ArticleBMC genomics2015
Comprehensive genome-wide transcription factor analysis reveals that a combination of high affinity and low affinity DNA binding is needed for human gene regulation.
Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 29 citations in OpenAlex.
- Protocol for identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome data.STAR protocols · 2026Article
- Bipartite DNA binding domain of transcription factor BCL11B binds clustered short DNA sequence motifs.bioRxiv : the preprint server for biology · 2026Article
- BayesPI-FLY: a Bayesian neural network approach for inferring feature weighted TF-DNA interaction.Briefings in bioinformatics · 2026Article
- Sequence-based modeling of low-affinity transcription factor-DNA binding through deep learning.NAR genomics and bioinformatics · 2026Article
- SMUG1 DNA glycosylase modulates reward behaviour through regulation of olfactory receptor gene expression.Nucleic acids research · 2025Article
- Multimeric transcription factor BCL11A utilizes two zinc-finger tandem arrays to bind clustered short sequence motifs.Nature communications · 2025Article
- Identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome data.iScience · 2023Article
- DNA selection by the master transcription factor PU.1.Cell reports · 2023Article
- On the incongruence of genotype-phenotype and fitness landscapes.PLoS computational biology · 2022Article
- abc4pwm: affinity based clustering for position weight matrices in applications of DNA sequence analysis.BMC bioinformatics · 2022Article
- The Non-continuum Nature of Eukaryotic Transcriptional Regulation.Advances in experimental medicine and biology · 2022Article
- IGAP-integrative genome analysis pipeline reveals new gene regulatory model associated with nonspecific TF-DNA binding affinity.Computational and structural biotechnology journal · 2020Article
- BayesPI-BAR2: A New Python Package for Predicting Functional Non-coding Mutations in Cancer Patient Cohorts.Frontiers in genetics · 2019Article
- Revealing transcription factor and histone modification co-localization and dynamics across cell lines by integrating ChIP-seq and RNA-seq data.BMC genomics · 2018Article
- Article
- Integrative whole-genome sequence analysis reveals roles of regulatory mutations in BCL6 and BCL2 in follicular lymphoma.Scientific reports · 2017Article
- Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell.Chemical reviews · 2016Review
- BayesPI-BAR: a new biophysical model for characterization of regulatory sequence variations.Nucleic acids research · 2015Article
- Education, collaboration, and innovation: intelligent biology and medicine in the era of big data.BMC genomics · 2015Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHigh-throughput in vivo protein-DNA interaction experiments are currently widely used in gene regulation studies. Hitherto, comprehensive data analysis remains a challenge and for that reason most computational methods only consider the top few hundred or thousand strongest protein binding sites whereas weak protein binding sites are completely ignored.
resultsA new biophysical model of protein-DNA interactions, BayesPI2+, was developed to address the above-mentioned challenges. BayesPI2+ can be run in either a serial computation model or a parallel ensemble learning framework. BayesPI2+ allowed us to analyze all binding sites of the transcription factors, including weak binding that cannot be analyzed by other models. It is evaluated in both synthetic and real in vivo protein-DNA binding experiments. Analysing ESR1 and SPIB in breast carcinoma and activated B cell-like diffuse large B-cell lymphoma cell lines, respectively, revealed that the concerted binding to high and low affinity sites correlates best with gene expression.
conclusionsBayesPI2+ allows us to analyze transcription factor binding on a larger scale than hitherto achieved. By this analysis, we were able to demonstrate that genes are regulated by concerted binding to high and low affinity binding sites. The program and output results are publicly available at: http://folk.uio.no/junbaiw/BayesPI2Plus.
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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 Socratic graph.