Giuseppina C Gini
TitoloCitata daAnno
An EMG-controlled exoskeleton for hand rehabilitation
M Mulas, M Folgheraiter, G Gini
9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005 …, 2005
Computational predictive programs (expert systems) in toxicology
E Benfenati, G Gini
Toxicology 119 (3), 213-225, 1997
QSAR as a random event: Modeling of nanoparticles uptake in PaCa2 cancer cells
AA Toropov, AP Toropova, T Puzyn, E Benfenati, G Gini, D Leszczynska, ...
Chemosphere 92 (1), 31-37, 2013
Predicting logP of pesticides using different software
E Benfenati, G Gini, N Piclin, A Roncaglioni, MR Varı
Chemosphere 53 (9), 1155-1164, 2003
CORAL: Quantitative structure–activity relationship models for estimating toxicity of organic compounds in rats
AP Toropova, AA Toropov, E Benfenati, G Gini, D Leszczynska, ...
Journal of Computational Chemistry 32 (12), 2727-2733, 2011
Predictive carcinogenicity: a model for aromatic compounds, with nitrogen-containing substituents, based on molecular descriptors using an artificial neural network
G Gini, M Lorenzini, E Benfenati, P Grasso, M Bruschi
Journal of chemical information and computer sciences 39 (6), 1076-1080, 1999
Novel application of the CORAL software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli
AA Toropov, AP Toropova, E Benfenati, G Gini, T Puzyn, D Leszczynska, ...
Chemosphere 89 (9), 1098-1102, 2012
An open source multistep model to predict mutagenicity from statistical analysis and relevant structural alerts
T Ferrari, G Gini
Chemistry Central Journal 4 (1), S2, 2010
Towards automatic error recovery in robot programs
M Gini, G Gini
Methods and Tools for Computer Integrated Manufacturing, 411-416, 1984
Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction
T Ferrari, D Cattaneo, G Gini, NG Bakhtyari, A Manganaro, E Benfenati
SAR and QSAR in Environmental Research 24 (5), 2013
Description of the electronic structure of organic chemicals using semiempirical and ab initio methods for development of toxicological QSARs
TI Netzeva, AO Aptula, E Benfenati, MTD Cronin, G Gini, I Lessigiarska, ...
Journal of chemical information and modeling 45 (1), 106-114, 2005
The importance of scaling in data mining for toxicity prediction
P Mazzatorta, E Benfenati, D Neagu, G Gini
Journal of chemical information and computer sciences 42 (5), 1250-1255, 2002
Robotic hands: design review and proposal of new design process
JWS Martell, G Gini
World Academy of Science, Engineering and Technology 26 (5), 85-90, 2007
CORAL: QSAR modeling of toxicity of organic chemicals towards Daphnia magna
AP Toropova, AA Toropov, SE Martyanov, E Benfenati, G Gini, ...
Chemometrics and Intelligent Laboratory Systems 110 (1), 177-181, 2012
Combining unsupervised and supervised artificial neural networks to predict aquatic toxicity
G Gini, MV Craciun, C König, E Benfenati
Journal of chemical information and computer sciences 44 (6), 1897-1902, 2004
Indoor robot navigation with single camera vision.
GC Gini, A Marchi
PRIS, 67-76, 2002
Exploratory study of computer integrated assembly systems
TO Binford, CR Lui, G Gini, M Gini, M M. Glaser, T Ishida, MS Mujtaba, ...
Progress Report 4, STAN-CS-76-568-4, AIM-285.4, Stanford University, 1977
Validation of counter propagation neural network models for predictive toxicology according to the OECD principles: a case study
M Vračko, V Bandelj, P Barbieri, E Benfenati, Q Chaudhry, M Cronin, ...
SAR and QSAR in Environmental Research 17 (3), 265-284, 2006
CORAL: Building up the model for bioconcentration factor and defining it’s applicability domain
AA Toropov, AP Toropova, A Lombardo, A Roncaglioni, E Benfenati, ...
European journal of medicinal chemistry 46 (4), 1400-1403, 2011
Co-evolutions of correlations for QSAR of toxicity of organometallic and inorganic substances: An unexpected good prediction based on a model that seems untrustworthy
AP Toropova, AA Toropov, E Benfenati, G Gini
Chemometrics and Intelligent Laboratory Systems 105 (2), 215-219, 2011
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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