Colloquium Details
Predicting Human Gene-regulatory Functions from DNA Sequence
Speaker: Johannes Linder, Calico Life Sciences
Location: 60 Fifth Avenue 150
Date: April 3, 2025, 2 p.m.
Host: Sumit Chopra
Synopsis:
There is a regulatory code written in DNA and RNA sequences that controls gene expression and isoform processing. Developing accurate models of this code is crucial for advancing human health - such models allow us to interpret harmful genetic mutations and design improved regulatory sequences. In this talk, I will first give an overview of existing machine learning methods for sequence-based prediction of regulatory functions (transcription, RNA splicing, etc.). I will then present a unified model of gene regulation that directly learns to predict raw RNA expression profiles from DNA sequence alone. In the second part of the talk, I will discuss methods for designing improved regulatory sequences and highlight their potential for molecular therapies. I will conclude by discussing future opportunities and challenges in developing even better models of gene expression.
Note: In-person attendance only available to those with active NYU ID cards.
Speaker Bio:
Johannes Linder is a machine learning scientist at Calico Life Sciences, working with Dr. David Kelley. He received his Ph.D. in Computer Science from the University of Washington in 2021, where he was advised by Prof. Georg Seelig. He was a postdoctoral researcher in Prof. Anshul Kundaje’s group at Stanford University before joining Calico Life Sciences in 2022. His research spans multiple fields, including machine learning, genomics, and synthetic biology.