Author

Shanshan Song

Johns Hopkins UniversityORCID 0000-0002-7597-2117Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Shanshan Song1 paper · Hammersmith Hospital

Biology Disciplines

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Bioinformatics· 1 Cell Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:dimensionality reduction· 1 Assay:electronic health records· 1 Approach:experimental assay· 1

Frequent Co-Authors

Aleksandra BabichevaiD· 1 shared Amin Izadi· 1 shared Ayako MakinoiD· 1 shared Christina M. PabelickiD· 1 shared Cole Paquin· 1 shared Harold P. LehmanniD· 1 shared Ibrahim Shehata ElmadbouhiD· 1 shared Jason X.‐J. YuaniD· 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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1 shared paperCell Biology

Aleksandra BabichevaORCID

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2 papers

Recent·Most cited

Store-operated Ca2+ entry is involved in endothelium-to-mesenchymal transition in lung vascular endothelial cells

Aleksandra Babicheva, Ibrahim Shehata Elmadbouh, Shanshan Song, Michael A Thompson, Ryan Powers, Pritesh Jain, Amin Izadi, Jiyuan Chen, Lauren Yung, Sophia Parmisano, Cole Paquin, Wei‐Ting Wang, Yuqin Chen, Ting Wang, Mona Alotaibi, , Jason X.‐J. Yuan

This study shows that TGF-β1-induced endothelial-to-mesenchymal transition in human lung vascular endothelial cells is Ca²⁺-dependent through store-operated Ca²⁺ entry via STIM1/Orai1 channels.

American Journal of Physiology-Lung Cellular and Molecular Physiology · May 7, 2025Peer-reviewedCell Biology

Machine Learning to Summarize and Provide Context for Sleep and Eating Schedules.

Tianyi Chen, Yiwen Chen, Jingyi Gao, Peiheng Gao, Jeong Hyun Moon, Jing-yi Ren, Ranran Zhu, Shanshan Song, Jeanne M. Clark, Wendy L. Bennett, Harold P. Lehmann, Tamás Budavári, Thomas B. Woolf

This study uses machine learning to analyze sleep and eating schedules from 500 participants, proposing a framework to classify chronotypes and assess circadian misalignment for health guidance.

bioRxiv · Dec 31, 2020 · PreprintBioinformatics