ArticleScientific reports2017
Analysis of Co-Associated Transcription Factors via Ordered Adjacency Differences on Motif Distribution.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 16 citations in OpenAlex.
- Identifying the "stripe" transcription factors and cooperative binding related to DNA methylation.Communications biology · 2024Article
- Role Assignment Mechanism of Unmanned Swarm Organization Reconstruction Based on the Fourth Directed Motif.Sensors (Basel, Switzerland) · 2022Article
- In silico analysis of promoter region and regulatory elements of mitogenome co-expressed trn gene clusters encoding for bio-pesticide in entomopathogenic fungus, Metarhizium anisopliae: strain ME1.Journal, genetic engineering & biotechnology · 2021Article
- Clustering and classification methods for single-cell RNA-sequencing data.Briefings in bioinformatics · 2020Review
- RF-PseU: A Random Forest Predictor for RNA Pseudouridine Sites.Frontiers in bioengineering and biotechnology · 2020Article
- Discovering Cancer Subtypes via an Accurate Fusion Strategy on Multiple Profile Data.Frontiers in genetics · 2019Article
- Identifying Plant Pentatricopeptide Repeat Coding Gene/Protein Using Mixed Feature Extraction Methods.Frontiers in plant science · 2018Article
- Identification of DNA-protein Binding Sites through Multi-Scale Local Average Blocks on Sequence Information.Molecules (Basel, Switzerland) · 2017Article
- Improved detection of DNA-binding proteins via compression technology on PSSM information.PloS one · 2017Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transcription factors (TFs) binding to specific DNA sequences or motifs, are elementary to the regulation of transcription. The gene is regulated by a combination of TFs in close proximity. Analysis of co-TFs is an important problem in understanding the mechanism of transcriptional regulation. Recently, ChIP-seq in mapping TF provides a large amount of experimental data to analyze co-TFs. Several studies show that if two TFs are co-associated, the relative distance between TFs exhibits a peak-like distribution. In order to analyze co-TFs, we develop a novel method to evaluate the associated situation between TFs. We design an adjacency score based on ordered differences, which can illustrate co-TF binding affinities for motif analysis. For all candidate motifs, we calculate corresponding adjacency scores, and then list descending-order motifs. From these lists, we can find co-TFs for candidate motifs. On ChIP-seq datasets, our method obtains best AUC results on five datasets, 0.9432 for NMYC, 0.9109 for KLF4, 0.9006 for ZFX, 0.8892 for ESRRB, 0.8920 for E2F1. Our method has great stability on large sample datasets. AUC results of our method on all datasets are above 0.8.
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