Author

Mohsen Farahpour

University of BirjandORCID 0000-0002-6908-2732Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Assay:multiome· 1 Assay:scRNA-seq· 1 Assay:spatial transcriptomics· 1 Approach:statistical model· 1

Frequent Co-Authors

A. Ali HeydariiD· 1 shared Afshin DerakhshaniiD· 1 shared Amirhossein SahebkariD· 1 shared Hossein SafarpouriD· 1 shared Mohammad GhasemiGoliD· 1 shared Nafiseh ErfanianiD· 1 shared Pablo Iáñez PicazoiD· 1 shared Saeed NasseriiD· 1 shared

Activity by Year

2021-2021 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperBioinformatics

A. Ali HeydariORCID

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1 paper

Recent·Most cited

Deep learning applications in single-cell omics data analysis

Nafiseh Erfanian, A. Ali Heydari, Pablo Iáñez Picazo, Afshin Derakhshani, Mohammad GhasemiGol, Mohsen Farahpour, Saeed Nasseri, Hossein Safarpour, Amirhossein Sahebkar

This paper reviews deep learning applications in single-cell omics, finding that while promising, DL models still lack biological interpretability and have not yet solved major challenges in the field.

bioRxiv · Nov 26, 2021 · PreprintBioinformatics