ReviewMolecular bioSystems2013
Prediction of RNA binding proteins comes of age from low resolution to high resolution.
Review in Molecular bioSystems, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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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.
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Who cites it
20 citing papers in PubMed, 40 citations in OpenAlex.
- Comparative assessment of binding residue predictions in intrinsically disordered regions.Protein science : a publication of the Protein Society · 2025Article
- DRBP-EDP: classification of DNA-binding proteins and RNA-binding proteins using ESM-2 and dual-path neural network.NAR genomics and bioinformatics · 2025Article
- Twenty years of advances in prediction of nucleic acid-binding residues in protein sequences.Briefings in bioinformatics · 2024Review
- HybridRNAbind: prediction of RNA interacting residues across structure-annotated and disorder-annotated proteins.Nucleic acids research · 2023Article
- qNABpredict: Quick, accurate, and taxonomy-aware sequence-based prediction of content of nucleic acid binding amino acids.Protein science : a publication of the Protein Society · 2023Article
- Complementarity of the residue-level protein function and structure predictions in human proteins.Computational and structural biotechnology journal · 2022Article
- DescribePROT: database of amino acid-level protein structure and function predictions.Nucleic acids research · 2021Article
- Comprehensive Survey and Comparative Assessment of RNA-Binding Residue Predictions with Analysis by RNA Type.International journal of molecular sciences · 2020Review
- PSIONplusBiomolecules · 2020Article
- Partner-specific prediction of RNA-binding residues in proteins: A critical assessment.Proteins · 2019Article
- DRNApred, fast sequence-based method that accurately predicts and discriminates DNA- and RNA-binding residues.Nucleic acids research · 2017Article
- Sequence-Based Prediction of RNA-Binding Residues in Proteins.Methods in molecular biology (Clifton, N.J.) · 2017Article
- A MOTIF-BASED METHOD FOR PREDICTING INTERFACIAL RESIDUES IN BOTH THE RNA AND PROTEIN COMPONENTS OF PROTEIN-RNA COMPLEXES.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2016Article
- A Large-Scale Assessment of Nucleic Acids Binding Site Prediction Programs.PLoS computational biology · 2015Article
- Computational Prediction of RNA-Binding Proteins and Binding Sites.International journal of molecular sciences · 2015Review
- High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder.Nucleic acids research · 2015Article
- Prediction of nucleic acid binding probability in proteins: a neighboring residue network based score.Nucleic acids research · 2015Article
- SPOT-Seq-RNA: predicting protein-RNA complex structure and RNA-binding function by fold recognition and binding affinity prediction.Methods in molecular biology (Clifton, N.J.) · 2014Article
- The potential of the riboSNitch in personalized medicine.Wiley interdisciplinary reviews. RNAReview
- Prediction of RNA- and DNA-Binding Proteins Using Various Machine Learning Classifiers.Avicenna journal of medical biotechnologyArticle
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Networks of protein-RNA interactions is likely to be larger than protein-protein and protein-DNA interaction networks because RNA transcripts are encoded tens of times more than proteins (e.g. only 3% of human genome coded for proteins), have diverse function and localization, and are controlled by proteins from birth (transcription) to death (degradation). This massive network is evidenced by several recent experimental discoveries of large numbers of previously unknown RNA-binding proteins (RBPs). Meanwhile, more than 400 non-redundant protein-RNA complex structures (at 25% sequence identity or less) have been deposited into the protein databank. These sequences and structural resources for RBPs provide ample data for the development of computational techniques dedicated to RBP prediction, as experimentally determining RNA-binding functions is time-consuming and expensive. This review compares traditional machine-learning based approaches with emerging template-based methods at several levels of prediction resolution ranging from two-state binding/non-binding prediction, to binding residue prediction and protein-RNA complex structure prediction. The analysis indicates that the two approaches are complementary and their combinations may lead to further improvements.
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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.