ReviewBiomolecules2022
Single-Stranded DNA Binding Proteins and Their Identification Using Machine Learning-Based Approaches.
Review in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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.
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.
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Who cites it
14 citing papers in PubMed, 20 citations in OpenAlex.
- RGTBind: RBF-gate graph transformer with spatially biased attention for protein-DNA binding-site prediction.Journal of molecular modeling · 2026Article
- The crystal structure of the herpes virus ICP8 protein in complex with single-stranded DNA reveals the molecular determinants of nucleotide recognition.The Journal of biological chemistry · 2026Article
- Response Factor Correction for Quantitative Determination of HomooligomericJournal of the American Society for Mass Spectrometry · 2026Article
- iDLDDG: predicting protein stability changes from missense mutations in DNA-binding proteins using integrated deep learning features.Briefings in bioinformatics · 2026Article
- Development of CPE/ssDNA-Based Electrochemical Sensor for the Detection of Leucine to Assess Soil Health.Biosensors · 2025Article
- Nucleic Acid Diversity in cGAS-STING Pathway Activation and Immune Dysregulation.Biomedicines · 2025Review
- GbTRB1 binds telomeric DNA in Ginkgo biloba.BMC plant biology · 2025Article
- Genomic privacy and security in the era of artificial intelligence and quantum computing.Discover computing · 2025Review
- Accurate prediction of nucleic acid binding proteins using protein language model.Bioinformatics advances · 2025Article
- Improved prediction of DNA and RNA binding proteins with deep learning models.Briefings in bioinformatics · 2024Article
- Three-Dimensional Modeling of CpG DNA Binding with Matrix Lumican Shows Leucine-Rich Repeat Motif Involvement as in TLR9-CpG DNA Interactions.International journal of molecular sciences · 2023Article
- The Inhibitory Effects and Cytotoxic Activities of the Stem Extract ofPlants (Basel, Switzerland) · 2023Article
- WHIRLY1 Acts Upstream of ABA-Related Reprogramming of Drought-Induced Gene Expression in Barley and Affects Stress-Related Histone Modifications.International journal of molecular sciences · 2023Article
- Unravelling How Single-Stranded DNA Binding Protein Coordinates DNA Metabolism Using Single-Molecule Approaches.International journal of molecular sciences · 2023Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Single-stranded DNA (ssDNA) binding proteins (SSBs) are critical in maintaining genome stability by protecting the transient existence of ssDNA from damage during essential biological processes, such as DNA replication and gene transcription. The single-stranded region of telomeres also requires protection by ssDNA binding proteins from being attacked in case it is wrongly recognized as an anomaly. In addition to their critical roles in genome stability and integrity, it has been demonstrated that ssDNA and SSB-ssDNA interactions play critical roles in transcriptional regulation in all three domains of life and viruses. In this review, we present our current knowledge of the structure and function of SSBs and the structural features for SSB binding specificity. We then discuss the machine learning-based approaches that have been developed for the prediction of SSBs from double-stranded DNA (dsDNA) binding proteins (DSBs).
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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.