Research Questions:
How do comorbidities, biological behaviors, lifestyle, environmental factors, plasma metabolites, and genetics interact in the occurrence and progression of skin diseases and sexually transmitted diseases (STDs)?
Which key biomarkers and pathways in the molecular mechanisms of skin diseases and STDs can be used for early screening, diagnosis, and treatment?
Research Objectives:
Integrate genetic, environmental, lifestyle, and biomarker data to create a multifactorial risk assessment model for skin diseases and STDs.
Identify key biological mechanisms and risk factors by exploring large-scale biological data (e.g., genomics, plasma metabolites, and epigenetics) to understand the molecular mechanisms of these diseases.
Use data mining and machine learning techniques to identify biomarkers linked to disease onset and prognosis, providing precise evidence for personalized prevention and treatment.
Scientific Basis for the Research:
Multifactorial Interaction: Skin diseases and STDs are influenced by multiple factors, including genetics, environment, lifestyle, and biomarkers. Integrating and analyzing these factors will help reveal their complex relationships.
Clinical Data Analysis and Statistical Methods: This study will use methods like logistic regression and Cox regression to assess how different factors impact the risk and prognosis of skin diseases and STDs. These methods help identify key factors and prognostic markers.
Bioinformatics and Data Mining: By combining bioinformatics techniques (e.g., genomics, metabolomics) with machine learning and GWAS analysis, this study will explore the key factors affecting the development of skin diseases and STDs, offering insights into their molecular mechanisms and supporting early screening and personalized treatment.