Entropy-based gene ranking without selection bias for the predictive classification of microarray data
2003-01-01 Furlanello, Cesare; Serafini, Maria; Merler, Stefano; Jurman, Giuseppe
Control of selection bias in microarray data analysis
2003-01-01 Furlanello, C; Serafini, M; Merler, S; Jurman, G
Quantification of the Immune Content in Neuroblastoma: Deep Learning and Topological Data Analysis in Digital Pathology
2021-01-01 Bussola, Nicole; Papa, Bruno; Melaiu, Ombretta; Castellano, Aurora; Fruci, Doriana; Jurman, Giuseppe
Giovani e ricerca: il progetto WebValley
2011-01-01 Furlanello, Cesare; De Filippi, Riccardo; Dolci, Claudia; Jurman, Giuseppe
Metric projection for dynamic multiplex networks
2016-01-01 Jurman, Giuseppe
Graded Lie algebras of maximal class, III
2005-01-01 Jurman, Giuseppe
A family of simple Lie algebras in characteristic two
2004-01-01 Jurman, Giuseppe
Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes
2010-01-01 Shi, W; Bessarabova, M; Dosymbekov, D; Dezso, Z; Nikolskaya, T; Dudoladova, M; Serebryiskaya, T; Bugrim, A; Guryanov, A; Brennan, Rj; Shah, R; Dopazo, J; Chen, M; Deng, Y; Shi, T; Jurman, G; Furlanello, C; Thomas, Rs; Corton, Jc; Tong, W; Shi, L; Nikolsky, Y
Terminated Ramp - Support Vector Machine: a nonparametric data dependent kernel
2006-01-01 Merler, Stefano; Jurman, Giuseppe
Algebraic stability indicators for ranked lists in molecular profiling
2008-01-01 Jurman, G; Merler, S; Barla, A; Paoli, S; Galea, A; Furlanello, C
Targeted proteomics and the presence of carotid plaques in subjects at low cardiovascular disease risk
2023-01-01 Baragetti, A.; Grigore, L.; Pellegatta, F.; Mattavelli, E.; Chierici, M.; Jurman, G.; Catapano, A.
A grid environment for high-throughput proteomics
2007-01-01 M., Cannataro; A., Barla; Flor, Roberto; A., Gallo; Jurman, Giuseppe; Merler, Stefano; Paoli, Silvano; G., Tradigo; P., Veltri; Furlanello, Cesare
A comparison of MCC and CEN error measures in multi-class prediction
2012-01-01 Jurman, G; Riccadonna, S; Furlanello, C
PD-L1 is a therapeutic target of the Bromodomain inhibitor JQ1 and, combined with HLA class I, a promising prognostic biomarker in neuroblastoma
2017-01-01 Melaiu, Ombretta; Mina, Marco; Chierici, Marco; Boldrini, Renata; Jurman, Giuseppe; Romania, Paolo; D'Alicandro, Valerio; Benedetti, Maria Chiara; Castellano, Aurora; Liu, Tao; Furlanello, Cesare; Locatelli, Franco; Fruci, Doriana
A machine learning pipeline for quantitative phenotype prediction from genotype data
2010-01-01 Guzzetta, G; Jurman, G; Furlanello, C
Quantification of the Immune Content in Neuroblastoma: Deep Learning and Topological Data Analysis in Digital Pathology
2021-01-01 Bussola, Nicole; Papa, Bruno; Melaiu, Ombretta; Castellano, Aurora; Fruci, Doriana; Jurman, Giuseppe
Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review
2012-01-01 R., Sanz Pamplona; A., Berenguer; D., Cordero; Riccadonna, Samantha; X., Sole'; M., Crous Bou; E., Guino'; X., Sanjuan; S., Biondo; A., Soriano; Jurman, Giuseppe; G., Capella; Furlanello, Cesare; V., Moreno
A grid environment for high-throughput proteomics
2007-01-01 Cannataro, M; Barla, A; Flor, R; Jurman, G; Merler, S; Paoli, S; Tradigo, G; Veltri, P; Furlanello, C
Seasonal Linear Predictivity in National Football Championships
2019-01-01 Jurman, Giuseppe
Application of Artificial Intelligence in Targeting Retinal Diseases
2020-01-01 Saverio Sorrentino, Francesco; Jurman, Giuseppe; De Nadai, Katia; Campa, Claudio; Furlanello, Cesare; Parmeggiani, Francesco
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| Entropy-based gene ranking without selection bias for the predictive classification of microarray data | 1-gen-2003 | Furlanello, Cesare; Serafini, Maria; Merler, Stefano; Jurman, Giuseppe | |
| Control of selection bias in microarray data analysis | 1-gen-2003 | Furlanello, C; Serafini, M; Merler, S; Jurman, G | |
| Quantification of the Immune Content in Neuroblastoma: Deep Learning and Topological Data Analysis in Digital Pathology | 1-gen-2021 | Bussola, Nicole; Papa, Bruno; Melaiu, Ombretta; Castellano, Aurora; Fruci, Doriana; Jurman, Giuseppe | |
| Giovani e ricerca: il progetto WebValley | 1-gen-2011 | Furlanello, Cesare; De Filippi, Riccardo; Dolci, Claudia; Jurman, Giuseppe | |
| Metric projection for dynamic multiplex networks | 1-gen-2016 | Jurman, Giuseppe | |
| Graded Lie algebras of maximal class, III | 1-gen-2005 | Jurman, Giuseppe | |
| A family of simple Lie algebras in characteristic two | 1-gen-2004 | Jurman, Giuseppe | |
| Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes | 1-gen-2010 | Shi, W; Bessarabova, M; Dosymbekov, D; Dezso, Z; Nikolskaya, T; Dudoladova, M; Serebryiskaya, T; Bugrim, A; Guryanov, A; Brennan, Rj; Shah, R; Dopazo, J; Chen, M; Deng, Y; Shi, T; Jurman, G; Furlanello, C; Thomas, Rs; Corton, Jc; Tong, W; Shi, L; Nikolsky, Y | |
| Terminated Ramp - Support Vector Machine: a nonparametric data dependent kernel | 1-gen-2006 | Merler, Stefano; Jurman, Giuseppe | |
| Algebraic stability indicators for ranked lists in molecular profiling | 1-gen-2008 | Jurman, G; Merler, S; Barla, A; Paoli, S; Galea, A; Furlanello, C | |
| Targeted proteomics and the presence of carotid plaques in subjects at low cardiovascular disease risk | 1-gen-2023 | Baragetti, A.; Grigore, L.; Pellegatta, F.; Mattavelli, E.; Chierici, M.; Jurman, G.; Catapano, A. | |
| A grid environment for high-throughput proteomics | 1-gen-2007 | M., Cannataro; A., Barla; Flor, Roberto; A., Gallo; Jurman, Giuseppe; Merler, Stefano; Paoli, Silvano; G., Tradigo; P., Veltri; Furlanello, Cesare | |
| A comparison of MCC and CEN error measures in multi-class prediction | 1-gen-2012 | Jurman, G; Riccadonna, S; Furlanello, C | |
| PD-L1 is a therapeutic target of the Bromodomain inhibitor JQ1 and, combined with HLA class I, a promising prognostic biomarker in neuroblastoma | 1-gen-2017 | Melaiu, Ombretta; Mina, Marco; Chierici, Marco; Boldrini, Renata; Jurman, Giuseppe; Romania, Paolo; D'Alicandro, Valerio; Benedetti, Maria Chiara; Castellano, Aurora; Liu, Tao; Furlanello, Cesare; Locatelli, Franco; Fruci, Doriana | |
| A machine learning pipeline for quantitative phenotype prediction from genotype data | 1-gen-2010 | Guzzetta, G; Jurman, G; Furlanello, C | |
| Quantification of the Immune Content in Neuroblastoma: Deep Learning and Topological Data Analysis in Digital Pathology | 1-gen-2021 | Bussola, Nicole; Papa, Bruno; Melaiu, Ombretta; Castellano, Aurora; Fruci, Doriana; Jurman, Giuseppe | |
| Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review | 1-gen-2012 | R., Sanz Pamplona; A., Berenguer; D., Cordero; Riccadonna, Samantha; X., Sole'; M., Crous Bou; E., Guino'; X., Sanjuan; S., Biondo; A., Soriano; Jurman, Giuseppe; G., Capella; Furlanello, Cesare; V., Moreno | |
| A grid environment for high-throughput proteomics | 1-gen-2007 | Cannataro, M; Barla, A; Flor, R; Jurman, G; Merler, S; Paoli, S; Tradigo, G; Veltri, P; Furlanello, C | |
| Seasonal Linear Predictivity in National Football Championships | 1-gen-2019 | Jurman, Giuseppe | |
| Application of Artificial Intelligence in Targeting Retinal Diseases | 1-gen-2020 | Saverio Sorrentino, Francesco; Jurman, Giuseppe; De Nadai, Katia; Campa, Claudio; Furlanello, Cesare; Parmeggiani, Francesco |
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