| Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors H Li, ET Courtois, D Sengupta, Y Tan, KH Chen, JJL Goh, SL Kong, ... Nature genetics 49 (5), 708-718, 2017 | 993 | 2017 |
| AutoImpute: Autoencoder based imputation of single-cell RNA-seq data D Talwar, A Mongia, D Sengupta, A Majumdar Scientific reports 8 (1), 16329, 2018 | 173 | 2018 |
| Recent smell loss is the best predictor of COVID-19 among individuals with recent respiratory symptoms RC Gerkin, K Ohla, MG Veldhuizen, PV Joseph, CE Kelly, AJ Bakke, ... Chemical senses 46, bjaa081, 2021 | 164 | 2021 |
| Tumor-derived circulating endothelial cell clusters in colorectal cancer I Cima, SL Kong, D Sengupta, IB Tan, WM Phyo, D Lee, M Hu, C Iliescu, ... Science translational medicine 8 (345), 345ra89-345ra89, 2016 | 121 | 2016 |
| Anemia prevalence in women of reproductive age in low-and middle-income countries between 2000 and 2018 D Kinyoki, AE Osgood-Zimmerman, NV Bhattacharjee, NJ Kassebaum, ... Nature medicine 27 (10), 1761-1782, 2021 | 119 | 2021 |
| Discovery of rare cells from voluminous single cell expression data A Jindal, P Gupta, Jayadeva, D Sengupta Nature communications 9 (1), 4719, 2018 | 116 | 2018 |
| dropClust: efficient clustering of ultra-large scRNA-seq data D Sinha, A Kumar, H Kumar, S Bandyopadhyay, D Sengupta Nucleic acids research 46 (6), e36-e36, 2018 | 110 | 2018 |
| McImpute: matrix completion based imputation for single cell RNA-seq data A Mongia, D Sengupta, A Majumdar Frontiers in genetics 10, 9, 2019 | 81 | 2019 |
| Gene expression based inference of cancer drug sensitivity S Chawla, A Rockstroh, M Lehman, E Ratther, A Jain, A Anand, A Gupta, ... Nature communications 13 (1), 5680, 2022 | 64 | 2022 |
| The cellular basis of loss of smell in 2019-nCoV-infected individuals K Gupta, SK Mohanty, A Mittal, S Kalra, S Kumar, T Mishra, J Ahuja, ... Briefings in bioinformatics 22 (2), 873-881, 2021 | 54 | 2021 |
| Mapping inequalities in exclusive breastfeeding in low-and middle-income countries, 2000–2018 NV Bhattacharjee, LE Schaeffer, SI Hay Nature Human Behaviour 5 (8), 1027-1045, 2021 | 53 | 2021 |
| Stable feature selection using copula based mutual information S Lall, D Sinha, A Ghosh, D Sengupta, S Bandyopadhyay Pattern Recognition 112, 107697, 2021 | 48 | 2021 |
| Structure-aware principal component analysis for single-cell RNA-seq data S Lall, D Sinha, S Bandyopadhyay, D Sengupta Journal of Computational Biology 25 (12), 1365-1373, 2018 | 45 | 2018 |
| FOCS: Fast overlapped community search S Bandyopadhyay, G Chowdhary, D Sengupta IEEE Transactions on Knowledge and Data Engineering 27 (11), 2974-2985, 2015 | 45 | 2015 |
| Hide and seek: outwitting community detection algorithms S Mittal, D Sengupta, T Chakraborty IEEE Transactions on Computational Social Systems 8 (4), 799-808, 2021 | 43 | 2021 |
| CellAtlasSearch: a scalable search engine for single cells D Srivastava, A Iyer, V Kumar, D Sengupta Nucleic acids research 46 (W1), W141-W147, 2018 | 43 | 2018 |
| Topological patterns in microRNA–gene regulatory network: studies in colorectal and breast cancer D Sengupta, S Bandyopadhyay Molecular bioSystems 9 (6), 1360-1371, 2013 | 39 | 2013 |
| Fast, scalable and accurate differential expression analysis for single cells D Sengupta, NA Rayan, M Lim, B Lim, S Prabhakar BioRxiv, 049734, 2016 | 38 | 2016 |
| Integrative analysis and machine learning based characterization of single circulating tumor cells A Iyer, K Gupta, S Sharma, K Hari, YF Lee, N Ramalingam, YS Yap, ... Journal of clinical medicine 9 (4), 1206, 2020 | 33 | 2020 |
| Participation of microRNAs in human interactome: extraction of microRNA–microRNA regulations D Sengupta, S Bandyopadhyay Molecular Biosystems 7 (6), 1966-1973, 2011 | 27 | 2011 |
Sanghamitra BandyopadhyayProfessor of Computer Science, Indian Statistical Institute, Kolkata, IndiaDirección de correo verificada de isical.ac.in
