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Debarka Sengupta
Debarka Sengupta
Assoc. Prof., IIIT-Delhi & (Adj.) Assoc. Prof., QUT, Brisbane
Verified email at iiitd.ac.in - Homepage
Title
Cited by
Cited by
Year
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
5942017
AutoImpute: Autoencoder based imputation of single-cell RNA-seq data
D Talwar, A Mongia, D Sengupta, A Majumdar
Scientific reports 8 (1), 1-11, 2018
922018
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
902016
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, 2021
842021
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
692018
McImpute: matrix completion based imputation for single cell RNA-seq data
A Mongia, D Sengupta, A Majumdar
Frontiers in genetics, 9, 2019
482019
Discovery of rare cells from voluminous single cell expression data
A Jindal, P Gupta, D Sengupta
Nature communications 9 (1), 1-9, 2018
472018
Topological patterns in microRNA–gene regulatory network: studies in colorectal and breast cancer
D Sengupta, S Bandyopadhyay
Molecular bioSystems 9 (6), 1360-1371, 2013
382013
FOCS: Fast overlapped community search
S Bandyopadhyay, G Chowdhary, D Sengupta
IEEE Transactions on Knowledge and Data Engineering 27 (11), 2974-2985, 2015
362015
Fast, scalable and accurate differential expression analysis for single cells
D Sengupta, NA Rayan, M Lim, B Lim, S Prabhakar
BioRxiv, 049734, 2016
342016
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
332021
CellAtlasSearch: a scalable search engine for single cells
D Srivastava, A Iyer, V Kumar, D Sengupta
Nucleic acids research 46 (W1), W141-W147, 2018
292018
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
282018
Participation of microRNAs in human interactome: extraction of microRNA–microRNA regulations
D Sengupta, S Bandyopadhyay
Molecular Biosystems 7 (6), 1966-1973, 2011
262011
The best COVID-19 predictor is recent smell loss: a cross-sectional study
RC Gerkin, K Ohla, MG Veldhuizen, PV Joseph, CE Kelly, AJ Bakke, ...
MedRxiv, 2020
192020
Recent smell loss is the best predictor of COVID-19: a preregistered, cross-sectional study.
RC Gerkin, K Ohla, MG Veldhuizen, PV Joseph, CE Kelly, AJ Bakke, ...
Medrxiv: the Preprint Server for Health Sciences, 2020
192020
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
192020
Weighted markov chain based aggregation of biomolecule orderings
D Sengupta, U Maulik, S Bandyopadhyay
IEEE/ACM transactions on computational biology and bioinformatics 9 (3), 924-933, 2012
182012
Staging system to predict the risk of relapse in multiple myeloma patients undergoing autologous stem cell transplantation
C Goswami, S Poonia, L Kumar, D Sengupta
Frontiers in oncology, 633, 2019
162019
The molecular basis of loss of smell in 2019-nCoV infected individuals
K Gupta, SK Mohanty, S Kalra, A Mittal, T Mishra, J Ahuja, D Sengupta, ...
OSF Preprints, 2020
152020
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