ArticleNucleic acids research2015
Prediction of nucleic acid binding probability in proteins: a neighboring residue network based score.
Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed.
- Protein-DNA Binding Sites Prediction via Integrating Pretrained Large Language Models and Contrastive Learning.Interdisciplinary sciences, computational life sciences · 2026Article
- Twenty years of advances in prediction of nucleic acid-binding residues in protein sequences.Briefings in bioinformatics · 2024Review
- GeoBind: segmentation of nucleic acid binding interface on protein surface with geometric deep learning.Nucleic acids research · 2023Article
- pyProGA-A PyMOL plugin for protein residue network analysis.PloS one · 2021Article
- Multiple protein-DNA interfaces unravelled by evolutionary information, physico-chemical and geometrical properties.PLoS computational biology · 2020Article
- Partner-specific prediction of RNA-binding residues in proteins: A critical assessment.Proteins · 2019Article
- Functional Site Discovery From Incomplete Training Data: A Case Study With Nucleic Acid-Binding Proteins.Frontiers in genetics · 2019Article
- PredPRBA: Prediction of Protein-RNA Binding Affinity Using Gradient Boosted Regression Trees.Frontiers in genetics · 2019Article
- Individually double minimum-distance definition of protein-RNA binding residues and application to structure-based prediction.Journal of computer-aided molecular design · 2018Article
- Review
- A structural dissection of protein-RNA interactions based on different RNA base areas of interfaces.RSC advances · 2018Article
- Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation.Chemical reviews · 2018Review
- Integrating sequence and gene expression information predicts genome-wide DNA-binding proteins and suggests a cooperative mechanism.Nucleic acids research · 2018Article
- A boosting approach for prediction of protein-RNA binding residues.BMC bioinformatics · 2017Article
- DRNApred, fast sequence-based method that accurately predicts and discriminates DNA- and RNA-binding residues.Nucleic acids research · 2017Article
- RPI-Bind: a structure-based method for accurate identification of RNA-protein binding sites.Scientific reports · 2017Article
- Fast H-DROP: A thirty times accelerated version of H-DROP for interactive SVM-based prediction of helical domain linkers.Journal of computer-aided molecular design · 2017Article
- Sequence-Based Prediction of RNA-Binding Residues in Proteins.Methods in molecular biology (Clifton, N.J.) · 2017Article
- Protein-RNA interactions: structural biology and computational modeling techniques.Biophysical reviews · 2016Review
- IPMiner: hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational prediction.BMC genomics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We describe a general binding score for predicting the nucleic acid binding probability in proteins. The score is directly derived from physicochemical and evolutionary features and integrates a residue neighboring network approach. Our process achieves stable and high accuracies on both DNA- and RNA-binding proteins and illustrates how the main driving forces for nucleic acid binding are common. Because of the effective integration of the synergetic effects of the network of neighboring residues and the fact that the prediction yields a hierarchical scoring on the protein surface, energy funnels for nucleic acid binding appear on protein surfaces, pointing to the dynamic process occurring in the binding of nucleic acids to proteins.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.