Evidence map›Paper›PMID 34353905›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

Interpreting machine learning models to investigate circadian regulation and facilitate exploration of clock function.

Laura-Jayne Gardiner, Rachel Rusholme-Pilcher, Josh Colmer, Hannah Rees, Juan Manuel Crescente, Anna Paola Carrieri, Susan Duncan, Edward O Pyzer-Knapp, Ritesh Krishna, Anthony Hall

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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  7. Maize inbreds show allelic variation for diel transcription patterns.bioRxiv : the preprint server for biology · 2024
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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

10 authors.

Laura-Jayne GardinerIBM Research Europe, The Hartree Centre, Warrington WA4 4AD, United Kingdom; laura-jayne.gardiner@ibm.com.ORCID 0000-0002-9177-4452
Rachel Rusholme-PilcherEarlham Institute, Norwich NR4 7UZ, United Kingdom.ORCID 0000-0003-0000-0038
Josh ColmerEarlham Institute, Norwich NR4 7UZ, United Kingdom.ORCID 0000-0002-0511-685X
Hannah ReesEarlham Institute, Norwich NR4 7UZ, United Kingdom.
Juan Manuel CrescenteIBM Research Europe, The Hartree Centre, Warrington WA4 4AD, United Kingdom.
Anna Paola CarrieriIBM Research Europe, The Hartree Centre, Warrington WA4 4AD, United Kingdom.
Susan DuncanEarlham Institute, Norwich NR4 7UZ, United Kingdom.ORCID 0000-0001-9581-1145
Edward O Pyzer-KnappIBM Research Europe, The Hartree Centre, Warrington WA4 4AD, United Kingdom.ORCID 0000-0002-8232-8282
Ritesh KrishnaIBM Research Europe, The Hartree Centre, Warrington WA4 4AD, United Kingdom.ORCID 0000-0002-5303-1412
Anthony HallEarlham Institute, Norwich NR4 7UZ, United Kingdom.ORCID 0000-0002-1806-020X

Funding

Biotechnology and Biological Sciences Research Council BBS/E/T/000PR9817
6 · The paper itself

Abstract

The circadian clock is an important adaptation to life on Earth. Here, we use machine learning to predict complex, temporal, and circadian gene expression patterns in

Indexed as

Machine LearningModels, BiologicalApoproteinsArabidopsisArabidopsis ProteinsCircadian ClocksCircadian RhythmEcotypeGene Expression ProfilingGene Expression Regulation, PlantPhytochromePhytochrome ARegulatory Sequences, Nucleic AcidApoproteinsArabidopsis ProteinsPHYA protein, ArabidopsisPHYE protein, ArabidopsisPhytochromePhytochrome Aphytochrome C, Arabidopsiscircadianexplainable AIfunctionregulationtranscriptome

Identifiers

PMID34353905
PMCPMC8364196

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.