Jing Tang
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Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations
J Corander, P Marttinen, J Sirén, J Tang
BMC bioinformatics 9, 1-14, 2008
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ...
Nature Machine Intelligence 3 (3), 199-217, 2021
Searching for drug synergy in complex dose–response landscapes using an interaction potency model
B Yadav, K Wennerberg, T Aittokallio, J Tang
Computational and structural biotechnology journal 13, 504-513, 2015
SynergyFinder: a web application for analyzing drug combination dose–response matrix data
A Ianevski, L He, T Aittokallio, J Tang
Bioinformatics 33 (15), 2413-2415, 2017
Toward more realistic drug–target interaction predictions
T Pahikkala, A Airola, S Pietilä, S Shakyawar, A Szwajda, J Tang, ...
Briefings in bioinformatics 16 (2), 325-337, 2015
Network pharmacology applications to map the unexplored target space and therapeutic potential of natural products
M Kibble, N Saarinen, J Tang, K Wennerberg, S Mäkelä, T Aittokallio
Natural product reports 32 (8), 1249-1266, 2015
Making sense of large-scale kinase inhibitor bioactivity data sets: a comparative and integrative analysis
J Tang, A Szwajda, S Shakyawar, T Xu, P Hintsanen, K Wennerberg, ...
Journal of Chemical Information and Modeling 54 (3), 735-743, 2014
Bayesian analysis of population structure based on linked molecular information
J Corander, J Tang
Mathematical biosciences 205 (1), 19-31, 2007
Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
MP Menden, D Wang, MJ Mason, B Szalai, KC Bulusu, Y Guan, T Yu, ...
Nature communications 10 (1), 2674, 2019
Association of lipidome remodeling in the adipocyte membrane with acquired obesity in humans
KH Pietiläinen, T Rog, T Seppänen-Laakso, S Virtue, P Gopalacharyulu, ...
PLoS biology 9 (6), e1000623, 2011
Hyper-recombination, diversity, and antibiotic resistance in pneumococcus
WP Hanage, C Fraser, J Tang, TR Connor, J Corander
Science 324 (5933), 1454-1457, 2009
What is synergy? The Saariselkä agreement revisited
J Tang, K Wennerberg, T Aittokallio
Frontiers in pharmacology 6, 181, 2015
Methods for high-throughput drug combination screening and synergy scoring
L He, E Kulesskiy, J Saarela, L Turunen, K Wennerberg, T Aittokallio, ...
Cancer systems biology: methods and protocols, 351-398, 2018
SynergyFinder plus: toward better interpretation and annotation of drug combination screening datasets
S Zheng, W Wang, J Aldahdooh, A Malyutina, T Shadbahr, Z Tanoli, ...
Genomics, Proteomics and Bioinformatics 20 (3), 587-596, 2022
Metabolome in schizophrenia and other psychotic disorders: a general population-based study
M Orešič, J Tang, T Seppänen-Laakso, I Mattila, SE Saarni, SI Saarni, ...
Genome medicine 3, 1-14, 2011
DrugComb: an integrative cancer drug combination data portal
B Zagidullin, J Aldahdooh, S Zheng, W Wang, Y Wang, J Saad, ...
Nucleic acids research 47 (W1), W43-W51, 2019
Network pharmacology strategies toward multi-target anticancer therapies: from computational models to experimental design principles
J Tang, T Aittokallio
Current pharmaceutical design 20 (1), 23-36, 2014
Drug target commons: a community effort to build a consensus knowledge base for drug-target interactions
J Tang, B Ravikumar, Z Alam, A Rebane, M Vähä-Koskela, G Peddinti, ...
Cell chemical biology 25 (2), 224-229. e2, 2018
JAK1/2 and BCL2 inhibitors synergize to counteract bone marrow stromal cell–induced protection of AML
R Karjalainen, T Pemovska, M Popa, M Liu, KK Javarappa, MM Majumder, ...
Blood, The Journal of the American Society of Hematology 130 (6), 789-802, 2017
Identifying currents in the gene pool for bacterial populations using an integrative approach
J Tang, WP Hanage, C Fraser, J Corander
PLoS computational biology 5 (8), e1000455, 2009
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