Biodata Mining

Papers
(The H4-Index of Biodata Mining is 16. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-06-01 to 2025-06-01.)
ArticleCitations
MOCAT: multi-omics integration with auxiliary classifiers enhanced autoencoder305
Transcriptome-based network analysis related to regulatory T cells infiltration identified RCN1 as a potential biomarker for prognosis in clear cell renal cell carcinoma230
A new pipeline for structural characterization and classification of RNA-Seq microbiome data52
Investigating potential drug targets for IgA nephropathy and membranous nephropathy through multi-queue plasma protein analysis: a Mendelian randomization study based on SMR and co-localization analys42
Correction: Detection and classification of long terminal repeat sequences in plant LTR-retrotransposons and their analysis using explainable machine learning40
Processing imbalanced medical data at the data level with assisted-reproduction data as an example39
Deep joint learning diagnosis of Alzheimer’s disease based on multimodal feature fusion30
Comparing new tools of artificial intelligence to the authentic intelligence of our global health students25
Unsupervised clustering based coronary artery segmentation22
Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient22
Machine learning approaches to identify systemic lupus erythematosus in anti-nuclear antibody-positive patients using genomic data and electronic health records22
Polygenic risk modeling of tumor stage and survival in bladder cancer21
Neural network methods for diagnosing patient conditions from cardiopulmonary exercise testing data20
Ten simple rules for providing bioinformatics support within a hospital19
Colorectal cancer subtype identification from differential gene expression levels using minimalist deep learning18
Decoding dynamic miRNA:ceRNA interactions unveils therapeutic insights and targets across predominant cancer landscapes17
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