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Vivek Das

Showing results (1-10 of 23) with videos related to

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Genes|December 30, 2025
What Do Single-Cell Models Already Know About Perturbations?Andreas Bjerregaard, Iñigo Prada-Luengo, Vivek Das, et al.
Frontiers in Molecular Biosciences|June 9, 2023
Unsupervised neural network for single cell Multi-omics INTegration (UMINT): an application to health and diseaseChayan Maitra, Dibyendu B Seal, Vivek Das, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|February 26, 2026
NeuroMDAVIS: Visualization of Single-Cell Multi-Omics Data under Deep Learning FrameworkChayan Maitra, Dibyendu B Seal, Vivek Das, et al.
Genomics|April 3, 2020
Estimating gene expression from DNA methylation and copy number variation: A deep learning regression model for multi-omics integrationDibyendu Bikash Seal, Vivek Das, Saptarsi Goswami, et al.
Frontiers in Genetics|December 28, 2020
State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and SharingMichal Krassowski, Vivek Das, Sangram K Sahu, et al.
Plant Science : an International Journal of Experimental Plant Biology|August 11, 2020
Short-term effects of the allelochemical umbelliferone on Triticum durum L. metabolism through GC-MS based untargeted metabolomicsBiswapriya B Misra, Vivek Das, M Landi, et al.
Nucleic Acids Research|May 19, 2016
RNAontheBENCH: computational and empirical resources for benchmarking RNAseq quantification and differential expression methodsPierre-Luc Germain, Alessandro Vitriolo, Antonio Adamo, et al.
The American Journal of Pathology|August 3, 2024
Single-Cell Advances in Investigating and Understanding Chronic Kidney Disease and Diabetic Kidney DiseaseSagar Bhayana, Philip A Schytz, Emma T Bisgaard Olesen, et al.
Plos One|May 20, 2024
Identification of ligand and receptor interactions in CKD and MASH through the integration of single cell and spatial transcriptomicsJaime Moreno, Lise Lotte Gluud, Elisabeth D Galsgaard, et al.
Frontiers in Bioinformatics|April 11, 2024
A systematic evaluation of state-of-the-art deconvolution methods in spatial transcriptomics: insights from cardiovascular disease and chronic kidney diseaseAlban Obel Slabowska, Charles Pyke, Henning Hvid, et al.
Pageof 3

Showing results (1-10 of 23) with videos related to

Sort By:
Pageof 3
Genes|December 30, 2025
What Do Single-Cell Models Already Know About Perturbations?Andreas Bjerregaard, Iñigo Prada-Luengo, Vivek Das, et al.
Frontiers in Molecular Biosciences|June 9, 2023
Unsupervised neural network for single cell Multi-omics INTegration (UMINT): an application to health and diseaseChayan Maitra, Dibyendu B Seal, Vivek Das, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|February 26, 2026
NeuroMDAVIS: Visualization of Single-Cell Multi-Omics Data under Deep Learning FrameworkChayan Maitra, Dibyendu B Seal, Vivek Das, et al.
Genomics|April 3, 2020
Estimating gene expression from DNA methylation and copy number variation: A deep learning regression model for multi-omics integrationDibyendu Bikash Seal, Vivek Das, Saptarsi Goswami, et al.
Frontiers in Genetics|December 28, 2020
State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and SharingMichal Krassowski, Vivek Das, Sangram K Sahu, et al.
Plant Science : an International Journal of Experimental Plant Biology|August 11, 2020
Short-term effects of the allelochemical umbelliferone on Triticum durum L. metabolism through GC-MS based untargeted metabolomicsBiswapriya B Misra, Vivek Das, M Landi, et al.
Nucleic Acids Research|May 19, 2016
RNAontheBENCH: computational and empirical resources for benchmarking RNAseq quantification and differential expression methodsPierre-Luc Germain, Alessandro Vitriolo, Antonio Adamo, et al.
The American Journal of Pathology|August 3, 2024
Single-Cell Advances in Investigating and Understanding Chronic Kidney Disease and Diabetic Kidney DiseaseSagar Bhayana, Philip A Schytz, Emma T Bisgaard Olesen, et al.
Plos One|May 20, 2024
Identification of ligand and receptor interactions in CKD and MASH through the integration of single cell and spatial transcriptomicsJaime Moreno, Lise Lotte Gluud, Elisabeth D Galsgaard, et al.
Frontiers in Bioinformatics|April 11, 2024
A systematic evaluation of state-of-the-art deconvolution methods in spatial transcriptomics: insights from cardiovascular disease and chronic kidney diseaseAlban Obel Slabowska, Charles Pyke, Henning Hvid, et al.
Pageof 3