Machine learning predicts nucleosome binding modes of transcription factors

被引：0
作者：
K. C. Kishan
Sridevi K. Subramanya
Rui Li
Feng Cui
机构：
[1] Rochester Institute of Technology,Thomas H. Gosnell School of Life Sciences
[2] Rochester Institute of Technology,Golisano College of Computing and Information Sciences
来源：
BMC Bioinformatics | / 22卷
关键词：
Machine learning; Nucleosome binding modes; Transcription factors;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
[21]   Opportunities for human factors in machine learning [J].
Baweja, Jessica A. ;
Fallon, Corey K. ;
Jefferson, Brett A. .
FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2023, 6
[22]   Predicting bacterial transcription factor binding sites through machine learning and structural characterization based on DNA duplex stability [J].
Borges Farias, Andre ;
Martinez, Gustavo Sganzerla ;
Galan-Vasquez, Edgardo ;
Nicolas, Marisa Fabiana ;
Perez-Rueda, Ernesto .
BRIEFINGS IN BIOINFORMATICS, 2024, 25 (06)
[23]   Machine learning models predicts risk of proliferative lupus nephritis [J].
Yang, Panyu ;
Liu, Zhongyu ;
Lu, Fenjian ;
Sha, Yulin ;
Li, Penghao ;
Zheng, Qu ;
Wang, Kefen ;
Zhou, Xin ;
Zeng, Xiaoxi ;
Wu, Yongkang .
FRONTIERS IN IMMUNOLOGY, 2024, 15
[24]   Machine learning predicts cerebral vasospasm in patients with subarachnoid haemorrhage [J].
Zarrin, David A. ;
Suri, Abhinav ;
McCarthy, Karen ;
Gaonkar, Bilwaj ;
Wilson, Bayard R. ;
Colby, Geoffrey P. ;
Freundlich, Robert E. ;
Gabel, Eilon .
EBIOMEDICINE, 2024, 105
[25]   Machine learning predicts properties of hydrochar derived from digestate [J].
Wang, Wei ;
Chang, Jo-Shu ;
Lee, Duu-Jong .
JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS, 2025, 167
[26]   Failure Modes Detection of Nuclear Systems using Machine Learning [J].
Tian, David ;
Deng, Jiamei ;
Zio, Enrico ;
Di Maio, Francesco ;
Liao, Fucheng .
2018 5TH INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND THEIR APPLICATIONS (DSA), 2018, :35-43
[27]   Physics-Informed Machine Learning for Optical Modes in Composites [J].
Ghosh, Abantika ;
Elhamod, Mohannad ;
Bu, Jie ;
Lee, Wei-Cheng ;
Karpatne, Anuj ;
Podolskiy, Viktor A. .
ADVANCED PHOTONICS RESEARCH, 2022, 3 (11)
[28]   Factors Influencing the Binding of HIV-1 Protease Inhibitors: Insights from Machine Learning Models [J].
Shalit, Yaffa ;
Tuvi-Arad, Inbal .
CHEMMEDCHEM, 2025,
[29]   Assessing the information content of structural and protein-ligand interaction representations for the classification of kinase inhibitor binding modes via machine learning and active learning [J].
Rodriguez-Perez, Raquel ;
Miljkovic, Filip ;
Bajorat, Juergen .
JOURNAL OF CHEMINFORMATICS, 2020, 12 (01)
[30]   Application of Machine Learning Algorithms to Metadynamics for the Elucidation of the Binding Modes and Free Energy Landscape of Drug/Target Interactions: a Case Study [J].
Siddiqui, Gohar Ali ;
Stebani, Julia A. ;
Wragg, Darren ;
Koutsourelakis, Phaedon-Stelios ;
Casini, Angela ;
Gagliardi, Alessio .
CHEMISTRY-A EUROPEAN JOURNAL, 2023, 29 (62)
12345