0000000000524862

AUTHOR

Giorgio Valentini

showing 2 related works from this author

Midinfrared FT-IR as a Tool for Monitoring Herbaceous Biomass Composition and Its Conversion to Furfural

2015

A semiquantitative analysis by means of midinfrared FT-IR spectroscopy was tuned for the simultaneous determination of cellulose, hemicellulose, and lignin in industrial crops such as giant reed (Arundo donaxL.) and switchgrass (Panicum virgatumL.). Ternary mixtures of pure cellulose, hemicellulose, and lignin were prepared and a direct correlation area/concentration was achieved for cellulose and lignin, whereas indirect correlations were found for hemicellulose quantification. Good correspondences between the values derived from our model and those reported in the literature or obtained according to the official Van Soest method were ascertained. Average contents of 40–45% of cellulose, 2…

Article SubjectbiologySpectroscopy; Analytical Chemistry; Atomic and Molecular Physics and OpticsArundo donaxSettore ING-IND/27 - Chimica Industriale E Tecnologicabiology.organism_classificationFurfuralAtomic and Molecular Physics and OpticsAnalytical Chemistrychemistry.chemical_compoundHydrolysischemistryAtomic and Molecular PhysicsYield (chemistry)Biomass characterization FTIR lignocellulose biomass pretreatmentlcsh:QC350-467Panicum virgatumLigninOrganic chemistryHemicelluloseand OpticsCelluloselcsh:Optics. LightSpectroscopyNuclear chemistryJournal of Spectroscopy
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Disease–Genes Must Guide Data Source Integration in the Gene Prioritization Process

2019

One of the main issues in detecting the genes involved in the etiology of genetic human diseases is the integration of different types of available functional relationships between genes. Numerous approaches exploited the complementary evidence coded in heterogeneous sources of data to prioritize disease-genes, such as functional profiles or expression quantitative trait loci, but none of them to our knowledge posed the scarcity of known disease-genes as a feature of their integration methodology. Nevertheless, in contexts where data are unbalanced, that is, where one class is largely under-represented, imbalance-unaware approaches may suffer a strong decrease in performance. We claim that …

0301 basic medicineClass (computer programming)Boosting (machine learning)Computer scienceProcess (engineering)media_common.quotation_subjectComputational biologyScarcity03 medical and health sciencesComputingMethodologies_PATTERNRECOGNITION030104 developmental biologyExpression quantitative trait lociKey (cryptography)Feature (machine learning)Gene prioritizationmedia_common
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