Sales Ended

Big-Data Analysis Points Toward A New Cancer Therapeutic Discovery Approach

Event Information

Share this event

Date and Time

Location

Location

UCSF Mission Hall: Global Health & Clinical Sciences Building

550 16th Street

Room 1406

San Francisco, CA 94158

View Map

Event description

Description

This seminar is co-organized and sponsored by San Francisco bay area chapter of American Statistical Association (SFASA; www.sfasa.org) and DahShu (www.dahshu.org).


Please specify online or in-person during registration.


Online meeting will start at 5pm with seminar presentation. Online registrants will receive the Webex link and dial-in information on September 25th (the day before the seminar).


In-person meeting schedule:

4:30- 5pm - social networking

5-6pm - seminar presentation and Q&A


Nearest parking garage ($8/2hrs):

UCSF Mission Bay Campus - 1630 Third Street Garage
1630 3rd St, San Francisco, CA 94158


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 identify 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.


Speaker Bio:

Dr. Bin Chen is an assistant professor in the Institute for Computational Health Sciences at University of California, San Francisco. Dr. Chen is also the founding member of DahShu, a non-profit organization to promote research and education in data sciences. Dr. Chen trained as a chemist in college, worked as a software engineer before graduate school, trained as a chem/bioinformatician in graduate school, 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 Butte’s lab at Stanford University. His lab is currently supported by the NIH Common Fund, NCI, NCATS and L’Oreal. His work in drug discovery is recently featured in UCSF News, STAT, GEN, GenomeWeb and KCBS. More info is available on his lab website (http://binchenlab.org/).


Bin Chen Profile

Share with friends

Date and Time

Location

UCSF Mission Hall: Global Health & Clinical Sciences Building

550 16th Street

Room 1406

San Francisco, CA 94158

View Map

Save This Event

Event Saved