{"id":null,"code":"DEKE0116","name":{"valueFi":"Food Metabolomics and Multivariate Analysis","valueEn":"Food Metabolomics and Multivariate Analysis","valueSv":"Food Metabolomics and Multivariate Analysis"},"credits":5.0,"minCredits":5,"maxCredits":5,"tags":[{"code":"KEKE","title":{"valueFi":"Kestävä kehitys","valueEn":"Sustainable development","valueSv":"Sustainable development"}}],"createdAt":1790534307938,"contentList":[{"title":{"valueFi":"Osaamistavoitteet","valueEn":"Learning outcomes","valueSv":""},"content":{"valueFi":"Student will understand the principles of MS and NMR-based metabolomics and their workflows and applications within food sciences. \r\nStudent learns to produce and interpret metabolomics data and apply relevant tools in the data processing.\r\nStudent learns the basics of various common statistical methods used in Food Sciences. \r\nStudent learns to interpret the univariate and multivariate models and knows the basics about creating them.\r\n\r\nWorklife skills:\r\n•\twritten communication and presentation skills\r\n•\tproblem-solving skills","valueEn":"Student will understand the principles of MS and NMR-based metabolomics and their workflows and applications within food sciences. \r\nStudent learns to produce and interpret metabolomics data and apply relevant tools in the data processing.\r\nStudent learns the basics of various common statistical methods used in Food Sciences. \r\nStudent learns to interpret the univariate and multivariate models and knows the basics about creating them.\r\n\r\nWorklife skills:\r\n•\twritten communication and presentation skills\r\n•\tproblem-solving skills","valueSv":"Student will understand the principles of MS and NMR-based metabolomics and their workflows and applications within food sciences. \r\nStudent learns to produce and interpret metabolomics data and apply relevant tools in the data processing.\r\nStudent learns the basics of various common statistical methods used in Food Sciences. \r\nStudent learns to interpret the univariate and multivariate models and knows the basics about creating them.\r\n\r\nWorklife skills:\r\n•\twritten communication and presentation skills\r\n•\tproblem-solving skills"}},{"title":{"valueFi":"Sisältö","valueEn":"Content","valueSv":""},"content":{"valueFi":"Basics of MS and NMR-based metabolomics and their workflows and applications in food science, including used software approaches for data acquisition, data processing and metabolite identification. Univariate and multivariate methods from a food scientist’s point of view. Laboratory exercise. Introduction to different statistical methods (e.g. t-test, ANOVA, PCA, PLS-DA, PLS regression) and interpretation of the results with practical examples.\r\n\r\nThe contents is related to the UN’s sustainable development goals 2 (Zero Hunger) and 3 (Good Health and Wellbeing) via examples of nutrition and healthy diets in connection to preventing non-communicable diseases.","valueEn":"Basics of MS and NMR-based metabolomics and their workflows and applications in food science, including used software approaches for data acquisition, data processing and metabolite identification. Univariate and multivariate methods from a food scientist’s point of view. Laboratory exercise. Introduction to different statistical methods (e.g. t-test, ANOVA, PCA, PLS-DA, PLS regression) and interpretation of the results with practical examples.\r\n\r\nThe contents is related to the UN’s sustainable development goals 2 (Zero Hunger) and 3 (Good Health and Wellbeing) via examples of nutrition and healthy diets in connection to preventing non-communicable diseases.","valueSv":"Basics of MS and NMR-based metabolomics and their workflows and applications in food science, including used software approaches for data acquisition, data processing and metabolite identification. Univariate and multivariate methods from a food scientist’s point of view. Laboratory exercise. Introduction to different statistical methods (e.g. t-test, ANOVA, PCA, PLS-DA, PLS regression) and interpretation of the results with practical examples.\r\n\r\nThe contents is related to the UN’s sustainable development goals 2 (Zero Hunger) and 3 (Good Health and Wellbeing) via examples of nutrition and healthy diets in connection to preventing non-communicable diseases."}},{"title":{"valueFi":"Suoritustavat","valueEn":"Study methods","valueSv":""},"content":{"valueFi":"Assignments, demonstrations, practical work, exam, learning diary","valueEn":"Assignments, demonstrations, practical work, exam, learning diary","valueSv":""}},{"title":{"valueFi":"Toteutustavat","valueEn":"Course unit methods","valueSv":""},"content":{"valueFi":"Lectures, demonstrations, laboratory work","valueEn":"Lectures, demonstrations, laboratory work","valueSv":""}},{"title":{"valueFi":"Oppimateriaalit","valueEn":"Learning material","valueSv":""},"content":{"valueFi":"Material in Moodle","valueEn":"Material in Moodle","valueSv":""}},{"title":{"valueFi":"Lisätiedot","valueEn":"Further information","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Kurssikirjallisuus","valueEn":"Literature","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Esitietovaatimukset","valueEn":"Qualifications","valueSv":""},"content":{"valueFi":"Prior knowledge on mass spectrometry is recommended (e.g. FOOD3846 Applications of Mass Spectrometry in Food Sciences or similar)","valueEn":"Prior knowledge on mass spectrometry is recommended (e.g. FOOD3846 Applications of Mass Spectrometry in Food Sciences or similar)","valueSv":""}},{"title":{"valueFi":"Arviointiasteikko","valueEn":"Assessment scale","valueSv":""},"content":{"valueFi":"0-5","valueEn":"0-5","valueSv":"0-5"}},{"title":{"valueFi":"Arviointikriteerit","valueEn":"Assessment criteria","valueSv":""},"content":{"valueFi":"The assessment consists of the combined score of the exam (50%) and the learning diary (50%).","valueEn":"The assessment consists of the combined score of the exam (50%) and the learning diary (50%).","valueSv":""}},{"title":{"valueFi":"Arviointikriteerit 2","valueEn":"Assessment criteria 2","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Arviointikriteerit 3","valueEn":"Assessment criteria 3","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Arviointikriteerit 4","valueEn":"Assessment criteria 4","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Kielet","valueEn":"Languages","valueSv":""},"content":{"valueFi":"englanti","valueEn":"English","valueSv":"engelska"}},{"title":{"valueFi":"Taso","valueEn":"Level","valueSv":""},"content":{"valueFi":"Syventävät opinnot","valueEn":"Advanced Studies","valueSv":""}},{"title":{"valueFi":"Oppiaine","valueEn":"Subject","valueSv":""},"content":{"valueFi":"Elintarviketekniikka","valueEn":"Food Technology","valueSv":"Food Technology"}},{"title":{"valueFi":"Vastuuhenkilöt","valueEn":"Person in charge","valueSv":""},"content":{"valueFi":"Maaria Kortesniemi, Kati Hanhineva","valueEn":"Maaria Kortesniemi, Kati Hanhineva","valueSv":"Maaria Kortesniemi, Kati Hanhineva"}},{"title":{"valueFi":"Luokittelu","valueEn":"Classification","valueSv":""},"content":{"valueFi":"Kestävä kehitys","valueEn":"Sustainable development","valueSv":"Sustainable development"}},{"title":{"valueFi":"Linkit","valueEn":"Links","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}}]}