Evan Seitz
Evan Seitz
Home
Skills
Projects
Publications
Presentations
CV
Light
Dark
Automatic
Scientific
Poster at CSHL Biological Data Science
Evan E Seitz, David M McCandlish, Justin B Kinney and Peter K Koo. “Deciphering the determinants of mechanistic variation in regulatory sequences”, Biological Data Science, November 2024.
Last updated on Nov 12, 2024
Abstract
Poster
Website
Poster at CSHL Genome Informatics
Evan E Seitz, David M McCandlish, Justin B Kinney and Peter K Koo. “A surrogate modeling framework for interpreting deep neural networks in functional genomics”, Genome Informatics, December 2023.
Last updated on Nov 12, 2024
Abstract
Poster
Website
SQUID Python Suite (2023)
SQUID (Surrogate Quantitative Interpretability for Deepnets) is a Python suite to interpret sequence-based deep learning models for regulatory genomics data with domain-specific surrogate models. This software was developed in the Kinney lab and Koo lab at Cold Spring Harbor Laboratory.
Cite
Software repository
Read the Docs
Poster at CSHL Biology of Genomes
Evan E Seitz, Justin B Kinney and Peter K Koo. “A surrogate modeling framework for interpreting deep neural networks in functional genomics”, Biology of Genomes, May 2023.
Last updated on Nov 29, 2023
Abstract
Photo 1
Photo 2
Photo 3
Website
ManifoldEM Python Suite (2021)
Public release of ManifoldEM Python suite (Beta version) for determination of conformational continua of biomolecules from single-particle cryo-EM data. This software was developed in the Frank research group at Columbia University in collaboration with members from UWM.
Cite
Software repository
User manual
Video demonstration
Cite
×