Machine Learning & Bioinformatics: In Conversation with Danielle Denisko @ UofT

We're excited to be featuring Danielle Denisko, a bioinformatics researcher from from the University of Toronto! Danielle will be speaking on machine learning applications for biology and sharing about her career path to date. Attendees from all technical backgrounds and experience levels are welcome!

SCHEDULE

• 6:00pm - Networking, snacks, drinks
• 6:30pm - Presentation, Danielle Denisko
• 7:30pm - More networking, snacks, drinks

ABOUT THE SPEAKER

Danielle uses statistics and machine learning methods to solve problems in biology. She is a graduate student in Michael Hoffman’s computational epigenomics lab in the Department of Medical Biophysics, University of Toronto. Recently, she published a commentary on an exciting new machine learning method that builds upon random forests to identify feature interactions. Her projects and research interests center on transcription factors, 3D chromatin organization, and local DNA shape. She received her Hon. B.Sc. from the University of Toronto in biological physics (specialist) and mathematics (minor).

Her talk will focus on machine learning and its various applications in biology, with prediction tasks spanning from molecular mechanisms to drug therapies. In particular, she will explore the popular random forests algorithm in detail and will outline some of its current exciting uses. Along the way, she will share her experiences in navigating graduate studies in bioinformatics, and will provide some tips for those who are interested in joining the field!