Machine learning predicts nucleosome binding modes of transcription factors

Machine learning predicts nucleosome binding modes of transcription factors

Background: Most transcription factors (TFs) compete with nucleosomes to gain access to their cognate binding sites. Recent studies have identified several TF-nucleosome interaction modes including end binding (EB), oriented binding, periodic binding, dyad binding, groove binding, and gyre spanning....

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Bibliographic Details
Main Authors: Cui, F. (Author), Kishan, K.C (Author), Li, R. (Author), Subramanya, S.K (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
amino acid sequence
Amino Acid Sequence
Binary classifiers
Binding energy
binding site
Binding sites
Binding Sites
Classification (of information)
Comprehensive analysis
Computational predictions
genetics
Interaction modes
machine learning
Machine learning
Machine Learning
metabolism
Multi label classification
Nested cross validations
nucleosome
Nucleosome binding modes
Nucleosomes
Off-the-shelf machine
protein binding
Protein Binding
Protein sequences
transcription factor
Transcription factors
Transcription Factors
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