Citation sources

Updated weekly. Details via Crossref
Crossref Scopus Google Scholar
16 14 Search
2025
Artificial Intelligence for Molecular Biology
2025
Artificial Intelligence for Molecular Biology
2025
DNA sequence analysis landscape: a comprehensive review of DNA sequence analysis task types, databases, datasets, word embedding methods, and language models
Frontiers in Medicine
2024
2024 IEEE International Symposium on Circuits and Systems (ISCAS)
2024
PSATF-6mA: an integrated learning fusion feature-encoded DNA-6 mA methylcytosine modification site recognition model based on attentional mechanisms
Frontiers in Genetics
2023
ELMo4m6A: A Contextual Language Embedding-Based Predictor for Detecting RNA N6-Methyladenosine Sites
IEEE/ACM Transactions on Computational Biology and Bioinformatics
2023
M6A-BERT-Stacking: A Tissue-Specific Predictor for Identifying RNA N6-Methyladenosine Sites Based on BERT and Stacking Strategy
Symmetry
2023
CNN6mA: Interpretable neural network model based on position-specific CNN and cross-interactive network for 6mA site prediction
Computational and Structural Biotechnology Journal
2023
DNA-MP: a generalized DNA modifications predictor for multiple species based on powerful sequence encoding method
Briefings in Bioinformatics
2023
Time series-based hybrid ensemble learning model with multivariate multidimensional feature coding for DNA methylation prediction
BMC Genomics
2023
DeepMethylation: a deep learning based framework with GloVe and Transformer encoder for DNA methylation prediction
PeerJ
2022
Deep6mAPred: A CNN and Bi-LSTM-based deep learning method for predicting DNA N6-methyladenosine sites across plant species
Methods
2022
BERT6mA: prediction of DNA N6-methyladenine site using deep learning-based approaches
Briefings in Bioinformatics
2022
MGF6mARice: prediction of DNA N6-methyladenine sites in rice by exploiting molecular graph feature and residual block
Briefings in Bioinformatics
2022
2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Additional cited-by details will be shown when available from Crossref