| Machine learning predicts new anti-CRISPR proteins S Eitzinger, A Asif, KE Watters, AT Iavarone, GJ Knott, JA Doudna, ... Nucleic acids research 48 (9), 4698-4708, 2020 | 78 | 2020 |
| Deep-PHURIE: deep learning based hurricane intensity estimation from infrared satellite imagery M Dawood, A Asif, FAA Minhas Neural Computing and Applications 32 (13), 9009-9017, 2020 | 41 | 2020 |
| Learning protein binding affinity using privileged information WA Abbasi, A Asif, A Ben-Hur, FAA Minhas BMC bioinformatics 19, 1-12, 2018 | 34 | 2018 |
| Machine learning with abstention for automated liver disease diagnosis K Hamid, A Asif, W Abbasi, D Sabih 2017 International Conference on Frontiers of Information Technology (FIT …, 2017 | 33 | 2017 |
| AcrDB: a database of anti-CRISPR operons in prokaryotes and viruses L Huang, B Yang, H Yi, A Asif, J Wang, T Lithgow, H Zhang, FAA Minhas, ... Nucleic Acids Research 49 (D1), D622-D629, 2021 | 32 | 2021 |
| PHURIE: hurricane intensity estimation from infrared satellite imagery using machine learning A Asif, M Dawood, B Jan, J Khurshid, M DeMaria, FAA Minhas Neural Computing and Applications 32, 4821-4834, 2020 | 31 | 2020 |
| CaMELS: In silico prediction of calmodulin binding proteins and their binding sites WA Abbasi, A Asif, S Andleeb, FUAA Minhas Proteins: Structure, Function, and Bioinformatics 85 (9), 1724-1740, 2017 | 29 | 2017 |
| Training host-pathogen protein–protein interaction predictors AH Basit, WA Abbasi, A Asif, S Gull, FUAA Minhas Journal of bioinformatics and computational biology 16 (04), 1850014, 2018 | 27 | 2018 |
| Correlation filters for detection of cellular nuclei in histopathology images A Ahmad, A Asif, N Rajpoot, M Arif, FAA Minhas Journal of medical systems 42, 1-8, 2018 | 16 | 2018 |
| An aggregation of aggregation methods in computational pathology M Bilal, R Jewsbury, R Wang, HM AlGhamdi, A Asif, M Eastwood, ... Medical Image Analysis, 102885, 2023 | 15 | 2023 |
| Now you see it, now you dont: adversarial vulnerabilities in computational pathology A Foote, A Asif, A Azam, T Marshall-Cox, N Rajpoot, F Minhas arXiv preprint arXiv:2106.08153, 2021 | 14 | 2021 |
| An embarrassingly simple approach to neural multiple instance classification A Asif Pattern Recognition Letters 128, 474-479, 2019 | 12 | 2019 |
| REET: robustness evaluation and enhancement toolbox for computational pathology A Foote, A Asif, N Rajpoot, F Minhas Bioinformatics 38 (12), 3312-3314, 2022 | 11 | 2022 |
| MILAMP: multiple instance prediction of amyloid proteins F Munir, S Gul, A Asif IEEE/ACM Transactions on Computational Biology and Bioinformatics 18 (3 …, 2019 | 10 | 2019 |
| Cross-domain knowledge transfer for prediction of chemosensitivity in ovarian cancer patients A Yaar, A Asif, SEA Raza, N Rajpoot, F Minhas Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 8 | 2020 |
| Ten ways to fool the masses with machine learning F Minhas, A Asif, A Ben-Hur arXiv preprint arXiv:1901.01686, 2019 | 8 | 2019 |
| Towards launching AI algorithms for cellular pathology into clinical & pharmaceutical orbits A Asif, K Rajpoot, D Snead, F Minhas, N Rajpoot arXiv preprint arXiv:2112.09496, 2021 | 6 | 2021 |
| Fayyaz ul Amir Afsar Minhas. 2020 S Eitzinger, A Asif, KE Watters, AT Iavarone, GJ Knott, JA Doudna Machine learning predicts new anti-CRISPR proteins. Nucleic acids research …, 2020 | 6 | 2020 |
| Unleashing the potential of AI for pathology: challenges and recommendations A Asif, K Rajpoot, S Graham, D Snead, F Minhas, N Rajpoot The Journal of Pathology 260 (5), 564-577, 2023 | 4 | 2023 |
| Generalized neural framework for learning with rejection A Asif 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 4* | 2020 |
