Ming D. Li - Infectious Diseases

Author Information

Ming D. Li is a distinguished researcher affiliated with the State Key Laboratory for Diagnosis and Treatment of Infectious Diseases at the Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases. This laboratory is part of The First Affiliated Hospital of Zhejiang University School of Medicine, located in Hangzhou, China. Ming D. Li's work primarily focuses on understanding the complex interactions between infectious diseases and various biological systems.

Research Contributions

Ming D. Li has made significant contributions to the fields of epigenetics, microbiota, and cancer research. In 2021 alone, he has published numerous papers addressing critical issues such as the impact of cigarette smoke on gut microbiota, the identification of biomarkers for major depressive disorder using machine learning, and the epigenetic landscape of immune-related diseases due to tobacco smoking. His research is marked by a multidisciplinary approach, combining genomics, bioinformatics, and clinical studies to unravel the molecular mechanisms underlying various health conditions.

Aliases

Ming D. Li is also referred to by several variations of his name, including Ming D Li and Ming Li. These aliases are used interchangeably in different publications and databases.

Publication and Citation Metrics

Metric	Value
Total Citation Count	8017
h-index	48
Total Paper Count	199

Publications:

Effect of Cigarette Smoke on Gut Microbiota: State of Knowledge

DOI: 10.3389/fphys.2021.673341

Year: 2021

Roles For N-Terminal Extracellular Domains Of Nicotinic Acetylcholine Receptor (Nachr) Ã”Â23 Subunits In Enhanced Functional Expression Of Mouse Ã”Â±6Ã”Â22Ã”Â23- And Ã”Â±6Ã”Â24Ã”Â23-Nachrs

DOI:

Year: 2021

Integrative Analysis of Epigenome and Transcriptome Data Reveals Aberrantly Methylated Promoters and Enhancers in Hepatocellular Carcinoma

DOI: 10.3389/fonc.2021.769390

Year: 2021

Identification of Diagnostic Markers for Major Depressive Disorder Using Machine Learning Methods

DOI: 10.3389/fnins.2021.645998

Year: 2021

DNA evolution depends on differential methylation patterns in rat speciation

DOI: 10.22541/AU.162256010.03393620/V1

Year: 2021

Correlation Between Prognostic Biomarker SLC1A5 and Immune Infiltrates in Various Types of Cancers Including Hepatocellular Carcinoma

DOI: 10.3389/fonc.2021.608641

Year: 2021

Genome-wide methylation and expression analyses reveal the epigenetic landscape of immune-related diseases for tobacco smoking

DOI: 10.1186/s13148-021-01208-0

Year: 2021

Prediction of repeated-dose intravenous ketamine response in major depressive disorder using the GWAS-based machine learning approach.

DOI: 10.1016/j.jpsychires.2021.04.014

Year: 2021

Landscape analysis of lncRNAs shows that DDX11-AS1 promotes cell-cycle progression in liver cancer through the PARP1/p53 axis.

DOI: 10.1016/j.canlet.2021.08.001

Year: 2021

Altered Intestinal Microbiomes and Lipid Metabolism in Patients With Chronic Disorders of Consciousness

DOI: 10.21203/rs.3.rs-824411/v1

Year: 2021

How Does NAT Work?

What Preventive Measures are Available?

What are the Common Imaging Tests?

When are Quarantine and Isolation Used?

How are HAIs Diagnosed?

How are Infectious Diseases Treated?

What is the Importance of International Collaboration?

What are the Benefits of Gene Therapy and Immunotherapy?

How Do Decongestants Work?

What are Some Natural Alternatives to Chemical Insect Repellents?

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