Author

Tina Kapur

Brigham and Women's HospitalORCID 0000-0003-3646-9508Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:metabolomics· 2 Organism:mouse· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:dimensionality reduction· 1 Organism:human· 1

Frequent Co-Authors

Elizabeth C. Randall· 2 shared Jann Nagina SarkariaiD· 2 shared Jeffrey N. AgariD· 2 shared Nathalie Y.R. AgariD· 2 shared Walid M. AbdelmoulaiD· 2 shared William M. WellsiD· 2 shared Begona G. C. Lopez· 1 shared Forest M. WhiteiD· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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2 shared papersBioinformatics

Elizabeth C. Randall

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2 papers

Recent·Most cited

BioinformaticsBioinformaticsPeer-reviewedJan 13, 2022

massNet: integrated processing and classification of spatially resolved mass spectrometry data using deep learning for rapid tumor delineation

Walid M. Abdelmoula, Sylwia A. Stopka, Elizabeth C. Randall…·Nathalie Y.R. Agar

massNet uses deep learning to classify spatial mass spectrometry data without preprocessing, achieving higher accuracy and faster speed than classical methods for tumor delineation in mouse brain tissue.

35 citations

mousemetabolomics

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BioinformaticsNature CommunicationsPeer-reviewedSep 20, 2021

msiPL: Non-linear Manifold and Peak Learning of Mass Spectrometry Imaging Data Using Artificial Neural Networks

Walid M. Abdelmoula, Begona G. C. Lopez, Elizabeth C. Randall…·Nathalie Y.R. Agar

The paper introduces msiPL, a deep learning model for analyzing MSI data, enabling efficient non-linear visualization and identification of biologically relevant patterns.

108 citationstop 1%

humanmouse

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