Author

Krishna G. Kumar

Indian Institute of Chemical BiologyORCID 0000-0001-5986-7248Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:database / resource· 2 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2 Organism:bacteria (other)· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1

Frequent Co-Authors

Saikat ChakrabartiiD· 3 shared Abhijit ChakrabortyiD· 1 shared Anakshi GayeniD· 1 shared Avik MukherjeeiD· 1 shared Chandrama MukherjeeiD· 1 shared Nupur BiswasiD· 1 shared Raisa Bera· 1 shared Sarpita Bose· 1 shared

Activity by Year

2020-2024 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 17 mutual co-author links

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3 shared papersBioinformatics

Saikat ChakrabartiORCID

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3 papers

Recent·Most cited

Molecular BiologyJournal of Cell SciencePeer-reviewedJun 1, 2024

mRNA capping enzyme exports to cytoplasm, localizes to stress granules and maintains cap homeostasis of the target mRNAs

Anakshi Gayen, Avik Mukherjee, Krishna G. Kumar…·Chandrama Mukherjee

The paper investigates the role of cytoplasmic capping enzyme (cCE) in maintaining cap homeostasis of target mRNAs during stress and recovery.

13 citations

multiomeexperimental assay

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BioinformaticsFrontiers in GeneticsPeer-reviewedDec 8, 2020

Analysis of Pan-Omics Data in Human Interactome Network (APODHIN)

Nupur Biswas, Krishna G. Kumar, Sarpita Bose…·Saikat Chakrabarti

APODHIN integrates multi-omics data into a human interactome network to identify key molecular players and their interconnections in cancer, providing tools for analysis and visualization.

17 citations

humanproteomics

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BioinformaticsRNA BiologyPeer-reviewedOct 25, 2020

PresRAT: A server for identification of bacterial small-RNA sequences and their targets with probable binding region.

Krishna G. Kumar, Abhijit Chakraborty, Saikat Chakrabarti

PresRAT identifies bacterial small-RNA sequences and their targets, predicting 60,518 sRNAs and 2447 targets across 54 and 13 bacterial genomes, respectively.

18 citations

bacteria (other)statistical model

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