AIMC Topic: DNA-Binding Proteins

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DRBP-EDP: classification of DNA-binding proteins and RNA-binding proteins using ESM-2 and dual-path neural network.

NAR genomics and bioinformatics
Regulation of DNA or RNA at the transcriptional, post-transcriptional, and translational levels are key steps in the central dogma of molecular biology. DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) play pivotal roles in the precise reg...

PLM-DBPs: enhancing plant DNA-binding protein prediction by integrating sequence-based and structure-aware protein language models.

Briefings in bioinformatics
DNA-binding proteins (DBPs) play a crucial role in gene regulation, development, and environmental responses across plants, animals, and microorganisms. Existing DBP prediction methods are largely limited to sequence information, whether through hand...

iProtDNA-SMOTE: Enhancing protein-DNA binding sites prediction through imbalanced graph neural networks.

PloS one
Protein-DNA interactions play a crucial role in cellular biology, essential for maintaining life processes and regulating cellular functions. We propose a method called iProtDNA-SMOTE, which utilizes non-equilibrium graph neural networks along with p...

Screening of gastric cancer diagnostic biomarkers in the homologous recombination signaling pathway and assessment of their clinical and radiomic correlations.

Cancer medicine
BACKGROUND: Homologous recombination plays a vital role in the occurrence and drug resistance of gastric cancer. This study aimed to screen new gastric cancer diagnostic biomarkers in the homologous recombination pathway and then used radiomic featur...

ProkDBP: Toward more precise identification of prokaryotic DNA binding proteins.

Protein science : a publication of the Protein Society
Prokaryotic DNA binding proteins (DBPs) play pivotal roles in governing gene regulation, DNA replication, and various cellular functions. Accurate computational models for predicting prokaryotic DBPs hold immense promise in accelerating the discovery...

EGPDI: identifying protein-DNA binding sites based on multi-view graph embedding fusion.

Briefings in bioinformatics
Mechanisms of protein-DNA interactions are involved in a wide range of biological activities and processes. Accurately identifying binding sites between proteins and DNA is crucial for analyzing genetic material, exploring protein functions, and desi...

Improved prediction of DNA and RNA binding proteins with deep learning models.

Briefings in bioinformatics
Nucleic acid-binding proteins (NABPs), including DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs), play important roles in essential biological processes. To facilitate functional annotation and accurate prediction of different types of NA...

Deep-learning optimized DEOCSU suite provides an iterable pipeline for accurate ChIP-exo peak calling.

Briefings in bioinformatics
Recognizing binding sites of DNA-binding proteins is a key factor for elucidating transcriptional regulation in organisms. ChIP-exo enables researchers to delineate genome-wide binding landscapes of DNA-binding proteins with near single base-pair res...

A deep learning-based method for the prediction of DNA interacting residues in a protein.

Briefings in bioinformatics
DNA-protein interaction is one of the most crucial interactions in the biological system, which decides the fate of many processes such as transcription, regulation and splicing of genes. In this study, we trained our models on a training dataset of ...

DNA-binding protein prediction based on deep transfer learning.

Mathematical biosciences and engineering : MBE
The study of DNA binding proteins (DBPs) is of great importance in the biomedical field and plays a key role in this field. At present, many researchers are working on the prediction and detection of DBPs. Traditional DBP prediction mainly uses machi...