NAPOLITANO, Francesco

NAPOLITANO, Francesco  

DIPARTIMENTO DI SCIENZE E TECNOLOGIE  

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Risultati 1 - 20 di 49 (tempo di esecuzione: 0.04 secondi).
Titolo Data di pubblicazione Autore(i) File
A scalable reference-point based algorithm to efficiently search large chemical databases 1-gen-2010 Napolitano, F.; Tagliaferri, R.; Baldi, P.
A siamese neural network model for the prioritization of metabolic disorders by integrating real and simulated data 1-gen-2020 Messa, G. M.; Napolitano, F.; Elsea, S. H.; di Bernardo, D.; Gao, X.
AI identifies potent inducers of breast cancer stem cell differentiation based on adversarial learning from gene expression data 1-gen-2024 Li, Zhongxiao; Napolitano, Antonella; Fedele, Monica; Gao, Xin; Napolitano, Francesco
Altered centriolar cohesion by CEP250 and appendages impact outcome of patients with pancreatic cancer 1-gen-2024 Giordano, Guido; Cipolletta, Giampiero; Mellone, Agostino; Puopolo, Giovanni; Coppola, Luigi; De Santis, Elena; Forte, Nicola; Napolitano, Francesco; Caruso, Francesca P; Parente, Paola; Landriscina, Matteo; Cerulo, Luigi; Costa, Maria Claudia; Pancione, Massimo
An adaptive reference point approach to efficiently search large chemical databases 1-gen-2014 Napolitano, F.; Tagliaferri, R.; Baldi, P.
An improved combinatorial biclustering algorithm 1-gen-2013 Nosova, E.; Napolitano, F.; Amato, R.; Cocozza, S.; Miele, G.; Raiconi, G.; Tagliaferri, R.
An interactive tool for data visualization and clustering 1-gen-2007 Iorio, F.; Miele, G.; Napolitano, F.; Raiconi, G.; Tagliaferri, R.
Automated counting of colony forming units using deep transfer learning from a model for congested scenes analysis 1-gen-2020 Albaradei, S. A.; Napolitano, F.; Uludag, M.; Thafar, M.; Napolitano, S.; Essack, M.; Bajic, V. B.; Gao, X.
Automatic identification of small molecules that promote cell conversion and reprogramming 1-gen-2021 Napolitano, F.; Rapakoulia, T.; Annunziata, P.; Hasegawa, A.; Cardon, M.; Napolitano, S.; Vaccaro, L.; Iuliano, A.; Wanderlingh, L. G.; Kasukawa, T.; Medina, D. L.; Cacchiarelli, D.; Gao, X.; di Bernardo, D.; Arner, E.
Bioinformatic pipelines in Python with Leaf 1-gen-2013 Napolitano, F.; Mariani-Costantini, R.; Tagliaferri, R.
Clustering and visualization approaches for human cell cycle gene expression data analysis 1-gen-2008 Napolitano, F.; Raiconi, G.; Tagliaferri, R.; Ciaramella, A; Staiano, A.; Miele, G.
Clustering, assessment and validation: An application to gene expression data 1-gen-2007 Ciaramella, A.; Cocozza, S.; Iorio, F.; Miele, G.; Napolitano, F.; Pinelli, M.; Raiconi, G.; Tagliaferri, R.
Comparing structural and transcriptional drug networks reveals signatures of drug activity and toxicity in transcriptional responses 1-gen-2017 Sirci, F.; Napolitano, F.; Pisonero-Vaquero, S.; Carrella, D.; Medina, D. L.; di Bernardo, D.
Computational Drug Networks: a computational approach to elucidate drug mode of action and to facilitate drug repositioning for neurodegenerative diseases 1-gen-2016 Sirci, F.; Napolitano, F.; di Bernardo, D.
Computer-aided drug repurposing for cancer therapy: Approaches and opportunities to challenge anticancer targets 1-gen-2019 Mottini, C.; Napolitano, F.; Li, Z.; Gao, X.; Cardone, L.
Consensus clustering in gene expression 1-gen-2015 Galdi, P.; Napolitano, F.; Tagliaferri, R.
Data Mining in Cancer Research 1-gen-2010 Lisboa Paulo, J. G.; Vellido, Alfredo; Tagliaferri, Roberto; Napolitano, Francesco; Ceccarelli, M; Martin Guerrero Jose, D.; Biganzoli, Elia
DATA VISUALIZATION AND CLUSTERING: AN APPLICATION TO GENE EXPRESSION DATA 1-gen-2007 Ciaramella, Angelo; Iorio, Francesco; Napolitano, Francesco; Raiconi, Giancarlo; Tagliaferri, Roberto; Miele, Gennaro; Staiano, Antonino
Distinctive gene expression profiles in Balb/3T3 cells exposed to low dose cobalt nanoparticles, microparticles and ions: potential nanotoxicological relevance 1-gen-2013 Perconti, S; Aceto, G M; Verginelli, F; Napolitano, F; Petrarca, C; Bernardini, G; Raiconi, G; Tagliaferri, R; Sabbioni, E; Di Gioacchino, M; Mariani-Costantini, R
Drug repositioning: A machine-learning approach through data integration 1-gen-2013 Napolitano, F.; Zhao, Y.; Moreira, V. M.; Tagliaferri, R.; Kere, J.; D'Amato, M.; Greco, D.