Mariana G. Lopez

发表

Métodos de agrupamiento no supervisado para la integración de datos genómicos y metabólicos de múltiples líneas de introgresión

Georgina Stegmayer, Diego H. Milone, Fernando Carrari, 2009, Inteligencia Artif..

Neural network model for integration and visualization of introgressed genome and metabolite data

Georgina Stegmayer, Diego H. Milone, Fernando Carrari, 2009, 2009 International Joint Conference on Neural Networks.

Improving clustering with metabolic pathway data

Georgina Stegmayer, Diego H. Milone, Fernando Carrari, 2014, BMC Bioinformatics.

*omeSOM: a software for clustering and visualization of transcriptional and metabolite data mined from interspecific crosses of crop plants

Georgina Stegmayer, Diego H. Milone, Fernando Carrari, 2010, BMC Bioinformatics.

Clustering biological data with SOMs: On topology preservation in non-linear dimensional reduction

Georgina Stegmayer, Diego H. Milone, Fernando Carrari, 2013, Expert Syst. Appl..

A Biologically Inspired Validity Measure for Comparison of Clustering Methods over Metabolic Data Sets

Georgina Stegmayer, Diego H. Milone, Fernando Carrari, 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Metabolic analyses of interspecific tomato recombinant inbred lines for fruit quality improvement

Diego H. Milone, Mariana G. Lopez, M. Zanor, 2015, Metabolomics.

Downregulation of polyphenol oxidase in potato tubers redirects phenylpropanoid metabolism enhancing chlorogenate content and late blight resistance

Mariana G. Lopez, F. Carrari, R. Asis, 2014, Molecular Breeding.

Downregulation of polyphenol oxidase in potato tubers redirects phenylpropanoid metabolism enhancing chlorogenate content and late blight resistance

Mariana G. Lopez, F. Carrari, R. Asis, 2014, Molecular Breeding.

Safety assessment of nonbrowning potatoes: opening the discussion about the relevance of substantial equivalence on next generation biotech crops.

Mariana G. Lopez, F. Carrari, B. Llorente, 2011, Plant biotechnology journal.

Coupling Virus-Induced Gene Silencing to Exogenous Green Fluorescence Protein Expression Provides a Highly Efficient System for Functional Genomics in Arabidopsis and across All Stages of Tomato Fruit Development1[C][W]

Mariana G. Lopez, F. Carrari, A. Fernie, 2011, Plant Physiology.

Breakthrough Technologies Coupling Virus-Induced Gene Silencing to Exogenous Green Fluorescence Protein Expression Provides a Highly Efficient System for Functional Genomics in Arabidopsis and across All Stages of Tomato Fruit Development 1 [ C ] [ W ]

Mariana G. Lopez, F. Carrari, A. Fernie, 2011 .

Metabolic analyses of interspecific tomato recombinant inbred lines for fruit quality improvement

Diego H. Milone, Mariana G. Lopez, M. Zanor, 2015, Metabolomics.

ANALYSIS AND INTEGRATION OF BIOLOGICAL DATA: A DATA MINING APPROACH USING NEURAL NETWORKS

Georgina Stegmayer, Diego H. Milone, Fernando Carrari, 2011 .

Coupling Virus-Induced Gene Silencing to Exogenous Green Fluorescence Protein Expression Provides a Highly Efficient System for Functional Genomics in Arabidopsis and across All Stages of Tomato Fruit Development1[C][W]

Mariana G. Lopez, F. Carrari, A. Fernie, 2011, Plant Physiology.