K
Kailin Tang
Researcher at Tongji University
Publications - 45
Citations - 1168
Kailin Tang is an academic researcher from Tongji University. The author has contributed to research in topics: Biology & Epitope. The author has an hindex of 17, co-authored 40 publications receiving 919 citations. Previous affiliations of Kailin Tang include Chinese Academy of Sciences & East China University of Science and Technology.
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HIT: linking herbal active ingredients to targets
Hao Ye,Li Ye,Hong Kang,Duanfeng Zhang,Lin Tao,Kailin Tang,Xueping Liu,Ruixin Zhu,Qi Liu,Yu Zong Chen,Yixue Li,Zhiwei Cao +11 more
TL;DR: A comprehensive and fully curated database for Herb Ingredients’ Targets (HIT) has been constructed to complement above resources and contains 5208 entries about 1301 known protein targets affected by 586 herbal compounds from more than 1300 reputable Chinese herbs.
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Combining genomic and network characteristics for extended capability in predicting synergistic drugs for cancer.
Yi Sun,Zhen Sheng,Chao Ma,Kailin Tang,Ruixin Zhu,Zhuanbin Wu,Ruling Shen,Jun Feng,Dingfeng Wu,Danyi Huang,Dandan Huang,Jian Fei,Qi Liu,Zhiwei Cao +13 more
TL;DR: A Ranking-system of Anti-Cancer Synergy (RACS) that combines features of targeting networks and transcriptomic profiles, and validate it on three types of cancer, can significantly improve drug synergy prediction and markedly reduce the experimental prescreening of existing drugs for repurposing to cancer treatment.
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SEPPA 2.0—more refined server to predict spatial epitope considering species of immune host and subcellular localization of protein antigen
Tao Qi,Tianyi Qiu,Qingchen Zhang,Kailin Tang,Yangyang Fan,Jingxuan Qiu,Dingfeng Wu,Wei Zhang,Yanan Chen,Jun Gao,Ruixin Zhu,Zhiwei Cao +11 more
TL;DR: As the first method which has considered the subcellular localization of protein antigen and species of immune host,SEPPA 2.0 shows obvious advantages over the other popular servers like SEPPA, PEPITO, DiscoTope-2, B-pred, Bpredictor and Epitopia in supporting more specific biological needs.
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SEPPA 3.0-enhanced spatial epitope prediction enabling glycoprotein antigens.
Chen Zhou,Zikun Chen,Lu Zhang,Deyu Yan,Tiantian Mao,Kailin Tang,Tianyi Qiu,Tianyi Qiu,Zhiwei Cao +8 more
TL;DR: As the first server enabling accurate epitope prediction for glycoproteins, SEPPA 3.0 shows significant advantages over popular peers on both general protein and glycoprotein antigens.
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Clarifying the signal network of salvianolic acid B using proteomic assay and bioinformatic analysis.
Li-Xing Feng,Chun-Jie Jing,Kailin Tang,Lin Tao,Zhiwei Cao,Wanying Wu,Shu-Hong Guan,Baohong Jiang,Min Yang,Xuan Liu,De-An Guo +10 more
TL;DR: In the present study, epidermal growth factor receptor (EGFR) was predicted to be the most possible direct protein target of SB by INVDOCK, a ligand–protein inverse‐docking algorithm and signal network from EGFR to the signal‐related proteins was established using bioinformatic analysis.