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Animals : an Open Access Journal From MDPI|December 19, 2020
Genetic Parameters of Bovine Milk Fatty Acid Profile, Yield, Composition, Total and Differential Somatic Cell CountTania Bobbo, Mauro Penasa, Martino Cassandro
Scientific Reports|July 2, 2021
Comparison of machine learning methods to predict udder health status based on somatic cell counts in dairy cowsTania Bobbo, Stefano Biffani, Cristian Taccioli, et al.
Animal Science Journal = Nihon Chikusan Gakkaiho|May 15, 2019
Genetic relationships of alternative somatic cell count traits with milk yield, composition and udder type traits in Italian Jersey cowsTania Bobbo, Chiara Roveglia, Mauro Penasa, et al.
Journal of Dairy Science|October 15, 2018
Genetic variation in serum protein pattern and blood β-hydroxybutyrate and their relationships with udder health traits, protein profile, and cheese-making properties in Holstein cowsAlessio Cecchinato, Tania Bobbo, Pamela L Ruegg, et al.
BMC Genomics|October 14, 2024
Machine learning classification of archaea and bacteria identifies novel predictive genomic featuresTania Bobbo, Filippo Biscarini, Sachithra K Yaddehige, et al.
Animals : an Open Access Journal From MDPI|April 30, 2021
Dairy Cows' Health during Alpine Summer Grazing as Assessed by Milk Traits, Including Differential Somatic Cell Count: A Case Study from ItalyGiovanni Niero, Tania Bobbo, Simone Callegaro, et al.
Scientific Reports|February 6, 2023
Discovering novel clues of natural selection on four worldwide goat breedsArianna Manunza, Johanna Ramirez Diaz, Brian L Sayre, et al.
Frontiers in Genetics|April 3, 2025
Exploring the complex population structure and admixture of four local Hungarian sheep breedsJohanna Ramírez-Díaz, Tania Bobbo, Bernt Guldbrandtsen, et al.
Biology|September 14, 2022
Machine Learning Algorithms Highlight tRNA Information Content and Chargaff's Second Parity Rule Score as Important Features in Discriminating Probiotics from Non-ProbioticsCarlo M Bergamini, Nicoletta Bianchi, Valerio Giaccone, et al.
Insects|April 23, 2025
Combining Environmental Variables and Machine Learning Methods to Determine the Most Significant Factors Influencing Honey ProductionJohanna Ramirez-Diaz, Arianna Manunza, Tiago Almeida de Oliveira, et al.
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