Evidence map›Paper›PMID 38352411›Full record

ArticlebioRxiv : the preprint server for biology2025

Predicting the DNA binding specificity of transcription factor mutants using family-level biophysically interpretable machine learning.

Shaoxun Liu, Pilar Gomez-Alcala, Christ Leemans, William J Glassford, Lucas A N Melo, Xiang-Jun Lu, Richard S Mann, Harmen J Bussemaker

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Shaoxun LiuDepartment of Biological Sciences, Columbia University, New York, NY, USA.ORCID 0000-0003-0997-3485
Pilar Gomez-AlcalaDepartment of Biological Sciences, Columbia University, New York, NY, USA.
Christ LeemansDepartment of Biological Sciences, Columbia University, New York, NY, USA.ORCID 0000-0002-3271-840X
William J GlassfordDepartment of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA.ORCID 0000-0003-4007-6731
Lucas A N MeloDepartment of Biological Sciences, Columbia University, New York, NY, USA.
Xiang-Jun LuDepartment of Biological Sciences, Columbia University, New York, NY, USA.
Richard S MannDepartment of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA.ORCID 0000-0002-4749-2765
Harmen J BussemakerDepartment of Biological Sciences, Columbia University, New York, NY, USA.ORCID 0000-0002-7274-5277
Columbia University · US

Funding

Inferring regulatory circuitry from microarray dataR01HG003008 · NHGRI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI BUSSEMAKER, HARMEN J · 2004 to 2020
$7.0M
Interpreting and Deploying Genomic Information During Animal DevelopmentR35GM118336 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI RICHARD S MANN · 2016 to 2026
$6.9M
Statistical models for fine-mapping and interpretation of schizophrenia-associated lociR01MH106842 · NIMH · NEW YORK GENOME CENTER · PI BUSSEMAKER, HARMEN J, LAPPALAINEN, TUULI · 2015 to 2024
$5.0M
NHGRI NIH HHS R01 HG003008NIGMS NIH HHS R35 GM118336NIMH NIH HHS R01 MH106842
6 · The paper itself

Abstract

Sequence-specific interactions of transcription factors (TFs) with genomic DNA underlie many cellular processes. High-throughput

Indexed as

basic helix-loop-helix (bHLH)biophysically interpretable machine learningDNA binding specificityfunctional impact of missense mutationshigh-throughput SELEXhomeodomainprotein binding microarray (PBM)transcription factors (TFs)

Identifiers

PMID38352411
PMCPMC10862739
OpenAlexW4391305887

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.