| GASOLINE: a greedy and stochastic algorithm for optimal local multiple alignment of interaction networks G Micale, A Pulvirenti, R Giugno, A Ferro PLoS One 9 (6), e98750, 2014 | 35 | 2014 |
| SPECTRA: an integrated knowledge base for comparing tissue and tumor-specific PPI networks in human G Micale, A Ferro, A Pulvirenti, R Giugno Frontiers in bioengineering and biotechnology 3, 58, 2015 | 16 | 2015 |
| NetMatchStar: an enhanced Cytoscape network querying app F Rinnone, G Micale, V Bonnici, GD Bader, D Shasha, A Ferro, ... F1000Research 4, 2015 | 16 | 2015 |
| Fast analytical methods for finding significant labeled graph motifs G Micale, R Giugno, A Ferro, M Mongiovì, D Shasha, A Pulvirenti Data Mining and Knowledge Discovery 32 (2), 504-531, 2018 | 14 | 2018 |
| APPAGATO: an APproximate PArallel and stochastic GrAph querying TOol for biological networks V Bonnici, F Busato, G Micale, N Bombieri, A Pulvirenti, R Giugno Bioinformatics 32 (14), 2159-2166, 2016 | 11 | 2016 |
| GASOLINE: a Cytoscape app for multiple local alignment of PPI networks G Micale, A Continella, A Ferro, R Giugno, A Pulvirenti F1000Research 3, 2014 | 10 | 2014 |
| Proteins comparison through probabilistic optimal structure local alignment G Micale, A Pulvirenti, R Giugno, A Ferro Frontiers in genetics 5, 302, 2014 | 6 | 2014 |
| Fast methods for finding significant motifs on labelled multi-relational networks G Micale, A Pulvirenti, A Ferro, R Giugno, D Shasha Journal of Complex Networks 7 (6), 817-837, 2019 | 4 | 2019 |
| Simple pattern-only heuristics lead to fast subgraph matching strategies on very large networks A Aparo, V Bonnici, G Micale, A Ferro, D Shasha, A Pulvirenti, R Giugno International Conference on Practical Applications of Computational Biology …, 2018 | 4 | 2018 |
| glabtrie: A data structure for motif discovery with constraints M Mongioví, G Micale, A Ferro, R Giugno, A Pulvirenti, D Shasha Graph Data Management, 71-95, 2018 | 4 | 2018 |
| Mining and ranking of generalized multi-dimensional frequent subgraphs A Petermann, G Micale, G Bergami, A Pulvirenti, E Rahm 2017 Twelfth International Conference on Digital Information Management …, 2017 | 3 | 2017 |
| SSRN Quick Links S Rankings | 3 | |
| Fast subgraph matching strategies based on pattern-only heuristics A Aparo, V Bonnici, G Micale, A Ferro, D Shasha, A Pulvirenti, R Giugno Interdisciplinary Sciences: Computational Life Sciences 11 (1), 21-32, 2019 | 2 | 2019 |
| Multiri: Fast subgraph matching in labeled multigraphs G Micale, V Bonnici, A Ferro, D Shasha, R Giugno, A Pulvirenti arXiv preprint arXiv:2003.11546, 2020 | 1 | 2020 |
| Computational Methods to Investigate the Impact of miRNAs on Pathways S Alaimo, G Micale, A La Ferlita, A Ferro, A Pulvirenti MicroRNA Target Identification, 183-209, 2019 | 1 | 2019 |
| INBIA: a boosting methodology for proteomic network inference DS Sardina, G Micale, A Ferro, A Pulvirenti, R Giugno BMC bioinformatics 19 (7), 77-88, 2018 | 1 | 2018 |
| Correlation between proteomic network inference and protein-protein interaction networks DS Sardina, G Micale, A Ferro, A Pulvirenti, R Giugno Proc. 13th International Conferenceon on Computational Intelligence Methods …, 2016 | 1 | 2016 |
| TemporalRI: A Subgraph Isomorphism Algorithm for Temporal Networks G Locicero, G Micale, A Pulvirenti, A Ferro International Conference on Complex Networks and Their Applications, 675-687, 2020 | | 2020 |
| Establish the expected number of induced motifs on unlabeled graphs through analytical models E Martorana, G Micale, A Ferro, A Pulvirenti Applied Network Science 5 (1), 1-23, 2020 | | 2020 |
| Establish the Expected Number of Injective Motifs on Unlabeled Graphs Through Analytical Models E Martorana, G Micale, A Ferro, A Pulvirenti International Conference on Complex Networks and Their Applications, 255-267, 2019 | | 2019 |
