Peipei Huo
Chinese Academy of Sciences
7 Papers
Peipei Huo is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Biology & Modern medicine. The author has an hindex of 3, co-authored 4 publications.
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Papers
KOBAS-i: intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis.
Dechao Bu,Haitao Luo,Peipei Huo,Zhihao Wang,Shan Zhang,Zihao He,Yang Wu,Lianhe Zhao,Jingjia Liu,Jin-Cheng Guo,Shuangsang Fang,Wanchen Cao,Lan Yi,Yi Zhao,Lei Kong +14 more
TL;DR: A novel machine learning-based method was introduced, CGPS, which incorporates seven FCS tools and two PT tools into a single ensemble score and intelligently prioritizes the relevant biological pathways.
HERB: a high-throughput experiment- and reference-guided database of traditional Chinese medicine.
Shuangsang Fang,Lei Dong,Liu Liu,Jin-Cheng Guo,Lianhe Zhao,JiaYuan Zhang,Dechao Bu,Xinkui Liu,Peipei Huo,Wanchen Cao,Qiongye Dong,Jiarui Wu,Xiaoxi Zeng,Yang Wu,Yi Zhao,Yi Zhao +15 more
TL;DR: HERB will intensively support the modernization of TCM and guide rational modern drug discovery efforts, with its Chinese name as BenCaoZuJian.
408
FangNet: Mining herb hidden knowledge from TCM clinical effective formulas using structure network algorithm.
Dechao Bu,Yan Xia,JiaYuan Zhang,Wanchen Cao,Peipei Huo,Zhihao Wang,Zihao He,Linyi Ding,Yang Wu,Shan Zhang,Kai Gao,He Yu,Tiegang Liu,Xia Ding,Xiaohong Gu,Yi Zhao,Yi Zhao +16 more
TL;DR: FangNet as mentioned in this paper ranks all herbs on their relative topological importance using the PageRank algorithm, based on the constructed symptom-herb network from a collection of clinical empirical prescriptions.
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ncFANs v2.0: an integrative platform for functional annotation of non-coding RNAs.
Yuwei Zhang,Dechao Bu,Peipei Huo,Zhihao Wang,Hao Rong,Yanguo Li,Jingjia Liu,Meng Ye,Yang Wu,Zheng Jiang,Qi Liao,Yi Zhao +11 more
TL;DR: NCFANs v2.0 as discussed by the authors is an online platform for data-free functional annotation based on four kinds of pre-built networks, including the co-expression network, co-methylation network, long non-coding RNA (lncRNA)-centric regulatory network and random forest-based network.
TREAT: Therapeutic RNAs exploration inspired by artificial intelligence technology
Yufan Luo,Liu Liu,Zihao He,Shan Zhang,Peipei Huo,Zhihao Wang,Qin Jiaxin,Lianhe Zhao,Yang Wu,Dongdong Zhang,Dechao Bu,Runsheng Chen,Yi Zhao +12 more
TL;DR: TREAT as discussed by the authors is a one-stop platform for the screening and design of therapeutic RNAs, with particular attention to noncoding RNAs and cutting-edge AI technology embedded, leading the progress of innovative therapeutics for challenging diseases.
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