Publications

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Zuccotti M, Merico V, Sacchi L, Bellone M, Brink TC, Stefanelli M, et al. Oct-4 regulates the expression of Stella and Foxj2 at the Nanog locus: implications for the developmental competence of mouse oocytes. Human Reproduction. 2009;24(9):2225-37.
Zuccotti M, Merico V, Sacchi L, Bellone M, Brink TC, Bellazzi R, et al. Maternal Oct-4 is a potential key regulator of the developmental competence of mouse oocytes. BMC Developmental Biology. 2008;8.
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Verduijn M, Sacchi L, Peek N, Bellazzi R, De Jonge E, de Mol B. Temporal abstraction for feature extraction: A comparative case study in prediction from intensive care monitoring data. Artificial Intelligence in Medicine. 2007;41.
Verduijn M, Dagliati A, Sacchi L, Peek N, Bellazzi R, De Jonge E, et al. IC prediction from patient monitoring data: a comparison of two temporal abstraction procedures.; 2005.
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Sacchi L, Bellazzi R, Larizza C, Magni P, Curk T, Petrovic U, et al. Clustering and classifying gene expressions data through Temporal Abstractions.; 2003.
Sacchi L, Larizza C, Magni P, Bellazzi R. Precedence temporal networks for the representation of temporal relationships in gene expression data.; 2006.
Sacchi L, Bellazzi R, Porreca R, Larizza C, Magni P. Precedence Temporal Networks: a New Tool for Extracting Temporal Relationships in Gene Expression Profiles.; 2005.
Sacchi L, Bellazzi R, Porreca R, Larizza C, Magni P. Precedence Temporal Networks from Gene Expression Data. Tsymbal A, Cunningham P, editors.; 2005.
Sacchi L, Bellazzi R, Larizza C, Porreca R, Magni P. Qualitative Representation and Clustering of Biomedical Time Series. Zupan B, Holmes JH, editors.; 2004.
Sacchi L, Bellazzi R, Larizza C, Magni P. Astrazioni temporali per il clustering di profili di espressione genica. Morgan E, editor.; 2004.
Sacchi L, Larizza C, Combi C, Bellazzi R. Data Mining with Temporal Abstractions: Learning Rules from Time Series. Data Mining and Knowledge Discovery. 2007;15.
Sacchi L, Bellazzi R, Larizza C, Magni P, Curk T, Petrovic U, et al. Temporal abstraction for clustering of gene expression data.; 2003.
Sacchi L, Bellazzi R, Larizza C, Magni P, Curk T, Petrovic U, et al. TA-clustering: Cluster analysis of gene expression profiles through Temporal Abstractions. International Journal of Medical Informatics. 2005;74:505-17.
Sacchi L, Nuzzo A, Decontardi F, Bellazzi R. Finding temporal patterns of GO processes in DNA microarray experiments.. Cagliari, Italy; 2008.
Sacchi L, Larizza C, Magni P, Bellazzi R. Precedence Temporal Networks to represent temporal relationships in gene expression data. Journal of Biomedical Informatics. 2007;40.
Sacchi L, Bellazzi R, Larizza C, Magni P, Curk T, Petrovic U, et al. Clustering gene expression data with Temporal Abstractions.; 2004.
Sacchi L, M.Verduijn, Peek N, De Jonge E, de Mol B, Bellazzi R. Describing and modeling time series based on qualitative temporal abstraction.; 2006.
Sacchi L, Porreca R, Larizza C, Magni P, Bellazzi R. Precedence Temporal Networks: Extraction and Representation of Temporal Relationships in Gene Expression Profiles.; 2005.
Sacchi L, Bellazzi R, Quaglini S, Sinico A, Moroni G. Temporal Rules to Predict Renal Flares in Lupus Nephritis. Combi C, Tucker A, editors.; 2007.
Sacchi L, Bellazzi R, Larizza C, Magni P, Curk T, Petrovic U, et al. Incremental template-based clustering of gene expression profiles with Temporal Abstractions.; 2004.
Sacchi L, Curk T, Demsar J, Shaulsky G, Zupan B, Bellazzi R. TA-based classification of transcriptional phenotypes.; 2006.
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Magni P, Ferrazzi F, Sacchi L, Bellazzi R. TimeClust: a clustering tool for gene expression time series. Bioinformatics. 2008;24(3):430-2.
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Ferrazzi F, Magni P, Sacchi L, Nuzzo A, Petrovic U, Bellazzi R. Inferring gene regulatory networks by integrating static and dynamic data. International Journal of Medical Informatics. 2007;76(Suppl 3):S462-75.
Ferrazzi F, Magni P, Sacchi L, Bellazzi R. Inferring gene expression networks through static and dynamic data integration. Vol 124. Hasman A, Haux R, van der Lei J, Clercq DE, France RFH, editors.; 2006.
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Curk T, Zupan B, Petrovic U, Demsar J, Shaulsky G, Sacchi L, et al. Machine learning for functional genomics: some experiments with supervised learning on microarray dataset.; 2003.