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Jing Tang 0002
Person information
- affiliation: University of Helsinki, Institute for Molecular Medicine, Finland
- affiliation (PhD 2009): University of Helsinki, Department of Mathematics and Statistics, Finland
Other persons with the same name
- Jing Tang — disambiguation page
- Jing Tang 0001 — Teesside University, School of Computing, Middlesbrough, UK (and 1 more)
- Jing Tang 0003 — Tokyo Institute of Technology, Department of Industrial Engineering and Management, Graduate School of Decision Science and Technology, Japan
- Jing Tang 0004 — Hong Kong University of Science and Technology Guangzhou (HKUST-GZ), Guangzhou, China (and 3 more)
- Jing Tang 0005 — Oakland University, Department of Electrical and Computer Engineering, Rochester, MI, USA
Other persons with a similar name
- Jing-Tang Jang
- Jing-Jou Tang
- Jing-Tian Tang
- Jing-Wei Tang
- Jing-Xian Tang
- Jing-Yau Tang
- Jing Rui Tang
- Jingfan Tang (aka: Jing-fan Tang)
- Jinglei Tang (aka: Jing-Lei Tang) — Northwest A&F University, Yangling, China (and 1 more)
- Xiao-Jing Tang
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2020 – today
- 2024
- [j30]Yinyin Wang, Yihang Sui, Jiaqi Yao, Hong Jiang, Qimeng Tian, Yun Tang, Yongyu Ou, Jing Tang, Ninghua Tan:
Herb-CMap: a multimodal fusion framework for deciphering the mechanisms of action in traditional Chinese medicine using Suhuang antitussive capsule as a case study. Briefings Bioinform. 25(5) (2024) - [j29]Yi-Ching Tang, Rongbin Li, Jing Tang, W. Jim Zheng, Xiaoqian Jiang:
SAFER: sub-hypergraph attention-based neural network for predicting effective responses to dose combinations. BMC Bioinform. 25(1): 250 (2024) - 2023
- [j28]Christian Ohmann, Maria Panagiotopoulou, Steve Canham, Petr Holub, Kurt Majcen, Gary Saunders, Maddalena Fratelli, Jing Tang, Philip Gribbon, Reagon Karki, Mari Kleemola, Katja Moilanen, Daan Broeder, Walter Daelemans, Pieter Fivez:
Proposal for a framework of contextual metadata in selected research infrastructures of the life sciences and the social sciences & humanities. Int. J. Metadata Semant. Ontologies 16(4): 261-277 (2023) - [j27]Alina Malyutina, Jing Tang, Alberto Pessia:
drda: An R Package for Dose-Response Data Analysis Using Logistic Functions. J. Stat. Softw. 106(4) (2023) - [j26]Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, Ian Selby, Anna Breger, Matthew Thorpe, Jonathan R. Weir-McCall, Effrossyni Gkrania-Klotsas, Anna Korhonen, Emily R. Jefferson, Georg Langs, Guang Yang, Helmut Prosch, Jan Stanczuk, Jing Tang, Judith Babar, Lorena Escudero Sanchez, Philip Teare, Mishal Patel, Marcel Wassin, Markus Holzer, Nicholas Walton, Pietro Lió, Tolou Shadbahr, Evis Sala, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb:
Navigating the development challenges in creating complex data systems. Nat. Mac. Intell. 5(7): 681-686 (2023) - [j25]Jianxin Wang, Min Li, Edwin Wang, Jing Tang, Bin Hu:
The Impact of Computational Drug Discovery on Society. IEEE Trans. Comput. Soc. Syst. 10(5): 2148-2159 (2023) - [i8]Zhangli Lu, Chuqi Lei, Kaili Wang, Libo Qin, Jing Tang, Min Li:
DTIAM: A unified framework for predicting drug-target interactions, binding affinities and activation/inhibition mechanisms. CoRR abs/2312.15252 (2023) - 2022
- [j24]ZiaurRehman Tanoli, Jehad Aldahdooh, Farhan Alam, Yinyin Wang, Umair Seemab, Maddalena Fratelli, Petr Pavlis, Marián Hajdúch, Florence Bietrix, Philip Gribbon, Andrea Zaliani, Matthew D. Hall, Min Shen, Kyle R. Brimacombe, Evgeny Kulesskiy, Saarela Jani, Krister Wennerberg, Markus Vähä-Koskela, Jing Tang:
Minimal information for chemosensitivity assays (MICHA): a next-generation pipeline to enable the FAIRification of drug screening experiments. Briefings Bioinform. 23(1) (2022) - [j23]Ali Amiryousefi, Bernardo Williams, Mohieddin Jafari, Jing Tang:
The ENDS of assumptions: an online tool for the epistemic non-parametric drug-response scoring. Bioinform. 38(11): 3132-3133 (2022) - [j22]Jehad Aldahdooh, Markus Vähä-Koskela, Jing Tang, ZiaurRehman Tanoli:
Using BERT to identify drug-target interactions from whole PubMed. BMC Bioinform. 23(1): 245 (2022) - [j21]Shuyu Zheng, Wenyu Wang, Jehad Aldahdooh, Alina Malyutina, Tolou Shadbahr, ZiaurRehman Tanoli, Alberto Pessia, Jing Tang:
SynergyFinder Plus: Toward Better Interpretation and Annotation of Drug Combination Screening Datasets. Genom. Proteom. Bioinform. 20(3): 587-596 (2022) - [i7]Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian D. Gilbey, Philip Teare, Sören Dittmer, Matthew Thorpe, Ramón Viñas Torné, Evis Sala, Pietro Lió, Mishal Patel, AIX-COVNET Collaboration, James H. F. Rudd, Tuomas Mirtti, Antti Rannikko, John A. D. Aston, Jing Tang, Carola-Bibiane Schönlieb:
Classification of datasets with imputed missing values: does imputation quality matter? CoRR abs/2206.08478 (2022) - [i6]Huimin Zhu, Renyi Zhou, Jing Tang, Min Li:
PGMG: A Pharmacophore-Guided Deep Learning Approach for Bioactive Molecular Generation. CoRR abs/2207.00821 (2022) - 2021
- [j20]ZiaurRehman Tanoli, Umair Seemab, Andreas Scherer, Krister Wennerberg, Jing Tang, Markus Vähä-Koskela:
Exploration of databases and methods supporting drug repurposing: a comprehensive survey. Briefings Bioinform. 22(2): 1656-1678 (2021) - [j19]Yinyin Wang, Hongbin Yang, Linxiao Chen, Mohieddin Jafari, Jing Tang:
Network-based modeling of herb combinations in traditional Chinese medicine. Briefings Bioinform. 22(5) (2021) - [j18]Liye He, Daria Bulanova, Jaana Oikkonen, Antti Häkkinen, Kaiyang Zhang, Shuyu Zheng, Wenyu Wang, Erdogan Pekcan Erkan, Olli Carpén, Titta Joutsiniemi, Sakari Hietanen, Johanna Hynninen, Kaisa Huhtinen, Sampsa Hautaniemi, Anna Vähärautio, Jing Tang, Krister Wennerberg, Tero Aittokallio:
Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer. Briefings Bioinform. 22(6) (2021) - [j17]Bulat Zagidullin, Ziyan Wang, Yuanfang Guan, Esa Pitkänen, Jing Tang:
Comparative analysis of molecular fingerprints in prediction of drug combination effects. Briefings Bioinform. 22(6) (2021) - [j16]Yejin Kim, Shuyu Zheng, Jing Tang, W. Jim Zheng, Zhao Li, Xiaoqian Jiang:
Anticancer drug synergy prediction in understudied tissues using transfer learning. J. Am. Medical Informatics Assoc. 28(1): 42-51 (2021) - [j15]Shuyu Zheng, Jehad Aldahdooh, Tolou Shadbahr, Yinyin Wang, Dalal Aldahdooh, Jie Bao, Wenyu Wang, Jing Tang:
DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal. Nucleic Acids Res. 49(Webserver-Issue): 174-184 (2021) - [i5]Jehad Aldahdooh, ZiaurRehman Tanoli, Jing Tang:
R-BERT-CNN: Drug-target interactions extraction from biomedical literature. CoRR abs/2111.00611 (2021) - [i4]Ville Kinnula, Jing Tang, Ali Amiryousefi:
Bayesian supervised predictive classification and hypothesis testing toolkit for partition exchangeability. CoRR abs/2112.01618 (2021) - [i3]Ali Amiryousefi, Ville Kinnula, Jing Tang:
Bayes in Wonderland! Predictive supervised classification inference hits unpredictability. CoRR abs/2112.01880 (2021) - 2020
- [j14]Aleksandr Ianevski, Liye He, Tero Aittokallio, Jing Tang:
SynergyFinder: a web application for analyzing drug combination dose-response matrix data. Bioinform. 36(8): 2645 (2020) - [i2]Kanglin Hsieh, Yinyin Wang, Luyao Chen, Zhongming Zhao, Sean I. Savitz, Xiaoqian Jiang, Jing Tang, Yejin Kim:
Drug Repurposing for COVID-19 using Graph Neural Network with Genetic, Mechanistic, and Epidemiological Validation. CoRR abs/2009.10931 (2020)
2010 – 2019
- 2019
- [j13]Bulat Zagidullin, Jehad Aldahdooh, Shuyu Zheng, Wenyu Wang, Yinyin Wang, Joseph Saad, Alina Malyutina, Mohieddin Jafari, ZiaurRehman Tanoli, Alberto Pessia, Jing Tang:
DrugComb: an integrative cancer drug combination data portal. Nucleic Acids Res. 47(Webserver-Issue): W43-W51 (2019) - [j12]Alina Malyutina, Muntasir Mamun Majumder, Wenyu Wang, Alberto Pessia, Caroline Heckman, Jing Tang:
Drug combination sensitivity scoring facilitates the discovery of synergistic and efficacious drug combinations in cancer. PLoS Comput. Biol. 15(5) (2019) - [j11]Yinyin Wang, Mohieddin Jafari, Yun Tang, Jing Tang:
Predicting Meridian in Chinese traditional medicine using machine learning approaches. PLoS Comput. Biol. 15(11) (2019) - [i1]Alberto Pessia, Jing Tang:
Numerical evaluation of the transition probability of the simple birth-and-death process. CoRR abs/1909.10765 (2019) - 2018
- [j10]ZiaurRehman Tanoli, Zaid Alam, Markus Vähä-Koskela, Balaguru Ravikumar, Alina Malyutina, Alok Jaiswal, Jing Tang, Krister Wennerberg, Tero Aittokallio:
Drug Target Commons 2.0: a community platform for systematic analysis of drug-target interaction profiles. Database J. Biol. Databases Curation 2018: bay083 (2018) - 2017
- [j9]Aleksandr Ianevski, Liye He, Tero Aittokallio, Jing Tang:
SynergyFinder: a web application for analyzing drug combination dose-response matrix data. Bioinform. 33(15): 2413-2415 (2017) - 2015
- [j8]Tapio Pahikkala, Antti Airola, Sami Pietilä, Sushil Kumar Shakyawar, Agnieszka Szwajda, Jing Tang, Tero Aittokallio:
Toward more realistic drug-target interaction predictions. Briefings Bioinform. 16(2): 325-337 (2015) - [j7]Liye He, Krister Wennerberg, Tero Aittokallio, Jing Tang:
TIMMA-R: an R package for predicting synergistic multi-targeted drug combinations in cancer cell lines or patient-derived samples. Bioinform. 31(11): 1866-1868 (2015) - [j6]Paul Blomstedt, Jing Tang, Jie Xiong, Christian Granlund, Jukka Corander:
A Bayesian Predictive Model for Clustering Data of Mixed Discrete and Continuous Type. IEEE Trans. Pattern Anal. Mach. Intell. 37(3): 489-498 (2015) - 2014
- [j5]Jing Tang, Agnieszka Szwajda, Sushil Kumar Shakyawar, Tao Xu, Petteri Hintsanen, Krister Wennerberg, Tero Aittokallio:
Making Sense of Large-Scale Kinase Inhibitor Bioactivity Data Sets: A Comparative and Integrative Analysis. J. Chem. Inf. Model. 54(3): 735-743 (2014) - 2013
- [j4]Jing Tang, Leena Karhinen, Tao Xu, Agnieszka Szwajda, Bhagwan Yadav, Krister Wennerberg, Tero Aittokallio:
Target Inhibition Networks: Predicting Selective Combinations of Druggable Targets to Block Cancer Survival Pathways. PLoS Comput. Biol. 9(9) (2013)
2000 – 2009
- 2009
- [j3]Pekka Marttinen, Jing Tang, Bernard De Baets, Peter Dawyndt, Jukka Corander:
Bayesian Clustering of Fuzzy Feature Vectors Using a Quasi-Likelihood Approach. IEEE Trans. Pattern Anal. Mach. Intell. 31(1): 74-85 (2009) - [j2]Jing Tang, William P. Hanage, Christophe Fraser, Jukka Corander:
Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach. PLoS Comput. Biol. 5(8) (2009) - 2008
- [j1]Jukka Corander, Pekka Marttinen, Jukka Sirén, Jing Tang:
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. BMC Bioinform. 9 (2008)
Coauthor Index
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