The long-term goal of Dr. Bin Chen's lab is to develop computational methods and tools to discover new or better therapeutic candidates for cancers through collaborating with bench scientists and clinicians. Rapidly decreasing costs of molecular measurement technologies not only enable profiling of disease sample molecular features (e.g., transcriptome, proteome, metabolome) at different levels (e.g., tissues, single cells), but also enable measuring of cellular signatures of individual drugs in clinically relevant models. Our lab is interested in leveraging these data and artificial intelligence to connect different components (patients, tissues, in vitro models and in vivo models) in translational research ( B. Chen, 2016). We currently focus on liver cancer, breast cancer and Ewing's sarcoma. We are hiring!
Bin Chen is invited to speak at 2018 Breast Oncology Program Annual Retreat at UCSF
We will present the open cancer therapeutic discovery pipeline at AACR Annual Meeting 2018 in Chicago, Illinois, USA
Bin Chen is invited to speak at 8th Genomics & Big Data Summit in San Diego, CA
Bin Chen is invited to speak at ICSA 2018 Applied Statistics Symposium in New Brunswick, NJ
Bin Chen is invited to speak at JSM 2018 in Vancouver, Canada
Billy submits his manuscript about using deep learning for reference normal tissue selection and Jenny submits her abstract about identifying breast cancer non-responder signatures.Well done.
Bin Chen organizes for the Chinese American Biopharmaceutical Society (CABS) workshop entitled BIG DATA FOR DRUG TARGET DISCOVERY
Bin Chen presents a poster about our drug discovery pipeline at PSB 2018 in The Big Island of Hawaii
We are joining the IDG (Illuminating the Druggable Genome ) Ion-Channel informatics team.
Bin Chen is invited to speak at Global Pharma R&D Informatics Congress 2017 in Lisbon, Portugal
Bin Chen is invited to speak at 2nd Strategic Partnerships for Drug Repurposing Forum in Boston MA
Bin Chen gives a talk for the DahShu Virtual Club and SFASA Monthly Seminar. Download slides and video here.
We are excited to participate the P01 grant entitled "I-SPY2 +: Evolving The I-SPY 2 Trial To Include MRI-Directed, Adaptive Sequential Treatment To Optimize Breast Cancer Outcomes". We will predict drugs to overcome drug resistance in breast cancer. Excited to join I-SPY.
The basal cell carcinoma repositioning work led by the Stanford researchers is accepted in JCI Insight.
We recieve a 2-year R21 ($570K in total) from NCATS to support our liver cancer drug repositioning work.
Our recent big data work is featured in KCBS.
We, together with Butte Lab and Hadley Lab, recieve funds from L'Oreal to discover drugs for hyperpigmentation.
Welcome Reuben Sarwal, an undergraduate student from UC Berkeley, to join us this summer as an intern.
Bin Chen is invited to present at 2017 UCSF Hepatobiliary Cancers Research Symposium
Bin Chen recieves the BD2K K01 Career Development Award (four years, $684,000 in total). He will use this award to develop novel methods for personalized cancer therapy.
Bin Chen is invited to present the work on using big data to combat cancer to UCSF donors at UCSF Cancer Showcase 2017.
our paper on using big data to identify new therapeutics for liver cancer is out ( press release)
Bin Chen gives a talk at AMIA 2017 TBI
Bin Chen is invited to participate the Big Data For Breast Cancer\West Coast Conference organized by Susan G. Komen
Summer student Tanisha Joshi presents her work at Dahshu 2017 Symposium
our paper on using big data to identify new therapeutics for Ewing Sarcoma is out.
Bin Chen and other members from Dahshu organize the conference Dahshu 2017: Data Science & Computational Precision Health. Paper submissions due: October 10, 2016 11:59PM PT!!!
Bin Chen gives an invited talk at DDW in San Diego, CA
Bin Chen gives an invited talk at the UCSF Precision Medicine Conference by PMSA at UCSF
Bin Chen and other members from Dahshu organize the Fourteenth Asia Pacific Bioinformatics Conference (APBC) in San Francisco, CA