ArticleBriefings in functional genomics2017
Modeling protein-DNA binding via high-throughput in vitro technologies.
Article in Briefings in functional genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Review
- miRNA Profiling and Its Role in Multi-Omics Regulatory Networks Connected with Somaclonal Variation in Cucumber (International journal of molecular sciences · 2022Article
- Navigating the pitfalls of applying machine learning in genomics.Nature reviews. Genetics · 2022Review
- RBPmap: A Tool for Mapping and Predicting the Binding Sites of RNA-Binding Proteins Considering the Motif Environment.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Transcription factor control of virulence in phytopathogenic fungi.Molecular plant pathology · 2021Review
- Landscape of DNA binding signatures of myocyte enhancer factor-2B reveals a unique interplay of base and shape readout.Nucleic acids research · 2020Article
- Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study.Genome biology · 2020Article
- Combined Analysis of the Metabolome and Transcriptome Identified Candidate Genes Involved in Phenolic Acid Biosynthesis in the Leaves ofInternational journal of molecular sciences · 2020Article
- Sharing DNA-binding information across structurally similar proteins enables accurate specificity determination.Nucleic acids research · 2020Article
- Combined Analysis of the Fruit Metabolome and Transcriptome Reveals Candidate Genes Involved in Flavonoid Biosynthesis in Actinidia arguta.International journal of molecular sciences · 2018Article
- MicroRNA and Transcription Factor: Key Players in Plant Regulatory Network.Frontiers in plant science · 2017Review
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein-DNA binding plays a central role in gene regulation and by that in all processes in the living cell. Novel experimental and computational approaches facilitate better understanding of protein-DNA binding preferences via high-throughput measurement of protein binding to a large number of DNA sequences and inference of binding models from them. Here we review the state of the art in measuring protein-DNA binding in vitro, emphasizing the advantages and limitations of different technologies. In addition, we describe models for representing protein-DNA binding preferences and key computational approaches to learn those from high-throughput data. Using large experimental data sets, we test the performance of different models based on different measuring techniques. We conclude with pertinent open problems.
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