Functional Analysis of Transcriptional Response During Cutaneous Wound Healing
Monday, May 16, 2016
2:00 PM-4:00 PM
BIOMED PhD Research Proposal
Title:
Functional Analysis of Transcriptional Response During Cutaneous Wound Healing
Speaker:
Sina Nassiri, PhD Candidate, School of Biomedical Engineering, Science and Health Systems
Advisors:
Kambiz Pourrezaei, PhD, Professor, School of Biomedical Engineering, Science and Health Systems, and Issa Zakeri, PhD, Professor, Dornsife School of Public Health
Abstract:
Wound healing is an extremely intricate and highly dynamic process. High throughput molecular screening technologies such as DNA microarrays hold great potential in enhancing our understanding of complex biological processes, and thus have been extensively exploited in wound healing research.
Previous attempts at analyzing transcriptional response during cutaneous wound healing have been limited to conventional statistical methods that are oblivious to the temporal aspect of time-course data. Functional data analysis (FDA) is a branch of statistical methods that treats the entire sequence of time-course data as a single functional entity rather than a set of discrete measurements. We hypothesize that by directly utilizing the time structure of data and borrowing information across all time points, FDA can more accurately elucidate transcriptional response during wound healing. To test this hypothesis, we propose a comprehensive functional approach to analyze time-course microarray data from two previously published studies; one on physiologic healing of human skin and the other on impaired healing in a murine model of diabetes. We will thoroughly investigate the dynamic of expression profiles both from a single-gene perspective using differentially expressed genes, and from a system-level perspective using the architecture of gene coexpression and regulatory networks.
Collectively, building upon the framework of functional data analysis, the proposed research aims to enhance the existing knowledge on transcriptional regulation during physiologic wound healing and shed light on the mechanisms of impaired healing in pathophysiologic conditions. Finally, our findings may lead to identification of novel candidate biomarkers and potential targets with implications in diagnostic and therapeutic applications.
Contact Information
Ken Barbee
215-895-1335
barbee@drexel.edu