Author

Jian Zhang

SUNY Downstate Health Sciences UniversityORCID 0000-0003-3838-7389Unclaimed ORCID profile · follow to get notified of new preprints

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Jian Zhang13 papers · Southern University of Science and Technology

Biology Disciplines

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Developmental Biology· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

Ashwini Kumar PandeyiD· 2 shared Bernice Porjesz AiD· 2 shared Chella KamarajaniD· 2 shared David Balin ChorlianiD· 2 shared Jacquelyn Leigh MeyersiD· 2 shared Sivan KinreichiD· 2 shared Alison K. MerikangasiD· 1 shared Andrey P. AnokhiniD· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersDevelopmental Biology

Ashwini Kumar PandeyORCID

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2 papers

Recent·Most cited

Developmental BiologybioRxivPreprintMar 13, 2024

Non-linear development of EEG coherence in adolescents and young adults shown by the analysis of neurophysiological trajectories and their covariance

David Balin Chorlian, Chella Kamarajan, Jacquelyn Leigh Meyers…·Bernice Porjesz A

The paper analyzes EEG coherence development in adolescents and young adults using tensorial analysis of covariance matrices, revealing non-linear patterns and sex differences in neural connectivity.

2 citations

humanelectronic health records

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NeurosciencebioRxivPreprintDec 30, 2022

Predicting alcohol-related memory problems in older adults: A machine learning study with multi-domain features

Chella Kamarajan, Ashwini Kumar Pandey, David Balin Chorlian…·Bernice Porjesz A

This study uses machine learning to predict alcohol-related memory problems in older adults by integrating multi-domain features including brain connectivity, polygenic risk, and lifestyle factors.

2 citations

humanmachine learning (classical)

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