Register training material
13 materials found

Authors: David Wishart  or Emma Griffiths 


Applying data standards to the harmonization of COVID-19 datasets from different sources

This video describes how public health genomics has played a key role in international responses to the COVID-19 pandemic, and how data standards are being used to harmonize data across jurisdictions for Canadian COVID-19 surveillance and outbreak investigations.

Scientific topics: Data integration and warehousing

Keywords: Data integration, Standards, Standardised vocabulary, data harmonization, Ontologies

Resource type: Video

Applying data standards to the harmonization of COVID-19 datasets from different sources http://tess.elixir-uk.org/materials/applying-data-standards-to-the-harmonization-of-covid-19-datasets-from-different-sources This video describes how public health genomics has played a key role in international responses to the COVID-19 pandemic, and how data standards are being used to harmonize data across jurisdictions for Canadian COVID-19 surveillance and outbreak investigations. Data integration and warehousing Data integration, Standards, Standardised vocabulary, data harmonization, Ontologies Anyone interested in data standardization and/or the ontology approach (i.e. public, end users).
Useful ontologies for harmonizing cohort data

This video describes a community of practice for interoperable ontology building called the OBO Foundry, and highlights a number of well curated and maintained ontologies that are useful for annotating cohort data.

Scientific topics: Ontology and terminology, Data management, Data integration and warehousing

Keywords: Ontologies, Cohort data, data annotation

Resource type: Video

Useful ontologies for harmonizing cohort data http://tess.elixir-uk.org/materials/useful-ontologies-for-harmonizing-cohort-data This video describes a community of practice for interoperable ontology building called the OBO Foundry, and highlights a number of well curated and maintained ontologies that are useful for annotating cohort data. Ontology and terminology Data management Data integration and warehousing Ontologies, Cohort data, data annotation Anyone interested in data standardization and/or the ontology approach (i.e. public, end users).
Annotating data using ontologies

This video highlights examples of tools and ontologies which can be used for annotating health data, and how ontologies help to support data ecosystems.

Scientific topics: Ontology and terminology, Data integration and warehousing, Data management

Keywords: Ontologies, Annotation, Data integration

Resource type: Video

Annotating data using ontologies http://tess.elixir-uk.org/materials/annotating-data-using-ontologies This video highlights examples of tools and ontologies which can be used for annotating health data, and how ontologies help to support data ecosystems. Ontology and terminology Data integration and warehousing Data management Ontologies, Annotation, Data integration
Solutions for overcoming cohort data integration challenges using ontology: an introduction

Ontologies are collections of well-defined, hierarchical, controlled vocabulary, linked by logical relationships. This video introduces the concept and benefits of implementing ontologies for solving data integration issues when data is generated by different research groups.

Scientific topics: Data management, Data integration and warehousing, Ontology and terminology

Keywords: Ontologies, Data integration, Annotation

Resource type: Video

Solutions for overcoming cohort data integration challenges using ontology: an introduction http://tess.elixir-uk.org/materials/solutions-for-overcoming-cohort-data-integration-challenges-using-ontology-an-introduction Ontologies are collections of well-defined, hierarchical, controlled vocabulary, linked by logical relationships. This video introduces the concept and benefits of implementing ontologies for solving data integration issues when data is generated by different research groups. Data management Data integration and warehousing Ontology and terminology Ontologies, Data integration, Annotation
Informatics and Statistics for Metabolomics 2018 Module 6-Future of Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 6-Future of Metabolomics http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-6-future-of-metabolomics Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. Researchers Post-Doctoral Fellows Graduate students Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2018 Module 3-Databases for Chemical, Spectral, and Biological Data

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 3-Databases for Chemical, Spectral, and Biological Data http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-3-databases-for-chemical-spectral-and-biological-data Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. Researchers Post-Doctoral Fellows Graduate Students Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2018 Module 2-Metabolite Identification and Annotation

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 2-Metabolite Identification and Annotation http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-2-metabolite-identification-and-annotation Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. Researchers Graduate students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2018 Module 1-Introduction to Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 1-Introduction to Metabolomics http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-1-introduction-to-metabolomics Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. Researchers Graduate Students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2017 Module 6-Future of Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 6-Future of Metabolomics http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-6-future-of-metabolomics Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Informatics and Statistics for Metabolomics 2017 Module 5-MetaboAnalyst

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 5-MetaboAnalyst http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-5-metaboanalyst Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases. Researchers Graduate Students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Informatics and Statistics for Metabolomics 2017 Module 3-Databases for Chemical, Spectral, and Biological Data

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 3-Databases for Chemical, Spectral, and Biological Data http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-3-databases-for-chemical-spectral-and-biological-data Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases. Researchers Graduate Students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Informatics and Statistics for Metabolomics 2017 Module 2-Metabolite Identification and Annotation

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 2-Metabolite Identification and Annotation http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-2-metabolite-identification-and-annotation Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases. Researchers Graduate students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2017 Module 1-Introduction to Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 1-Introduction to Metabolomics http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-1-introduction-to-metabolomics Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows