| Integrating deep learning with microfluidics for biophysical classification of sickle red blood cells adhered to laminin N Praljak, S Iram, U Goreke, G Singh, A Hill, UA Gurkan, M Hinczewski PLoS Computational Biology 17 (11), e1008946, 2021 | 17* | 2021 |
| Discerning the painter’s hand: machine learning on surface topography F Ji, MS McMaster, S Schwab, G Singh, LN Smith, S Adhikari, M O’Dwyer, ... Heritage Science 9, 1-11, 2021 | 10 | 2021 |
| Catch bonds in sickle cell disease: shear-enhanced adhesion of red blood cells to laminin U Goreke, S Iram, G Singh, S Domínguez-Medina, Y Man, A Bode, R An, ... Biophysical Journal 122 (12), 2564-2576, 2023 | 3 | 2023 |
| A Deep Learning Framework for Sickle Cell Disease Microfluidic Biomarker Assays N Praljak, B Shipley, A Gonzales, U Goreke, S Iram, G Singh, A Hill, ... Blood 136, 15-16, 2020 | 1 | 2020 |
| Chromatinization modulates topoisomerase II processivity J Lee, M Wu, G Singh, J Inman, S ha Park, JH Lee, RM Fullbright, Y Hong, ... Biophysical Journal 123 (3), 499a, 2024 | | 2024 |
| Chromatinization modulates topoisomerase II processivity J Lee, M Wu, JT Inman, G Singh, SH Park, JH Lee, RM Fulbright, Y Hong, ... Nature communications 14 (1), 6844, 2023 | | 2023 |
| Classification of blood cells N Praljak, I Shamreen, U Goreke, M Hinczewski, H Ailis, U Gurkan, ... US Patent App. 17/928,976, 2023 | | 2023 |
| Investigating Heterogeneity within Sickle Cell Disease Using Deep Learning N Praljak, S Iram, G Singh, A Hill, U Goreke, U Gurkan, M Hinczewski Bulletin of the American Physical Society 64, 2019 | | 2019 |
| The dynamics of laminin-mediated red blood cell adhesion in sickle cell disease S Iram, U Goreke, G Singh, J Little, U Gurkan, M Hinczewski APS March Meeting Abstracts 2019, P66. 009, 2019 | | 2019 |
| Machine Learning-Based Numerical Characterization of Paintings Using Variation in Brushstroke Styles G Singh, F Ji, J Trookman, K Singer, I Martin, L Smith, E Bolman, ... | | |
