Author

Akash Anand

Nference (India)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Organism:human· 2 Assay:scRNA-seq· 2 Approach:deep learning· 1 Approach:statistical model· 1

Frequent Co-Authors

Abhinav GargiD· 2 shared AJ VenkatakrishnaniD· 2 shared David ZemmouriD· 2 shared Enrique Garcia-RiveraiD· 2 shared Rakesh D. BarveiD· 2 shared Ramakrishna Chilaka· 2 shared Venky SoundararajaniD· 2 shared Akhil Kasaraneni· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 43 mutual co-author links

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2 shared papersGenomics

Abhinav GargORCID

Mutual co-authors in cluster

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2 papers

Recent·Most cited

A literature-derived knowledge graph augments the interpretation of single cell RNA-seq datasets

Deeksha Doddahonnaiah, Patrick J. Lenehan, Travis K. Hughes, David Zemmour, Enrique Garcia-Rivera, AJ Venkatakrishnan, Ramakrishna Chilaka, Apoorv Khare, Akhil Kasaraneni, Abhinav Garg, Akash Anand, Rakesh D. Barve, Viswanathan Thiagarajan, Venky Soundararajan

This study uses a literature-derived knowledge graph to improve scRNA-seq annotation by leveraging gene-cell type associations from biomedical texts.

Genes · Jun 10, 2021Peer-reviewedGenomics

Knowledge synthesis from 100 million biomedical documents augments the deep expression profiling of coronavirus receptors

AJ Venkatakrishnan, Arjun Puranik, Akash Anand, David Zemmour, Xiang Yao, Xiaoying Wu, Ramakrishna Chilaka, Dariusz K. Murakowski, Kristopher Standish, Bharathwaj Raghunathan, Tyler Wagner, Enrique Garcia-Rivera, Hugo Solomon, Abhinav Garg, Rakesh D. Barve, , Venky Soundararajan

The paper uses a data science platform to integrate biomedical text and single-cell RNA-seq data to identify new SARS-CoV-2 receptor expression patterns and potential infection targets.

eLife · May 28, 2020Peer-reviewedGenomics