning based methods have been proposed to predict binding affinities and att
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b43183935709096ff00f429692444e32
https://doi.org/10.1101/2019.12.30.891515
https://doi.org/10.1101/2019.12.30.891515