Author

Tianyi Ling

University Health NetworkORCID 0009-0007-4410-3043Unclaimed 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:cell type annotation· 2 Approach:experimental assay· 2 Organism:human· 2 Assay:bulk RNA-seq· 1 Research Focus:cancer & tumor microenvironment· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Courtney L. JonesiD· 2 shared Amanda C. WintersiD· 1 shared Anagha Inguva ShethiD· 1 shared Anastasia N. TikhonovaiD· 1 shared Anna E. KrugiD· 1 shared Austin E. GilleniD· 1 shared Blagoj RistevskiiD· 1 shared Brett M. StevensiD· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersCancer Biology

Courtney L. JonesORCID

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3 papers

Recent·Most cited

Cancer BiologybioRxivPreprintSep 2, 2025

Surface proteomics reveals arginine metabolism as a vulnerability in high grade serous ovarian cancer

Meinusha Govindarajan, Matthew Waas, Salvador Meija-Guerrero…·Thomas Kislinger

This study identifies SLC7A1 and arginine metabolism as a therapeutic vulnerability in high-grade serous ovarian cancer through surface proteomics and functional analysis.

DOI 10.1101/2025.09.02.673726

humanproteomics

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Cancer BiologyCancer DiscoveryPeer-reviewedMay 23, 2024

Targeting Acute Myeloid Leukemia Stem Cells Through Perturbation of Mitochondrial Calcium

Anagha Inguva Sheth, Krysta L. Engel, Hunter Tolison…·Craig T. Jordan

This study identifies mitochondrial calcium utilization as a metabolic requirement of venetoclax-resistant acute myeloid leukemia stem cells and shows that targeting mitochondrial calcium uptake can eradicate these cells.

61 citationstop 1%

humanbulk RNA-seq

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BioinformaticsPLoS Computational BiologyPeer-reviewedJul 20, 2020

A Novel Riboswitch Classification based on Imbalanced Sequences achieved by Machine Learning

Solomon Shiferaw Beyene, Tianyi Ling, Blagoj Ristevski, Ming Chen

The paper addresses riboswitch classification challenges using machine learning on imbalanced datasets, showing improved performance with balanced data and identifying biologically relevant k-mers.

5 citations

protein sequencemachine learning (classical)

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