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16 materials found

Authors: David Wishart  or stortebecker 


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 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 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 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 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 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 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 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 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.

Proteomics - Peptide and Protein ID using OpenMS tools

Training material for proteomics workflows in Galaxy

Questions of the tutorial:

  • How to convert LC-MS/MS raw files?
  • How to identify peptides?
  • How to identify proteins?
  • How to evaluate the results?

Objectives of the tutorial:

  • Protein identification from LC-MS/MS raw files.

Resource type: Tutorial

Proteomics - Detection and quantitation of N-termini (degradomics) via N-TAILS

Training material for proteomics workflows in Galaxy

Questions of the tutorial:

  • How can protein N-termini be enriched for LC-MS/MS?
  • How to analyze the LC-MS/MS data?

Objectives of the tutorial:

  • Run an N-TAILS data analysis.

Resource type: Tutorial

Proteomics - Peptide and Protein Quantification via Stable Isotope Labelling (SIL)

Training material for proteomics workflows in Galaxy

Questions of the tutorial:

  • What are MS1 features?
  • How to quantify based on MS1 features?
  • How to map MS1 features to MS2 identifications?
  • How to evaluate and optimize the results?

Objectives of the tutorial:

  • MS1 feature...

Resource type: Tutorial

Proteomics - Peptide and Protein ID using SearchGUI and PeptideShaker

Training material for proteomics workflows in Galaxy

Questions of the tutorial:

  • How to convert LC-MS/MS raw files?
  • How to identify peptides?
  • How to identify proteins?
  • How to evaluate the results?

Objectives of the tutorial:

  • Protein identification from LC-MS/MS raw files.

Resource type: Tutorial

Proteomics - Secretome Prediction

Training material for proteomics workflows in Galaxy

Questions of the tutorial:

  • How to predict cellular protein localization based upon GO-terms?
  • How to combine multiple localization predictions?

Objectives of the tutorial:

  • Predict proteins in the cellular secretome by using...

Resource type: Tutorial

Proteomics - Label-free versus Labelled - How to Choose Your Quantitation Method

Training material for proteomics workflows in Galaxy

Questions of the tutorial:

  • What are benefits and drawbacks of different quantitation methods?
  • How to choose which quantitation method bests suits my need?

Objectives of the tutorial:

  • Choose your quantitation method.

Resource type: Tutorial

Proteomics - Protein FASTA Database Handling

Training material for proteomics workflows in Galaxy

Questions of the tutorial:

  • How to download protein FASTA databases of a certain organism?
  • How to download a contaminant database?
  • How to create a decoy database?
  • How to combine databases?

Objectives of the tutorial:

  • Creation of a...

Resource type: Tutorial