Evidence map›Paper›PMID 35927613›Full record

ArticleBMC bioinformatics2022

SEMplMe: a tool for integrating DNA methylation effects in transcription factor binding affinity predictions.

Sierra S Nishizaki, Alan P Boyle

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Databases and prospects of dynamic gene regulation in eukaryotes: A mini review.Computational and structural biotechnology journal · 2023
    Review
  3. 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

2 authors at 1 institution in 1 country.

Sierra S NishizakiDepartment of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA.ORCID http://orcid.org/0000-0002-4288-4567
Alan P BoyleDepartment of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA. apboyle@umich.edu.ORCID http://orcid.org/0000-0002-2081-1105
University of Michigan · US

Funding

University of Michigan Training Program in Genomic ScienceT32HG000040 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sebastian Zoellner · 1995 to 2026
$16.4M
Resource Informatics and ProductionU41HG009293 · NHGRI · STANFORD UNIVERSITY · PI BOYLE, ALAN P, CHERRY, J. MICHAEL · 2017 to 2019
$2.2M
The Lowe Oculocerebrorenal SyndromeZ01HG000040 · NHGRI · HUMAN GENOME RESEARCH · PI NUSSBAUM, ROBERT L · 1995 to 2005
–
Intramural NIH HHS Z01 HG000040NHGRI NIH HHS T32 HG000040NHGRI NIH HHS U41 HG009293NIH HHS HG00040NIH HHS U41 HG009293
6 · The paper itself

Abstract

motivationAberrant DNA methylation in transcription factor binding sites has been shown to lead to anomalous gene regulation that is strongly associated with human disease. However, the majority of methylation-sensitive positions within transcription factor binding sites remain unknown. Here we introduce SEMplMe, a computational tool to generate predictions of the effect of methylation on transcription factor binding strength in every position within a transcription factor's motif.

resultsSEMplMe uses ChIP-seq and whole genome bisulfite sequencing to predict effects of methylation within binding sites. SEMplMe validates known methylation sensitive and insensitive positions within a binding motif, identifies cell type specific transcription factor binding driven by methylation, and outperforms SELEX-based predictions for CTCF. These predictions can be used to identify aberrant sites of DNA methylation contributing to human disease. AVAILABILITY AND IMPLEMENTATION: SEMplMe is available from https://github.com/Boyle-Lab/SEMplMe .

Indexed as

DNA MethylationTranscription FactorsBinding SitesGene Expression RegulationHumansProtein BindingTranscription FactorsDNA methylationGene regulationNoncoding variationOpen-sourceSoftwareTFBSTranscription factor

Identifiers

PMID35927613
PMCPMC9351228
OpenAlexW4289838143

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.