ArticleMolecular therapy. Nucleic acids2019
SDM6A: A Web-Based Integrative Machine-Learning Framework for Predicting 6mA Sites in the Rice Genome.
Article in Molecular therapy. Nucleic acids, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 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
55 citing papers in PubMed, 159 citations in OpenAlex.
- Deep learning-based identification of N6-methyladenine sites via hybrid feature fusion and SHAP-driven feature selection.Scientific reports · 2026Article
- iDNA-DAPHA: a generic framework for methylation prediction via domain-adaptive pretraining and hierarchical attention.Briefings in bioinformatics · 2025Article
- Identification of DNA N6-methyladenine modifications in the rice genome with a fine-tuned large language model.Frontiers in plant science · 2025Article
- FSFT6mA: a feature-synthesis fine-tuning framework for DNA 6mA site prediction.Frontiers in genetics · 2025Article
- DeepRice6mA: A convolutional neural network approach for 6mA site prediction in the rice Genome.PloS one · 2025Article
- Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approach.Briefings in bioinformatics · 2023Article
- DLC-ac4C: A Prediction Model for N4-acetylcytidine Sites in Human mRNA Based on DenseNet and Bidirectional LSTM Methods.Current genomics · 2023Article
- MLACNN: an attention mechanism-based CNN architecture for predicting genome-wide DNA methylation.Theory in biosciences = Theorie in den Biowissenschaften · 2023Article
- Prediction of DNA Methylation based on Multi-dimensional feature encoding and double convolutional fully connected convolutional neural network.PLoS computational biology · 2023Article
- EMDL-ac4C: identifying N4-acetylcytidine based on ensemble two-branch residual connection DenseNet and attention.Frontiers in genetics · 2023Article
- MethSemble-6mA: an ensemble-based 6mA prediction server and its application on promoter region of LBD gene family in Poaceae.Frontiers in plant science · 2023Article
- 4acCPred: Weakly supervised prediction ofMolecular therapy. Nucleic acids · 2022Article
- Deep polygenic neural network for predicting and identifying yield-associated genes in Indonesian rice accessions.Scientific reports · 2022Article
- Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy.Molecular therapy : the journal of the American Society of Gene Therapy · 2022Article
- TACOS: a novel approach for accurate prediction of cell-specific long noncoding RNAs subcellular localization.Briefings in bioinformatics · 2022Article
- BERT6mA: prediction of DNA N6-methyladenine site using deep learning-based approaches.Briefings in bioinformatics · 2022Article
- Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2.Briefings in bioinformatics · 2022Article
- STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction.Briefings in bioinformatics · 2022Article
- Using k-mer embeddings learned from a Skip-gram based neural network for building a cross-species DNA N6-methyladenine site prediction model.Plant molecular biology · 2021Article
- Leveraging the attention mechanism to improve the identification of DNA N6-methyladenine sites.Briefings in bioinformatics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
DNA N
Indexed as
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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.