Presenter: Haohan Wang, PhD

The development of machine learning techniques has offered us a new opportunity to analyze complex structured neuroscience data at a large scale to unveil the pathology of some neurodegenerative disorders and to offer potential preventive and therapeutic strategies.

Presenter: DBMI DEI Committee

An interactive discussion of the importance of diversity, equity, and inclusion to DBMI and what we might do to advance these values through all aspects of our mission

Presenter: Thanksgiving Break
Presenter: Sandra Kane-Gill, PharmD, MS, FCCM, FCCP

Nephrotoxin stewardship ensures a structured and consistent approach to safe medication use and prevention of patient harm. Clinical decision support can assist with stewardship efforts to reduce medication errors and adverse drug events and prevent or reduce severity of D-AKI.

Presenter: Yufei Huang, PhD

N6-methyladenosine (m6A) is the most abundant methylation in transcripts, existing in >25% of human mRNAs. Exciting recent discoveries indicate a close involvement of m6A in regulating many different aspects of mRNA metabolism and cancer.

Presenter: Maria Chikina, PhD

Genome scale technologies can measure thousands or even millions of molecular features but the individual measurements are often noisy redouts of a smaller set of parameters describing the internal biological state.  Indeed, many computational analyses can be viewed as methods to infer the true biological variables from their coordinated effects on a larger set of experimental readouts.  In this talk I will discuss methods that use biologically motivated priors and constraints to  reduce lar

Presenter: Craig Wilcox, PhD

Attendees will learn how federal regulation and University policy define research misconduct, and what to do if they observe possible misconduct.  Attendees will also learn steps to take that can help reduce the possibility of research misconduct in their laboratories, and how good research practies can help them protect their lab and defend themselves in the event of false alligations of research misconduct.