Biological processes are precisely regulated by TFs, miRNAs and other regulators. We aim to combine data from different sources, e.g, TF binding data (ChIP-seq and ChIP-chip), gene expression data (microarray and RNA-seq), with computational techniques to construct the integrated regulatory networks underlying cancer and other diseases.
TFs are collaborated with each other during transcriptional regulation. We aim to infer the combinatorial interactions among different TFs. We also aim to investigate how TF-TF interactions vary in different cell types/conditions, and how these interactions evolve in different related species.
Biological processes are also under intensive regulation at the epigenomic level. We aim to understand the functions of DNA methylation and histone modifications in these processes and to provide new insight on the relationship between epigenetic events and human diseases, e.g. tumor development and progression.
Clinical Outcome Prediction
Strictly speaking, each case of cancer should be regarded as a specific disease, but cancer of the same type can often be categorized into different sub-types. We aim to develop methods that integrate different data sources (e.g. expression data, somatic mutation profile, epigenetic data, etc) to classify tumor. We also aim to predict the clinical outcome of patients based on the molecular features of tumors and their genotype.
Join Our Lab
Post-doc positions: The Cheng Lab is searching for highly motivated and talented post-doc candidates to work on Bioinformatics and Computational Biology. The candidate should have experience in processing and analyzing next-generation sequencing data. Previous experience in both Bioinformatics and Cancer Systems Biology are desirable. View job posting.
Graduate students: The Cheng Lab welcomes interested Ph.D. and M.D. students already admitted to the Graduate Programs at Baylor College of Medicine. See our graduate schools admission page. Interested students should contact firstname.lastname@example.org about potential rotation and thesis projects.
Undergraduate students: The Cheng Lab has openings for motivated undergraduates from different scientific disciplines (biology, statistics, computer science, etc) who are interested in working in bioinformatics and genomics. Interested students should email email@example.com.
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