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Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision
View ORCID ProfileYungang Xu, Yongcui Wang, Jiesi Luo, Weiling Zhao, Xiaobo Zhou
doi: https://doi.org/10.1101/189183
Yungang Xu
1Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
3Center for Systems Medicine, School of Medical Bioinformatics, University of Texas Health Science Center at Houston, TX, 77030, USA
Yongcui Wang
2Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai, 810008, China
Jiesi Luo
1Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
Weiling Zhao
1Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
Xiaobo Zhou
1Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
3Center for Systems Medicine, School of Medical Bioinformatics, University of Texas Health Science Center at Houston, TX, 77030, USA
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Posted September 15, 2017.
Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision
Yungang Xu, Yongcui Wang, Jiesi Luo, Weiling Zhao, Xiaobo Zhou
bioRxiv 189183; doi: https://doi.org/10.1101/189183
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