| Prevalence of malnutrition in patients at first medical oncology visit: the PreMiO study M Muscaritoli, S Lucia, A Farcomeni, V Lorusso, V Saracino, C Barone, ... Oncotarget 8 (45), 79884, 2017 | 477 | 2017 |
| Genome‐wide linkage analysis for human longevity: Genetics of Healthy Aging Study M Beekman, H Blanché, M Perola, A Hervonen, V Bezrukov, E Sikora, ... Aging cell 12 (2), 184-193, 2013 | 215 | 2013 |
| Introduction to clustering P Giordani, MB Ferraro, F Martella, P Giordani, MB Ferraro, F Martella An Introduction to Clustering with R, 3-5, 2020 | 97 | 2020 |
| A biclustering approach to university performances: an Italian case study V Raponi, F Martella, A Maruotti Journal of Applied Statistics 43 (1), 31-45, 2016 | 38 | 2016 |
| Classification of microarray data with factor mixture models F Martella Bioinformatics 22 (2), 202-208, 2006 | 34 | 2006 |
| Biclustering of gene expression data by an extension of mixtures of factor analyzers F Martella, M Alfo, M Vichi The international journal of biostatistics 4 (1), 2008 | 32 | 2008 |
| Hierarchical clustering P Giordani, MB Ferraro, F Martella, P Giordani, MB Ferraro, F Martella An Introduction to Clustering with R, 9-73, 2020 | 26* | 2020 |
| Dynamic mixtures of factor analyzers to characterize multivariate air pollutant exposures A Maruotti, J Bulla, F Lagona, M Picone, F Martella | 25 | 2017 |
| Classifying and mapping potential distribution of forest types using a finite mixture model F Attorre, F Francesconi, M De Sanctis, M Alfò, F Martella, R Valenti, ... Folia Geobotanica 49, 313-335, 2014 | 22 | 2014 |
| Dimensions of well-being and their statistical measurements C Ferrara, F Martella, M Vichi Topics in theoretical and applied statistics, 85-99, 2016 | 18 | 2016 |
| Clustering microarray data using model-based double K-means F Martella, M Vichi Journal of Applied Statistics 39 (9), 1853-1869, 2012 | 14 | 2012 |
| Finite mixture clustering of human tissues with different levels of IGF-1 splice variants mRNA transcripts M Pelosi, M Alfò, F Martella, E Pappalardo, A Musarò BMC bioinformatics 16, 1-17, 2015 | 12 | 2015 |
| Hierarchical mixture models for biclustering in microarray data F Martella, M Alfò, M Vichi Statistical Modelling 11 (6), 489-505, 2011 | 11 | 2011 |
| Probabilistic disjoint principal component analysis C Ferrara, F Martella, M Vichi Multivariate Behavioral Research 54 (1), 47-61, 2019 | 9 | 2019 |
| A finite mixture approach to joint clustering of individuals and multivariate discrete outcomes F Martella, M Alfò Journal of Statistical Computation and Simulation 87 (11), 2186-2206, 2017 | 9 | 2017 |
| Finite mixtures of latent trait analyzers with concomitant variables for bipartite networks: an analysis of COVID-19 data D Failli, MF Marino, F Martella Multivariate Behavioral Research 59 (4), 801-817, 2024 | 8 | 2024 |
| A mixture model with random‐effects components for classifying sibling pairs F Martella, JK Vermunt, M Beekman, RGJ Westendorp, PE Slagboom, ... Statistics in medicine 30 (27), 3252-3264, 2011 | 8 | 2011 |
| Partitioning predictors in multivariate regression models F Martella, D Vicari, M Vichi Statistics and Computing 25, 261-272, 2015 | 7 | 2015 |
| datasetsICR: Datasets from the Book “An Introduction to Clustering with R”, R package version 1.0 (2020) P Giordani, MB Ferraro, F Martella | 7 | |
| Biclustering multivariate discrete longitudinal data M Alfó, MF Marino, F Martella Statistics and Computing 34 (1), 42, 2024 | 5 | 2024 |
