Single-cell foundation models identify shared and divergent transcriptomic signatures of aging across invertebrates and mammals
Mohammad Aman Ullah Al Amin, Khoi Le, Hong HQ Qin
bioRxiv · Jul 27, 2026 · PreprintGenomics
Author
Hong HQ Qin
University of Tennessee at ChattanoogaORCID 0000-0002-1060-6722Unclaimed ORCID profile · follow to get notified of new preprints
Biology Disciplines
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2020-2026 · peak 2/yrCo-Author Collaboration Network
8 top collaborators · 16 mutual co-author linksFocal author (center)Selected co-authorORCID co-authorUnlinked name
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Recent·Most cited
Protein interaction probability landscapes for yeast replicative aging
Hao‐Bo Guo, Mehran Ghafari, Weiwei Dang, Hong HQ Qin
The paper introduces a probability landscape approach to analyze gene network changes during yeast replicative aging, revealing distinct roles for essential and hub proteins.
Scientific Reports · Mar 30, 2021Peer-reviewedSystems Biology
Complementary Performances of Convolutional and Capsule Neural Networks on Classifying Microfluidic Images of Dividing Yeast Cells
Mehran Ghafari, Justin Clark, Hao‐Bo Guo, Ruofan Yu, Yu Sun, Weiwei Dang, Hong HQ Qin
This study compares convolutional and capsule neural networks for classifying microfluidic images of dividing yeast cells, finding convolutional networks more accurate overall while capsule networks excel at specific categories.
PLoS ONE · Mar 17, 2021Peer-reviewedBioinformatics