Welcome to the Cheng Lab

Computational Biology and Bioinformatics
Baylor College of Medicine

Overview

We are dedicated to understanding the molecular mechanisms underlying human diseases, with a particular emphasis on cancer. By leveraging advanced computational techniques, we collaborate closely with cancer researchers and clinicians to enhance the prevention, diagnosis, and treatment of cancer. Our interdisciplinary approach aims to translate data-driven insights into tangible improvements in patient care.

Research Interests

Computational Algorithms and Frameworks

To better understand the mechanisms and improve treatment efficacy of human diseases such as cancer, diverse type of data have been generated including genomics, transcriptomic, epigenetics, biomedical images, and clinical records. We are interested in developing new Computational algorithms and frameworks to process, analyze, and integrate these biomedical data.

Machine Learning

Machine learning, especially deep-learning have been widely applied in the field of biological and biomedical researches and demonstrated high performance. We are interested in developed new deep-learning based models to more effective utilize biomedical data for improving personalized treatment of cancer.

Cancer Biomarkers

Gene signatures and biomarkers have been widely used to stratify cancer patients based on their prognosis (prognostic biomarkers) and response to therapeutic treatments. We are interested in developed prognostic and predictive biomarkers in directing the treatment of cancer patients in a personalized manner.

Clonal hematopoiesis

Clonal hematopoiesis (CH) is a condition that occurs when a single blood cell line develops a genetic mutation and contributes to the formation of a distinct population of blood cells. CH has been reported to increase the risk of a variety of human diseases such as hematological malignancy, cardiovascular diseases. We are interested in the association between the presence of CH mutations and the risk of solid cancers.