Evidence map›Paper›PMID 37434003›Full record

ArticleNature methods2023

Scaling biological discovery at the interface of deep learning and cellular imaging.

Morgan Schwartz, Uriah Israel, Xuefei Julie Wang, Emily Laubscher, Changhua Yu, Rohit Dilip, Qilin Li, Joud Mari, Johnathon Soro, Kevin Yu and 6 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Morgan SchwartzDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.ORCID http://orcid.org/0000-0001-8131-9125
Uriah IsraelDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
Xuefei Julie WangDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
Emily LaubscherDepartment of Chemistry, California Institute of Technology, Pasadena, CA, USA.ORCID http://orcid.org/0009-0008-0242-0507
Changhua YuDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
Rohit DilipDepartment of Computer Science, California Institute of Technology, Pasadena, CA, USA.
Qilin LiDepartment of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA.
Joud MariDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
Johnathon SoroDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
Kevin YuDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
Elora PradhanDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
Ada AtesDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
Danielle GallandtDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
Ross BarnowskiDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
Edward PaoDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA.
David Van ValenDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA, USA. vanvalen@caltech.edu.ORCID http://orcid.org/0000-0001-7534-7621

Funding

Unraveling the genetic basis of cellular behaviors with deep learning and imaging-based reverse geneticsDP2GM149556 · NIGMS · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI VAN VALEN, DAVID A · 2022 to 2025
$2.0M
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Deep LearningResearch Design

Identifiers

PMID37434003

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.