- M. Re, M. Mesiti and G. Valentini, A Fast Ranking Algorithm for Predicting Gene Functions in Biomolecular Networks, IEEE ACM Transactions on Computational Biology and Bioinformatics (in press)
- M. Re and G. Valentini, Random walking on functional interaction networks to rank genes involved in cancer 2nd Artificial Intelligence Applications in Biomedicine Workshop, in: L. Iliadis et al. (Eds) AIAI 2012 - Artificial Intelligence Applications and Innovations, pp. 66-75, IFIP AICT Series, Springer, 2012
- M. Re and G. Valentini, Cancer module genes ranking using kernelized score functions BMC Bioinformatics 13 (Suppl 14): S3, 2012.
- N. Cesa-Bianchi, M. Re, G. Valentini, Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference, Machine Learning, vol.88(1), pp. 209-241, 2012. Springer link
- M. Re, M. Mesiti, G.Valentini, Drug reposition through pharmacological spaces integration based on networks projection, EMBnet.journal, vol 18, Supplement A, pp.30-31, BITS 2012, Bioinformatics Italian Society Meeting, Catania, Italy, 2012.
- M. Frasca, A. Bertoni, G. Valentini, Regularized Network-Based Algorithm for Predicting Gene Functions with High-Imbalanced Data, EMBnet.journal, vol 18, Supplement A, pp.41,42, BITS 2012, Bioinformatics Italian Society Meeting, Catania, Italy, 2012.
- M. Re, G. Valentini, Large Scale Ranking and Repositioning of Drugs with Respect to DrugBank Therapeutic Categories, slides In: L. Bleris et al. (Eds.): International Symposium on Bioinformatics Research and Applications (ISBRA 2012), Dallas, USA, Lecture Notes in Bioinformatics vol.7292, pp. 225-236, Springer, 2012.
- A. Bertoni, M. Frasca, G. Valentini, COSNet: a Cost Sensitive Neural Network for Semi-supervised Learning in Graphs., In: "Machine Learning and Knowledge Discovery in Databases". European Conference, ECML PKDD 2011, Athens, Greece, Proceedings, Part I, Lecture Notes on Artificial Intelligence, vol. 6911, pp.219-234, Springer, 2011.
- M. Frasca, A. Bertoni, G. Valentini, A cost-sensitive neural algorithm to predict gene functions using large biological networks., Network Biology SIG: On the Analysis and Visualization of Networks in Biology, ISMB 2011, Wien
- A. Rozza, G. Lombardi, M. Re, E. Casiraghi, G. Valentini and P. Campadelli, A Novel Ensemble Technique for Protein Subcellular Location Prediction , In: "Ensembles in Machine Learning Applications", Studies in Computational Intelligence vol. 373, pp. 151-167, Springer, 2011.
- G. ValentiniTrue Path Rule hierarchical ensembles for genome-wide gene function prediction, IEEE ACM Transactions on Computational Biology and Bioinformatics, vol.8 n.3 pp. 832-847, 2011, IEEE CS Digital library
- M. Muselli, A. Bertoni, M. Frasca, A. Beghini, F. Ruffino, and G. ValentiniA mathematical model for the validation of gene selection methods, IEEE ACM Transactions on Computational Biology and Bioinformatics, vol.8 n.5 pp. 1385-1392, 2011, IEEE CS Digital library
- M. Re, G. ValentiniGenes prioritization with respect to Cancer Gene Modules using functional interaction network data , NETTAB 2011 Workshop on Clinical Bioinformatics, Pavia 12-14 October, 2011.
- A. Bertoni, M. Re, F. Sacca, G. Valentini Identification of promoter regions in genomic sequences by 1-dimensional constraint clustering, Frontiers in Artificial Intelligence and Applications, vol. 234, Neural Nets WIRN11 - Proceedings, pp. 162-169, 2011.
- N. Cesa-Bianchi, M. Re, G. Valentini, Functional Inference in FunCat through the Combination of Hierarchical Ensembles with Data Fusion Methods, ICML Workshop on learning from Multi-Label Data, Haifa, Israel, 2010
- M. Re, G. ValentiniNoise tolerance of Multiple Classifier Systems in data integration-based gene function prediction, Journal of Integrative Bioinformatics, 7(3):139, 2010
- M. Re, G. Valentini, Simple ensemble methods are competitive with state-of-the-art data integration methods for gene function prediction, Journal of Machine Learning Research, W&C Proceedings, vol.8: Machine Learning in Systems Biology, pp. 98-111, 2010
- N. Cesa-Bianchi, G. Valentini, Hierarchical cost-sensitive algorithms for genome-wide gene function prediction, Journal of Machine Learning Research, W&C Proceedings, vol.8: Machine Learning in Systems Biology, pp.14-29, 2010
- A. Rozza, G. Lombardi, M. Re, E. Casiraghi, and G. Valentini,DDAG K-TIPCAC: an ensemble method for protein subcellular localization Proc. of the Third Edition of ECML-SUEMA, pp. 75-84 Barcelona, Spain, 2010
- A. Bertoni, M. Frasca, G. Grossi, G. Valentini Learning functional linkage networks with a cost-sensitive approach , Proc. of WIRN 2010, IOS Press
- M. Re, G. ValentiniIntegration of heterogeneous data sources for gene function prediction using Decision Templates and ensembles of learning machines, Neurocomputing, 73:7-9 pp. 1533-37, 2010, Neurocomputing site
- M. Re, G. ValentiniAn experimental comparison of Hierarchical Bayes and True Path Rule ensembles for protein function prediction, In: Nineth International Workshop on Multiple Classifier Systems MCS 2010, Lecture Notes in Computer Science, vol. 5997, pp. 294-303, Springer, 2010
- M. Re, G. Valentini,Prediction of gene function using ensembles of SVMs and heterogeneous data sources, in: Applications of supervised and unsupervised ensemble methods, Computational Intelligence Series vol.245, pp. 79-91, Springer, 2010.
- M. Re, G. Pesole and D.S. Horner,Accurate discrimination of conserved coding and non-coding regions through multiple indicators of evolutionary dynamics, BMC Bioinformatics 10:282, 2009
- M. Mesiti, E. Jimenez-Ruiz, I. Sanz, R. Berlanga-Llavori, P. Perlasca, G. Valentini and D. Manset,XML-Based Approaches for the Integration of Heterogeneous Bio-Molecular Data, BMC Bioinformatics 10:(S12)S7, 2009
- M. Re, G. Pavesi , Detecting conserved coding genomic regions through signal processing of nucleotide substitution patterns, Artif Intell Med. 45(2-3):117-23, 2009
- R. Avogadri, M. Brioschi, F. Ferrazzi, M. Re, A. Beghini, and G. Valentini, A stability-based algorithm to validate hierarchical clusters of genes, International Journal of Knowledge Engineering and Soft Data Paradigms 1(4), pp. 318-330, 2009
- G.Valentini, R.Tagliaferri, F.Masulli, Computational Intelligence and Machine Learning in Bioinformatics, Artificial Intelligence in Medicine 45(2), pp. 91-96, 2009
- R. Avogadri, G.Valentini, Fuzzy ensemble clustering based on random projections for DNA microarray data analysis, Artificial Intelligence in Medicine 45(2), pp. 173-183, 2009
- G.Pavesi, G.Valentini, Classification of co-expressed genes from DNA regulatory regions, Information Fusion 10(3), pp. 233-241, 2009
- G. Valentini, M. Re, ,Weighted True Path Rule: a multilabel hierarchical algorithm for gene function prediction, ECML-MLD 2009, 1st International Workshop on learning from Multi-Label Data, Bled, Slovenia, pp. 133-146, 2009.
- M. Re, G. Valentini,Predicting gene expression from heterogeneous data, CIBB 2009, The Sixth International Conference on Bioinformatics and Biostatistics, Genova, Italy, 2009.
- M. Re, G. Valentini, Comparing early and late data fusion methods for gene function prediction, Neural Nets WIRN09, Proceedings of the 19th Italian Workshop on Neural Nets, Vietri sul Mare, Salerno, Italy, 2009, Frontiers in Artificial Intelligence and Applications vol. 204, pp. 197-207, IOS Press, 2009.
- M. Re, G. iValentini,Ensemble based Data Fusion for Gene Function Prediction, In: (J. Kittler, J. Benediktsson, F. Roli, Eds.) Eighth International Workshop on Multiple Classifier Systems MCS 2009, Lecture Notes in Computer Science, vol.5519 pp.448-457, Springer 2009.
- O. Okun, G. Valentini, H. Priisalu, Exploring the link between bolstered classification error and dataset complexity for gene expression based cancer classification, New Signal Processing Research, Nova Publishers, 2009.
- A. Bertoni, G. Valentini,Unsupervised stability-based ensembles to discover reliable structures in complex bio-molecular data, Proc. CIBB 2008, The Fifth International Conference on Bioinformatics and Biostatistics, Lecture Notes in Computer Science, vol. 5488 pp. 25-43, Springer, 2009.
- A. Bertoni, G.Valentini, Discovering multi-level structures in bio-molecular data through the Bernstein inequality BMC Bioinformatics 9 Suppl 2 S4, 2008
- G.Valentini, N. Cesa-Bianchi, HCGene: a software tool to support the hierarchical classification of genes, Bioinformatics, 24(5), pp. 729-731, 2008. HCGene web-site
- F. Ruffino, M. Muselli, G.Valentini, Gene expression modelling through positive Boolean functions,International Journal of Approximate Reasoning 47(1), pp. 97-108, 2008.
- M. Mesiti, E. J. Ruiz, I. Sanz, R. Berlanga, G. Valentini, P Perlasca, D. MansetXML-based approaches for the integration of heterogeneous bio-molecular data, NETTAB 2008, workshop on Bioinformatics Methods for Biomedical Complex System Applications, 2008.
- R. Avogadri, G.Valentini,Ensemble Clustering with a Fuzzy Approach, in: "Supervised and Unsupervised Ensemble Methods and their Applications", Studies in Computational Intelligence, vol. 126, Springer, 2008.
- A.Bertoni, G.Valentini Model order selection for biomolecular data clustering, BMC Bioinformatics vol.8, Suppl.3, 2007. Mosclust web-site
- G.Valentini Mosclust: a software library for discovering significant structures in bio-molecular data Bioinformatics 23(3):387-389, 2007.
- A. Bertoni, G.Valentini,Discovering Significant Structures in Clustered Bio-molecular Data Through the Bernstein Inequality, Knowledge-Based Intelligent Information and Engineering Systems, 11th International Conference, KES 2007, Lecture Notes in Computer Science, vol. 4694 pp. 886-891, 2007.
- R. Avogadri, G.Valentini, Fuzzy ensemble clustering for DNA microarray data analysis CIBB 2007, The Fourth International Conference on Bioinformatics and Biostatistics, Lecture Notes in Computer Science, vol. 4578, pp.537-543, 2007
- R. Avogadri, G.Valentini,An unsupervised fuzzy ensemble algorithmic scheme for gene expression data analysis, NETTAB 2007 workshop on a Semantic Web for Bioinformatics, Pisa, Italy, 2007.
- A.Bertoni, G.Valentini,Randomized Embedding Cluster Ensembles for gene expression data analysis, SETIT 2007 - IEEE International Conf. on Sciences of Electronic, Technologies of Information and Telecommunications, Hammamet, Tunisia, 2007.
- G. Valentini, F.Ruffino, Characterization of Lung tumor subtypes through gene expression cluster validity assessment, RAIRO - Theoretical Informatics and Applications, 40:163-176, 2006
- A.Bertoni, G. Valentini, Randomized maps for assessing the reliability of patients clusters in DNA microarray data analyses, Artificial Intelligence in Medicine 37(2):85-109, 2006, Science Direct access
- G.Valentini Clusterv: a tool for assessing the reliability of clusters discovered in DNA microarray data, Bioinformatics 22(3):369-370, 2006. Clusterv web-site
- A.Bertoni, G. Valentini,Model order selection for clustered bio-molecular data, In: J. Rousu, S. Kaski and E. Ukkonen (Eds.), Probabilistic Modeling and Machine Learning in Structural and Systems Biology, Tuusula, Finland, pp. 85-90, Helsinki University Printing House, 2006
- A.Bertoni, G. Valentini,Ensembles Based on Random Projections to Improve the Accuracy of Clustering Algorithms,Neural Nets, WIRN 2005, Lecture Notes in Computer Science, vol. 3931, pp. 31-37, 2006.
