| Advanced methods and tools for ECG data analysis GD Clifford, F Azuaje Artech house, 2006 | 1116 | 2006 |
| Cluster validation techniques for genome expression data N Bolshakova, F Azuaje Signal processing 83 (4), 825-833, 2003 | 486 | 2003 |
| Multiple SVM-RFE for gene selection in cancer classification with expression data KB Duan, JC Rajapakse, H Wang, F Azuaje IEEE transactions on nanobioscience 4 (3), 228-234, 2005 | 469 | 2005 |
| Stem cell-associated heterogeneity in Glioblastoma results from intrinsic tumor plasticity shaped by the microenvironment A Dirkse, A Golebiewska, T Buder, PV Nazarov, A Muller, S Poovathingal, ... Nature communications 10 (1), 1-16, 2019 | 351 | 2019 |
| Use of circulating microRNAs to diagnose acute myocardial infarction Y Devaux, M Vausort, E Goretti, PV Nazarov, F Azuaje, G Gilson, ... Clinical chemistry 58 (3), 559-567, 2012 | 307 | 2012 |
| ECG statistics, noise, artifacts, and missing data GD Clifford, F Azuaje, P Mcsharry Advanced methods and tools for ECG data analysis 6 (1), 18, 2006 | 210 | 2006 |
| An assessment of recently published gene expression data analyses: reporting experimental design and statistical factors P Jafari, F Azuaje BMC Medical Informatics and Decision Making 6 (1), 1-8, 2006 | 204 | 2006 |
| Gene expression correlation and gene ontology-based similarity: an assessment of quantitative relationships H Wang, F Azuaje, O Bodenreider, J Dopazo 2004 Symposium on Computational Intelligence in Bioinformatics and …, 2004 | 195 | 2004 |
| Solutions to instability problems with sequential wrapper-based approaches to feature selection K Dunne, P Cunningham, F Azuaje Journal of Machine Learning Research 1, 22, 2002 | 180 | 2002 |
| Computational models for predicting drug responses in cancer research F Azuaje Briefings in bioinformatics 18 (5), 820-829, 2017 | 167 | 2017 |
| Single‐cell transcriptomics reveals distinct inflammation‐induced microglia signatures C Sousa, A Golebiewska, SK Poovathingal, T Kaoma, Y Pires‐Afonso, ... EMBO reports 19 (11), e46171, 2018 | 164 | 2018 |
| Ontology-driven similarity approaches to supporting gene functional assessment F Azuaje, H Wang, O Bodenreider Proceedings of the ISMB’2005 SIG meeting on Bio-ontologies 2005, 9-10, 2005 | 134 | 2005 |
| A cluster validity framework for genome expression data F Azuaje Bioinformatics 18 (2), 319-320, 2002 | 127 | 2002 |
| Permutation–based statistical tests for multiple hypotheses A Camargo, F Azuaje, H Wang, H Zheng Source code for biology and medicine 3 (1), 1-8, 2008 | 102 | 2008 |
| Databases for lncRNAs: a comparative evaluation of emerging tools S Fritah, SP Niclou, F Azuaje Rna 20 (11), 1655-1665, 2014 | 97 | 2014 |
| A knowledge-driven approach to cluster validity assessment N Bolshakova, F Azuaje, P Cunningham Bioinformatics 21 (10), 2546-2547, 2005 | 84 | 2005 |
| An integrated tool for microarray data clustering and cluster validity assessment N Bolshakova, F Azuaje, P Cunningham Proceedings of the 2004 ACM symposium on Applied computing, 133-137, 2004 | 83 | 2004 |
| Artificial intelligence for precision oncology: beyond patient stratification F Azuaje NPJ precision oncology 3 (1), 1-5, 2019 | 82 | 2019 |
| Molecular crosstalk between tumour and brain parenchyma instructs histopathological features in glioblastoma S Bougnaud, A Golebiewska, A Oudin, O Keunen, PN Harter, L Mäder, ... Oncotarget 7 (22), 31955, 2016 | 79 | 2016 |
| A computational neural approach to support the discovery of gene function and classes of cancer F Azuaje IEEE Transactions on biomedical engineering 48 (3), 332-339, 2001 | 77 | 2001 |
