Xie Yiluo

Biomedical Scientist & Research Innovator
Xuzhou, CN.

About

Highly accomplished and innovative biomedical scientist with a strong foundation in multi-omics analysis, machine learning, and deep learning applications for clinical research. Proven ability to lead complex scientific projects, evidenced by multiple first-author SCI publications in high-impact journals (Q1/Q2 IF up to 6.0) and over 15 national/provincial awards. Adept at translating complex data into actionable insights, driving advancements in lung adenocarcinoma prognosis and immunotherapy.

Education

Bengbu Medical University
Bengbu, Anhui, China

Bachelor of Medicine

Publications

Integration of single cell and bulk transcriptomes identifies T cell stress subtypes in LUAD
Molecular characterization and prognostic modeling associated with M2-like tumor-associated macrophages in breast cancer: revealing the immunosuppressive role of DLG3
Integration of single-cell transcriptomics and bulk transcriptomics to explore prognostic and immunotherapeutic characteristics of nucleotide metabolism in lung adenocarcinoma
Network pharmacology combined with molecular docking and experimental validation of the mechanism of action of columbianetin acetate in the treatment of ovarian cancer
Development of a novel centrosome-related risk signature to predict prognosis and treatment response in lung adenocarcinoma
Identification of a novel immunogenic death-associated model for predicting the immune microenvironment in lung adenocarcinoma from single-cell and Bulk transcriptomes
Identification and validation of tryptophan-related gene signatures to predict prognosis and immunotherapy response in lung adenocarcinoma reveals a critical role for PTTG1
Comprehensive bioinformatics analysis of malignant transformation and potential therapeutic possibility of lung adenocarcinoma after lipopolysaccharide induction
Copper-binding protein modelling by single-cell transcriptome and Bulk transcriptome to predict overall survival in lung adenocarcinoma patients
Triglyceride-glucose indices predict all-cause mortality after stroke in NHANES 1999-2018

Published by

Peer-Reviewed Scientific Journal (SCI Q1, IF: 4.5)

Summary

Co-corresponding author publication analyzing NHANES data to predict all-cause mortality after stroke using triglyceride-glucose indices, demonstrating significant epidemiological insight.

Integration of the bulk transcriptome and single-cell transcriptome reveals efferocytosis features in lung adenocarcinoma prognosis and immunotherapy by combining deep learning

Published by

Peer-Reviewed Scientific Journal (SCI Q1, IF: 6.0)

Summary

First author publication leveraging deep learning with bulk and single-cell transcriptomics to uncover efferocytosis features in lung adenocarcinoma, achieving a high impact factor.

Integrating multi-omics and machine learning survival frameworks to build a prognostic model based on immune function and cell death patterns in a lung adenocarcinoma cohort

Published by

Peer-Reviewed Scientific Journal (SCI Q1, IF: 5.9)

Summary

First author publication developing a robust prognostic model for lung adenocarcinoma by integrating multi-omics and machine learning, with high impact factor.

Identification of T-cell exhaustion-related genes and prediction of their immunotherapeutic role in lung adenocarcinoma

Published by

Peer-Reviewed Scientific Journal (SCI Q2, IF: 3.3)

Summary

Co-first author publication identifying T-cell exhaustion-related genes and predicting their immunotherapeutic role in lung adenocarcinoma, advancing immunotherapy strategies.

Multi-omics identification of GPCR gene features in lung adenocarcinoma based on multiple machine learning combinations

Published by

Peer-Reviewed Scientific Journal (SCI Q2, IF: 3.3)

Summary

First author publication utilizing multi-omics data and machine learning to identify GPCR gene features, significantly contributing to lung adenocarcinoma research.

Skills

Research & Data Analysis

Multi-omics, Machine Learning, Deep Learning, Statistical Modeling, Bioinformatics, Genomics, Transcriptomics, Clinical Research, Experimental Design, Data Interpretation, Scientific Writing.

Medical & Laboratory Expertise

Anesthesiology, Pathology, Internal Medicine, Biochemistry, Physiology, Oncology, Immunology, Molecular Biology, Laboratory Techniques.

Leadership & Project Management

Team Leadership, Project Management, Mentorship, Cross-functional Collaboration, Strategic Planning, Problem-Solving, Innovation.

Software & Tools

Statistical Software, Data Visualization Tools, Programming (implied by machine/deep learning).