AI identifies developmental defects and drug mechanisms in embryos

Müller, P

doi:10.1038/s41592-023-01872-5

Local TagsRelease HistoryDetailsSummary

AI identifies developmental defects and drug mechanisms in embryos

Müller, P. (2023). AI identifies developmental defects and drug mechanisms in embryos. Nature Methods, 20(6), 793-794. doi:10.1038/s41592-023-01872-5.

Item is Released

show all hide all

Basic

show hide

Item Permalink: https://hdl.handle.net/21.11116/0000-000F-7703-8 Version Permalink: https://hdl.handle.net/21.11116/0000-000F-7704-7

Genre: Journal Article

Files

show Files

Locators

show

Creators

show

hide

Creators:
Müller, P¹, Author

Affiliations:
1Müller Group, Friedrich Miescher Laboratory, Max Planck Society, ou_3008690

Content

show

hide

Free keywords: -

Abstract: We developed EmbryoNet, a deep learning tool that can automatically identify and classify developmental defects caused by perturbations of signaling pathways in vertebrate embryos. The tool could help to elucidate the mechanisms of action of pharmaceuticals, potentially transforming the drug discovery process.

Details

show

hide

Language(s):

Dates: Date issued: 2023-06

Publication Status: Issued

Pages: -

Publishing info: -

Table of Contents: -

Rev. Type: -

Identifiers: DOI: 10.1038/s41592-023-01872-5
PMID: 37156845

Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show

hide

Title: Nature Methods

Abbreviation : Nat Methods

Source Genre: Journal

Creator(s):

Affiliations:

Publ. Info: New York, NY : Nature Publishing Group

Pages: - Volume / Issue: 20 (6) Sequence Number: - Start / End Page: 793 - 794 Identifier: ISSN: 1548-7091
CoNE: https://pure.mpg.de/cone/journals/resource/111088195279556