Evidence map›Paper›PMID 37298131›Full record

ReviewInternational journal of molecular sciences2023

Florent Laval, Georges Coppin, Jean-Claude Twizere, Marc Vidal

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

4 authors.

Florent LavalCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA 02215, USA.ORCID 0000-0001-7744-6199
Georges CoppinCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Jean-Claude TwizereCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Marc VidalCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA 02215, USA.

Funding

Molecular phenotyping of ~100,000 coding variants across Mendelian disease genesUM1HG011989 · NHGRI · DANA-FARBER CANCER INST · PI Marc Vidal · 2021 to 2026
$9.9M
Rewiring of regulatory networks in breast cancer by transcription factor isoformsU01CA232161 · NCI · DANA-FARBER CANCER INST · PI BULYK, MARTHA L, FUXMAN BASS, JUAN IGNACIO · 2018 to 2022
$4.1M
Selective disruption of histone deacetylase complexes using protein interaction modulatorsR01CA266194 · NCI · DANA-FARBER CANCER INST · PI Marc Vidal · 2022 to 2026
$3.4M
Interface-resolution domain-domain interactome map of the yeast complexomeR01GM130885 · NIGMS · DANA-FARBER CANCER INST · PI VIDAL, MARC · 2019 to 2022
$2.7M
Incomplete Penetrance via Edgetic SuppressionR01GM133185 · NIGMS · DANA-FARBER CANCER INST · PI CALDERWOOD, MICHAEL A, ROTH, FREDERICK P · 2019 to 2022
$2.4M
NCI NIH HHS R01 CA266194NCI NIH HHS U01 CA232161NHGRI NIH HHS UM1 HG011989NIGMS NIH HHS R01 GM130885NIGMS NIH HHS R01 GM133185NIH HHS R01CA266194NIH HHS R01GM130885NIH HHS R01GM133185NIH HHS U01CA232161NIH HHS UM1HG011989
6 · The paper itself

Abstract

Understanding how genetic variation affects phenotypes represents a major challenge, particularly in the context of human disease. Although numerous disease-associated genes have been identified, the clinical significance of most human variants remains unknown. Despite unparalleled advances in genomics, functional assays often lack sufficient throughput, hindering efficient variant functionalization. There is a critical need for the development of more potent, high-throughput methods for characterizing human genetic variants. Here, we review how yeast helps tackle this challenge, both as a valuable model organism and as an experimental tool for investigating the molecular basis of phenotypic perturbation upon genetic variation. In systems biology, yeast has played a pivotal role as a highly scalable platform which has allowed us to gain extensive genetic and molecular knowledge, including the construction of comprehensive interactome maps at the proteome scale for various organisms. By leveraging interactome networks, one can view biology from a systems perspective, unravel the molecular mechanisms underlying genetic diseases, and identify therapeutic targets. The use of yeast to assess the molecular impacts of genetic variants, including those associated with viral interactions, cancer, and rare and complex diseases, has the potential to bridge the gap between genotype and phenotype, opening the door for precision medicine approaches and therapeutic development.

Indexed as

NeoplasmsSaccharomyces cerevisiaeGenomicsHumansPhenotypeProteomeProteomeedgeticshuman variomeinteractomepersonalized medicineprotein–protein interactionyeast

Identifiers

PMID37298131
PMCPMC10252790

What OpenQuestion holds

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LicenceCC BY
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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.