Geisel Faculty Candidate Special Seminar

Speaker: Alvin Makohon-Moore, Ph.D., Postdoctoral Researcher, Memorial Sloan Kettering Cancer Center

February 3, 2020
12 pm - 1 pm
Location
DHMC, Auditorium H
Sponsored by
Geisel School of Medicine
Audience
Public
More information
Biomedical Data Science Department

Please join us for an NCCC and Biomedical Data Science Bioinformatics and Computational 

Oncology Faculty Candidate Seminar with Alvin Makohon-Moore, Ph.D., Postdoctoral Researcher,

Memorial Sloan Kettering Cancer Center on Monday, February 3 at 12:00 p.m., Auditorium H, DHMC. 

 

 

Talk title: “Evolutionary analysis and genetic heterogeneity of human cancers”

 

Hosted by: Brock Christensen, Ph.D.

 

 

Light refreshments will be provided on a first-come, first-served basis. 

 

Talk Summary 

Cancer results from an evolutionary process involving cellular variation and dynamic 

microenvironments. In this seminar, I will discuss the evolution of early and late stage cancers, 

with a focus on genetic heterogeneity. I will also present my own work using next generation 

sequencing and phylogenetics of human tumors. My research aims to define aspects of cancer 

evolution that lead to clinical endpoints and therapeutic opportunities.

 

Biography

Alvin Makohon-Moore is a Research Scholar in the Human Oncology and Pathogenesis Program 

at Memorial Sloan Kettering Cancer Center. He obtained his Ph.D. in Pathobiology from Johns 

Hopkins University. His research focuses on evolutionary dynamics in cancer. Currently, he is 

working on applying phylogenetic and experimental approaches to identify mechanisms by 

which cancer evolves.

 

 

Please also mark your calendar for upcoming NCCC/BMDS Bioinformatics and Computational 

Oncology faculty candidate seminars: 


Dr. Siming Zhao - Wed., 2/12: Aud. H @ 11:00am

Postdoctoral Scholar, Computational Methods Development in Cancer Genomics 

University of Chicago, Department of Human Genetics
 

 

 

Location
DHMC, Auditorium H
Sponsored by
Geisel School of Medicine
Audience
Public
More information
Biomedical Data Science Department