Evidence map›Paper›PMID 39677755›Full record

ArticlebioRxiv : the preprint server for biology2024

A mathematical model clarifies the ABC Score formula used in enhancer-gene prediction.

Joseph Nasser, Kee-Myoung Nam, Jeremy Gunawardena

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Joseph NasserDepartment of Systems Biology, Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-5941-5751
Kee-Myoung NamDepartment of Systems Biology, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-3594-6141
Jeremy GunawardenaDepartment of Systems Biology, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-7280-1152

Funding

Information Integration and Energy Expenditure in Eukaryotic Gene RegulationR01GM122928 · NIGMS · HARVARD MEDICAL SCHOOL · PI DEPACE, ANGELA H, GUNAWARDENA, JEREMY · 2017 to 2024
$3.7M
NIGMS NIH HHS R01 GM122928
6 · The paper itself

Abstract

Enhancers are discrete DNA elements that regulate the expression of eukaryotic genes. They are important not only for their regulatory function, but also as loci that are frequently associated with disease traits. Despite their significance, our conceptual understanding of how enhancers work remains limited. CRISPR-interference methods have recently provided the means to systematically screen for enhancers in cell culture, from which a formula for predicting whether an enhancer regulates a gene, the Activity-by-Contact (ABC) Score, has emerged and has been widely adopted. While useful as a binary classifier, it is less effective at predicting the quantitative effect of an enhancer on gene expression. It is also unclear how the algebraic form of the ABC Score arises from the underlying molecular mechanisms and what assumptions are needed for it to hold. Here, we use the graph-theoretic linear framework, previously introduced to analyze gene regulation, to formulate the

Identifiers

PMID39677755
PMCPMC11642778

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Registered trials

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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.