Evidence map›Paper›PMID 41997213›Full record

ArticleJournal of molecular biology2026

ShapeME: A Tool and Web Front-end for De Novo Discovery of Structural Motifs Underpinning Protein-DNA Interactions.

Jeremy W Schroeder, Vivian Ramirez, Michael B Wolfe, Lydia Freddolino

Abstract read
In one paragraph

Article in Journal of molecular biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. The Algorithm for Reversible Jump Inference of Motifs.bioRxiv : the preprint server for biology · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Jeremy W SchroederDepartment of Biological Chemistry, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: schroedj@umich.edu.
Vivian RamirezDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Michael B WolfeDepartment of Biochemistry, University of Wisconsin - Madison, Madison, WI 53706, USA.
Lydia FreddolinoDepartment of Biological Chemistry, University of Michigan, Ann Arbor, MI 48109, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: lydsf@umich.edu.

Funding

Building a unified framework for understanding bacterial gene regulation and chromosomal architectureR35GM128637 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Lydia Petra Freddolino · 2018 to 2026
$3.6M
NIGMS NIH HHS R35 GM128637
6 · The paper itself

Abstract

Determining where proteins bind a genome is paramount to understanding gene regulation. In addition to DNA sequence motifs, structural motifs (e.g., a narrow minor groove width) determine binding for some proteins (Rohs et al., 2009) [1]. Algorithms using structural features of DNA to predict protein binding exist (Mathelier et al., 2016; Samee et al., 2019; Yang et al., 2019; Pal et al., 2019) [2-5], but a structural motif discovery framework which can be applied to a variety of experimental designs is needed. We present a workflow capable of utilizing virtually any type of data representing sequence coverage or enrichment (e.g. ChIP-seq, RNA-seq, SELEX, etc.) to discover structural motifs with explanatory power for a protein's DNA binding preference. Our approach to motif discovery wraps shape and sequence motif inference into a single tool called ShapeME (github: https://github.com/freddolino-lab/ShapeME.git, web interface: https://seq2fun.dcmb.med.umich.edu/shapeme). Application of ShapeME to ENCODE datasets reveals proteins for which short structural motifs outperform the best PWM for that protein at the JASPAR database, or as identified by the sequence motif elicitation tool STREME. ShapeME is a powerful, versatile framework for inferring structural DNA binding motifs.

Indexed as

Computational BiologyDNADNA-Binding ProteinsSoftwareAlgorithmsBinding SitesInternetNucleotide MotifsProtein BindingDNADNA-Binding ProteinsDNA binding proteingene regulationMotifmutual informationtranscription factor

Identifiers

PMID41997213
PMCPMC13329772

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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.