Quantitative biologist, currently working to advance deep learning for genomics as a Computational Postdoctoral Fellow @CSHL
New York City
Joined July 2017
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Evan Seitz retweeted
Which mutations rewire function of regulatory DNA?
Excited to share SEAM: Systematic Explanation of Attribtuion-based Mechanisms. SEAM is an explainable AI method that dissects cis-regulatory mechanisms learned by seq2fun genomic deep learning models.
Led by @EESetiz
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Evan Seitz retweeted
At @iclr_conf and interested in AI x Bio? Come see new work by the Koo Lab!
1. Oral presentation at @gembioworkshop by Evan Seitz (@EESeitz) on SEAM a method to decode the mechanistic impact of genetic variation on regulatory sequences with deep learning!
openreview.net/forum?id=PtjM…
Evan Seitz retweeted
Very proud that SQUID is now published in Nature Machine Intelligence! @NatMachIntell
View only link (no subscription needed):
rdcu.be/dLuZe
Full link (w/ subscription):
nature.com/articles/s42256-0…
@EESeitz @jbkinney @TheDMMcC
(Thanks to reviewers for feedback)
Excited to share new work on "Interpreting cis-regulatory mechanisms from genomic deep neural networks using surrogate models” led by @EESeitz, jointly advised by me and @jbkinney and in collab with @TheDMMcC
Paper: biorxiv.org/content/10.1101/…
Docs: squid-nn.readthedocs.io
Evan Seitz retweeted
In genomic deep learning, the trends right now are to build bigger models that consider longer sequence contexts. While predictions are more powerful, their scale makes them difficult to interpret. To address this gap, we have developed CREME.
Paper: biorxiv.org/content/10.1101/…
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Evan Seitz retweeted
Excited to share new work on "Interpreting cis-regulatory mechanisms from genomic deep neural networks using surrogate models” led by @EESeitz, jointly advised by me and @jbkinney and in collab with @TheDMMcC
Paper: biorxiv.org/content/10.1101/…
Docs: squid-nn.readthedocs.io
Thesis published: Analysis of Conformational Continuum and Free-energy Landscapes from Manifold Embedding of Single-particle Cryo-EM Ensembles of Biomolecules doi.org/10.7916/4n0v-wa24
I'm happy to announce the release of the ManifoldEM Python (beta) software suite, available at github.com/evanseitz/Manifol…, featuring many interactive tools to help researchers explore highly heterogeneous cryo-EM data sets. #CryoEM #ManifoldEM
We've released a new paper exploring manifold analysis of cryo-EM data: biorxiv.org/content/10.1101/…
New paper -- A simulation of cryo-EM images from a continuously varying structure:
biorxiv.org/content/10.1101/…
Read about our latest #research on #cryoEM #Biology #protein, published with @SpringerNature in @naturemethods. Read here: nature.com/articles/s41592-0…