San Francisco Bay Area Chapter of
American Statistical Association
Monthly Seminar
Co-sponsored by DahShu (www.dahshu.org)
|
Title: |
Big-Data
Analysis Points Toward a New Cancer Therapeutic Discovery Approach |
|
Abstract: |
Rapidly
decreasing costs of molecular measurement technologies not only enable
profiling of disease sample molecular features at different levels (e.g., transcriptome, proteome, metabolome),
but also enable measuring of cellular signatures of individual drugs in
clinically relevant models. Exploring systematic approaches to find drugs for
diseases through various molecular features is critically important in the
discovery of new therapeutics. We propose a systems-approach to identifying
drugs that reverse the molecular state of a disease. Using this approach, we
have identified drug candidates for hepatocellular carcinoma and Ewing's
sarcoma. Our recent pan-cancer analysis indicates that the ability to reverse
cancer gene expression correlates to drug efficacy. In this talk, I will
present our two recent papers published in Gastroenterology and Nature
Communications to demonstrate this systems approach. I will also share how a
data scientist led the discovery of new therapeutic candidates for liver
cancer. |
|
Time: |
4:30 – 6:00 pm, September 26, 2017 (4:30-5:00 social networking, 5:00-6:00 seminar) |
|
Location: |
UCSF Mission Hall: Global Health & Clinical Sciences
Building 550
16th Street, Room 1406, San Francisco, CA 94158 Nearest
parking garage ($8/2hrs): UCSF
Mission Bay Campus – 1630 Third Street Garage 1630
3rd St., San Francisco, CA 94158 |
|
Registration: |
Register online at |
|
Speaker: |
Dr. Bin Chen Assistant Professor, Institute for Computational Health
Sciences at UCSF Speaker
bio: Dr. Chen is an assistant professor in the Institute for Computational
Health Sciences at UCSF. He is also the founding member of DahShu, a non-profit organization to promote research and
education in data sciences. He trained as a chemist in college, and worked as
a software engineer before attending graduate school. In graduate school, he trained as a chem/bioinformatician; and later had worked as a computational
scientist at Novartis, Pfizer, and Merck. He received his PhD in informatics
at Indiana University, Bloomington and then pursued his postdoctoral training
in Dr. Atul ButteĠs lab at Stanford University.
His lab at UCSF is currently supported by the NIH
Common Fund, NCI, NCATS and LĠOreal. His work in drug discovery is
recently featured in UCSF News, STAT, GEN, GenomeWeb
and KCBS. More information is available on his lab website (http://binchenlab.org/).
|
