Bioinformatics Journal Club: Deep Learning for Disease Understanding

Bioinformatics Journal Club: Deep Learning for Disease Understanding

Join us for a deep dive into cutting-edge bioinformatics research! We'll be discussing the fascinating paper: Accurate prediction of cancer drug sensitivity with a self-attention-based deep learning model, published in Nature Methods!

This session is perfect for anyone with an interest in bioinformatics, from post-high school students to postdocs. We'll explore how computational biology and neural networks are revolutionizing our understanding of disease biology and paving the way for innovative treatment strategies.

This paper specifically looks at using a self-attention-based deep learning model to predict cancer drug sensitivity.

About the Bioinformatics Journal Club:

• Purpose: We discuss recent publications in Bioinformatics, Computational Biology, Biostatistics, Machine Learning, and related fields (Genomics, Single Cell methods, Immuno-Oncology, Drug Discovery & Development, Clinical Trials, etc.).
• Paper Selection: Papers are chosen by volunteer presenters, often focusing on their areas of expertise. Want to present a paper? Let us know! Send your suggestions to Celine, Simon, and Xiaochen via LinkedIn (please, no Meetup messages).
• Meeting Time: Saturday at 16:45 CET.
• Format: Our meetings are informal and casual. We typically discuss 1-2 papers per session, but we're flexible and can adjust based on interest.
• Discord: Join our Discord server for more info and discussions: Bioinformatics Journal Club Discord

Meeting Details:

• Date: Saturday
• Time: 16:45 CET
• Platform: Meetup & Zoom (link will be provided upon RSVP)

We're excited to learn and explore together! This is a safe space to ask questions, share ideas, and expand your knowledge of bioinformatics. We look forward to seeing you there!