| GraphDTA: predicting drug–target binding affinity with graph neural networks T Nguyen, H Le, TP Quinn, T Nguyen, TD Le, S Venkatesh Bioinformatics 37 (8), 1140-1147, 2021 | 569 | 2021 |
| Understanding sequencing data as compositions: an outlook and review TP Quinn, I Erb, MF Richardson, TM Crowley Bioinformatics 34 (16), 2870-2878, 2018 | 283 | 2018 |
| A field guide for the compositional analysis of any-omics data TP Quinn, I Erb, G Gloor, C Notredame, MF Richardson, TM Crowley GigaScience 8 (9), giz107, 2019 | 213 | 2019 |
| propr: an R-package for identifying proportionally abundant features using compositional data analysis TP Quinn, MF Richardson, D Lovell, TM Crowley Scientific reports 7 (1), 1-9, 2017 | 164 | 2017 |
| The three ghosts of medical AI: Can the black-box present deliver? TP Quinn, S Jacobs, M Senadeera, V Le, S Coghlan Artificial intelligence in medicine 124, 102158, 2022 | 96 | 2022 |
| Trust and medical AI: the challenges we face and the expertise needed to overcome them TP Quinn, M Senadeera, S Jacobs, S Coghlan, V Le Journal of the American Medical Informatics Association 28 (4), 890-894, 2021 | 71 | 2021 |
| Blood transcriptomic comparison of individuals with and without autism spectrum disorder: A combined‐samples mega‐analysis DS Tylee, JL Hess, TP Quinn, R Barve, H Huang, Y Zhang‐James, ... American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 174 …, 2017 | 65 | 2017 |
| The maternal gut microbiome during pregnancy and offspring allergy and asthma Y Gao, R Nanan, L Macia, J Tan, L Sominsky, TP Quinn, M O’Hely, ... Journal of Allergy and Clinical Immunology 148 (3), 669-678, 2021 | 64 | 2021 |
| Aza-crown macrocycles as chiral solvating agents for mandelic acid derivatives TP Quinn, PD Atwood, JM Tanski, TF Moore, JF Folmer-Andersen The Journal of Organic Chemistry 76 (24), 10020-10030, 2011 | 61 | 2011 |
| Neurological and neuropsychiatric complications of COVID-19 in 153 patients: a UK-wide surveillance study. Lancet Psychiatry 7: 875–882 A Varatharaj, N Thomas, MA Ellul, NWS Davies, TA Pollak, EL Tenorio, ... S2215-0366 (20), 2020 | 60 | 2020 |
| Benchmarking differential expression analysis tools for RNA-Seq: normalization-based vs. log-ratio transformation-based methods TP Quinn, TM Crowley, MF Richardson BMC bioinformatics 19, 1-15, 2018 | 58 | 2018 |
| Deep in the bowel: highly interpretable neural encoder-decoder networks predict gut metabolites from gut microbiome V Le, TP Quinn, T Tran, S Venkatesh BMC genomics 21, 1-15, 2020 | 49 | 2020 |
| DeepTRIAGE: interpretable and individualised biomarker scores using attention mechanism for the classification of breast cancer sub-types A Beykikhoshk, TP Quinn, SC Lee, T Tran, S Venkatesh BMC medical genomics 13 (Suppl 3), 20, 2020 | 32 | 2020 |
| Bioinformatic analyses and conceptual synthesis of evidence linking ZNF804A to risk for schizophrenia and bipolar disorder JL Hess, TP Quinn, S Akbarian, SJ Glatt American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 168 …, 2015 | 29 | 2015 |
| Interpretable log contrasts for the classification of health biomarkers: a new approach to balance selection TP Quinn, I Erb Msystems 5 (2), 10.1128/msystems. 00230-19, 2020 | 28* | 2020 |
| Learning sparse log-ratios for high-throughput sequencing data E Gordon-Rodriguez, TP Quinn, JP Cunningham Bioinformatics 38 (1), 157-163, 2022 | 27 | 2022 |
| Meta-analysis and systematic review of ADGRL3 (LPHN3) polymorphisms in ADHD susceptibility EM Bruxel, CR Moreira-Maia, GC Akutagava-Martins, TP Quinn, M Klein, ... Molecular psychiatry 26 (6), 2277-2285, 2021 | 26 | 2021 |
| Infant microbiota in colic: Predictive associations with problem crying and subsequent child behavior A Loughman, T Quinn, ML Nation, A Reichelt, RJ Moore, TTH Van, ... Journal of Developmental Origins of Health and Disease 12 (2), 260-270, 2021 | 26 | 2021 |
| Amalgams: data-driven amalgamation for the dimensionality reduction of compositional data TP Quinn, I Erb NAR genomics and bioinformatics 2 (4), lqaa076, 2020 | 26* | 2020 |
| Machine-learning classification of 22q11. 2 deletion syndrome: a diffusion tensor imaging study DS Tylee, Z Kikinis, TP Quinn, KM Antshel, W Fremont, MA Tahir, A Zhu, ... NeuroImage: Clinical 15, 832-842, 2017 | 25 | 2017 |
Svetha VenkateshAlfred Deakin Professor, Deakin UniversityVerified email at deakin.edu.au
