OOIR: Observatory of International Research

Papers

(The TQCC of Biodata Mining is 4. 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 2021-04-01 to 2025-04-01.)

Article	Citations
Correction: Predictive modeling of ALS progression: an XGBoost approach using clinical features	258
Transcriptome- and DNA methylation-based cell-type deconvolutions produce similar estimates of differential gene expression and differential methylation	189
QIGTD: identifying critical genes in the evolution of lung adenocarcinoma with tensor decomposition	46
A deep learning approach for classifying and predicting children's nutritional status in Ethiopia using LSTM-FC neural networks	39
Processing imbalanced medical data at the data level with assisted-reproduction data as an example	39
Saliency-driven explainable deep learning in medical imaging: bridging visual explainability and statistical quantitative analysis	34
Neural network-based prognostic predictive tool for gastric cardiac cancer: the worldwide retrospective study	28
Modeling heterogeneity of Sudanese hospital stay in neonatal and maternal unit: non-parametric random effect models with Gamma distribution	23
An unsupervised image segmentation algorithm for coronary angiography	22
Correction: Detection and classification of long terminal repeat sequences in plant LTR-retrotransposons and their analysis using explainable machine learning	22
Machine learning and statistical approaches for classification of risk of coronary artery disease using plasma cytokines	20
A new pipeline for structural characterization and classification of RNA-Seq microbiome data	19
A maximum flow-based network approach for identification of stable noncoding biomarkers associated with the multigenic neurological condition, autism	18
Taxonomy-based data representation for data mining: an example of the magnitude of risk associated with H. pylori infection	14
LoFTK: a framework for fully automated calculation of predicted Loss-of-Function variants and genes	13
Machine learning based study for the classification of Type 2 diabetes mellitus subtypes	13
Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods	10
Ensemble feature selection and tabular data augmentation with generative adversarial networks to enhance cutaneous melanoma identification and interpretability	10
Exploring glioma heterogeneity through omics networks: from gene network discovery to causal insights and patient stratification	9
Deep joint learning diagnosis of Alzheimer’s disease based on multimodal feature fusion	9
Interaction models matter: an efficient, flexible computational framework for model-specific investigation of epistasis	9
Transcriptome-based network analysis related to regulatory T cells infiltration identified RCN1 as a potential biomarker for prognosis in clear cell renal cell carcinoma	9
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 analys	9
Reference-free phylogeny from sequencing data	9
Development of glaucoma predictive model and risk factors assessment based on supervised models	8

A new challenge for data analytics: transposons	8
Deciphering the tissue-specific functional effect of Alzheimer risk SNPs with deep genome annotation	8
Open challenges and opportunities in federated foundation models towards biomedical healthcare	8
eQTpLot: a user-friendly R package for the visualization of colocalization between eQTL and GWAS signals	7
Machine learning approaches for the genomic prediction of rheumatoid arthritis and systemic lupus erythematosus	7
Prescription pattern analysis of Type 2 Diabetes Mellitus: a cross-sectional study in Isfahan, Iran	6
Electronic medical records imputation by temporal Generative Adversarial Network	6
Detection of iron deficiency anemia by medical images: a comparative study of machine learning algorithms	6
Unsupervised clustering based coronary artery segmentation	6
iU-Net: a hybrid structured network with a novel feature fusion approach for medical image segmentation	6
MOCAT: multi-omics integration with auxiliary classifiers enhanced autoencoder	6
Novel digital approaches to the assessment of problematic opioid use	5
mSRFR: a machine learning model using microalgal signature features for ncRNA classification	5
Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient	5
iGlioSub: an integrative transcriptomic and epigenomic classifier for glioblastoma molecular subtypes	5
Learning and visualizing chronic latent representations using electronic health records	5
Polygenic risk modeling of tumor stage and survival in bladder cancer	5
Inferring protein from transcript abundances using convolutional neural networks	5
Evaluating risk detection methods to uncover ontogenic-mediated adverse drug effect mechanisms in children	5
Machine learning approaches to identify systemic lupus erythematosus in anti-nuclear antibody-positive patients using genomic data and electronic health records	5
Humans and machines in biomedical knowledge curation: hypertrophic cardiomyopathy molecular mechanisms’ representation	5
6mA-StackingCV: an improved stacking ensemble model for predicting DNA N6-methyladenine site	4
DIVIS: a semantic DIstance to improve the VISualisation of heterogeneous phenotypic datasets	4
Unsupervised encoding selection through ensemble pruning for biomedical classification	4
Priority-Elastic net for binary disease outcome prediction based on multi-omics data	4
ParticleChromo3D: a Particle Swarm Optimization algorithm for chromosome 3D structure prediction from Hi-C data	4