ArticleScientific reports2021
Prediction of PCR amplification from primer and template sequences using recurrent neural network.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 30 citations in OpenAlex.
- Detection of Microorganisms Causing Human Respiratory Infection Using One-Tube Multiplex PCR.Infectious disease reports · 2025Article
- The Evolution of Nucleic Acid-Based Diagnosis Methods from the (pre-)CRISPR to CRISPR era and the Associated Machine/Deep Learning Approaches in Relevant RNA Design.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Article
- A computational framework to improve cross-platform implementation of transcriptomics signatures.EBioMedicine · 2024Review
- Efficient DNA Coding Algorithm for Polymerase Chain Reaction Amplification Information Retrieval.International journal of molecular sciences · 2024Article
- DeGenPrime provides robust primer design and optimization unlocking the biosphere.Bioinformatics advances · 2024Article
- High throughput human genotyping for variants associated with malarial disease outcomes using custom targeted amplicon sequencing.Scientific reports · 2023Article
- Article
- Identifying immunodominant multi-epitopes from the envelope glycoprotein of the Lassa mammarenavirus as vaccine candidate for Lassa fever.Clinical and experimental vaccine research · 2022Article
- AI-aided on-chip nucleic acid assay for smart diagnosis of infectious disease.Fundamental research · 2022Article
- Designing highly multiplex PCR primer sets with Simulated Annealing Design using Dimer Likelihood Estimation (SADDLE).Nature communications · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We have developed a novel method to predict the success of PCR amplification for a specific primer set and DNA template based on the relationship between the primer sequence and the template. To perform the prediction using a recurrent neural network, the usual double-stranded formation between the primer and template nucleotide sequences was herein expressed as a five-lettered word. The set of words (pseudo-sentences) was placed to indicate the success or failure of PCR targeted to learn recurrent neural network (RNN). After learning pseudo-sentences, RNN predicted PCR results from pseudo-sentences which were created by primer and template sequences with 70% accuracy. These results suggest that PCR results could be predicted using learned RNN and the trained RNN could be used as a replacement for preliminary PCR experimentation. This is the first report which utilized the application of neural network for primer design and prediction of PCR results.
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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.