Yaozhong Liu
Biochemistry, Genetics and Molecular Biology · University of Michigan
Publications
65
Citations
1,304
Est. group size
—
Recurring co-author estimate
Active years
22
Publishing since 2004
Typically publishes in teams of ~5 · 38% small-team papers (≤3 authors) · across 26 venues
- RNA sequencing identifies MAP1A and PTTG1 as predictive genes of aging CD264+ human mesenchymal stem cells at an early passage
Cytotechnology · 2025
- Global burden of diseases attributable to childhood sexual abuse and bullying: findings from 1990 to 2019 and predictions to 2035
Social Psychiatry and Psychiatric Epidemiology · 2025
- Global burden of diseases attributable to intimate partner violence: findings from the Global Burden of Disease Study 2019
Social Psychiatry and Psychiatric Epidemiology · 2024
- Perceived overqualification and knowledge sharing: The role of organizational identity and psychological entitlement
Work · 2024
- A novel 7 RNA-based signature for prediction of prognosis and therapeutic responses of wild-type BRAF cutaneous melanoma
Biological Procedures Online · 2022
- A Novel 7 RNA-Based Signature for Prediction of Prognosis and Therapeutic Responses of Wild-Type BRAF Cutaneous Melanoma
Research Square · 2022
- [Retracted] Exosomal miR‐27b‐3p Derived from Hypoxic Cardiac Microvascular Endothelial Cells Alleviates Rat Myocardial Ischemia/Reperfusion Injury through Inhibiting Oxidative Stress‐Induced Pyroptosis via Foxo1/GSDMD Signaling
Oxidative Medicine and Cellular Longevity · 2022
- Longer Leukocyte Telomere Length Increases the Risk of Atrial Fibrillation: A Mendelian Randomization Study
Aging and Disease · 2022
- Education and Atrial Fibrillation: Mendelian Randomization Study
Global Heart · 2022
- The impact of social comparison and (un)fairness on upstream indirect reciprocity: Evidence from ERP
Neuropsychologia · 2022
- What Causes Delay Asymmetry: A Large-scale One-way Delay Measurement and Empirical Study
GLOBECOM 2022 - 2022 IEEE Global Communications Conference · 2022
- Additional file 2 of Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease
Figshare · 2021
- Additional file 3 of Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease
Open MIND · 2021
- NAD+ and cardiovascular diseases
Clinica Chimica Acta · 2021
- Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease
BMC Cardiovascular Disorders · 2021
- Psychology×5
- Clinica Chimica Acta×3
- Research Square×3
- Cardiovascular Drugs and Therapy×2
- BMC Cardiovascular Disorders×2
- Vikram A. Bagchi
Biochemistry, Genetics and Molecular Biology · University of Michigan
- Matthew Flickinger
Biochemistry, Genetics and Molecular Biology · University of Michigan
- Jonathon LeFaive
Biochemistry, Genetics and Molecular Biology · University of Michigan
- Sebastian Zöllner
Biochemistry, Genetics and Molecular Biology · University of Michigan
- Goo Jun
Biochemistry, Genetics and Molecular Biology · University of Michigan
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 25, 2026.
Claim or correct this profile