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Clelia Di Serio

Showing results (1-10 of 81) with videos related to

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BMC Bioinformatics|February 11, 2017
A novel scan statistics approach for clustering identification and comparison in binary genomic dataDanilo Pellin, Clelia Di Serio
Statistical Methods in Medical Research|July 31, 2012
Evaluating treatment effect within a multivariate stochastic ordering framework: Nonparametric combination methodology applied to a study on multiple sclerosisChiara Brombin, Clelia Di Serio
Plos Computational Biology|August 9, 2008
Retroviral integration process in the human genome: is it really non-random? A new statistical approachAlessandro Ambrosi, Claudia Cattoglio, Clelia Di Serio
Statistical Methods in Medical Research|March 28, 2014
Joint modeling of HIV data in multicenter observational studies: A comparison among different approachesChiara Brombin, Clelia Di Serio, Paola Mv Rancoita
PNAS Nexus|February 6, 2023
The reproducibility of COVID-19 data analysis: paradoxes, pitfalls, and future challengesClelia Di Serio, Antonio Malgaroli, Paolo Ferrari, et al.
BMC Bioinformatics|August 2, 2018
Effect of the number of removed lymph nodes on prostate cancer recurrence and survival: evidence from an observational studyChiara Gigliarano, Alessandro Nonis, Alberto Briganti, et al.
Plos One|April 4, 2012
A genome-wide identification analysis of small regulatory RNAs in Mycobacterium tuberculosis by RNA-Seq and conservation analysisDanilo Pellin, Paolo Miotto, Alessandro Ambrosi, et al.
Plos One|November 17, 2018
Modeling physiological responses induced by an emotion recognition task using latent class mixed modelsFederica Cugnata, Riccardo Maria Martoni, Manuela Ferrario, et al.
Frontiers in Psychology|May 30, 2017
Validating the Italian Version of the Disgust and Propensity Scale-RevisedRiccardo M Martoni, Paola M V Rancoita, Clelia Di Serio, et al.
Plos One|July 1, 2025
Usability of machine learning algorithms based on electronic health records for the prediction of acute kidney injury and transition to acute kidney disease: A proof of concept studyLorenzo Ruinelli, Pietro Cippà, Chantal Sieber, et al.
Pageof 9

Showing results (1-10 of 81) with videos related to

Sort By:
Pageof 9
BMC Bioinformatics|February 11, 2017
A novel scan statistics approach for clustering identification and comparison in binary genomic dataDanilo Pellin, Clelia Di Serio
Statistical Methods in Medical Research|July 31, 2012
Evaluating treatment effect within a multivariate stochastic ordering framework: Nonparametric combination methodology applied to a study on multiple sclerosisChiara Brombin, Clelia Di Serio
Plos Computational Biology|August 9, 2008
Retroviral integration process in the human genome: is it really non-random? A new statistical approachAlessandro Ambrosi, Claudia Cattoglio, Clelia Di Serio
Statistical Methods in Medical Research|March 28, 2014
Joint modeling of HIV data in multicenter observational studies: A comparison among different approachesChiara Brombin, Clelia Di Serio, Paola Mv Rancoita
PNAS Nexus|February 6, 2023
The reproducibility of COVID-19 data analysis: paradoxes, pitfalls, and future challengesClelia Di Serio, Antonio Malgaroli, Paolo Ferrari, et al.
BMC Bioinformatics|August 2, 2018
Effect of the number of removed lymph nodes on prostate cancer recurrence and survival: evidence from an observational studyChiara Gigliarano, Alessandro Nonis, Alberto Briganti, et al.
Plos One|April 4, 2012
A genome-wide identification analysis of small regulatory RNAs in Mycobacterium tuberculosis by RNA-Seq and conservation analysisDanilo Pellin, Paolo Miotto, Alessandro Ambrosi, et al.
Plos One|November 17, 2018
Modeling physiological responses induced by an emotion recognition task using latent class mixed modelsFederica Cugnata, Riccardo Maria Martoni, Manuela Ferrario, et al.
Frontiers in Psychology|May 30, 2017
Validating the Italian Version of the Disgust and Propensity Scale-RevisedRiccardo M Martoni, Paola M V Rancoita, Clelia Di Serio, et al.
Plos One|July 1, 2025
Usability of machine learning algorithms based on electronic health records for the prediction of acute kidney injury and transition to acute kidney disease: A proof of concept studyLorenzo Ruinelli, Pietro Cippà, Chantal Sieber, et al.
Pageof 9