The workshops and seminars by Proteomics.Asia cover these areas:
Protein and Peptide analytics
- How to analyse a recombinant/natural protein
- What are the analytical techniques applied
- Developing a workflow for comprehensive analysis
- How to understand the results and validate them
- What are the pitfalls in protein and prptide analysis
- How to chose a reliable contract laboratory
- What data are needed for the approval process
Proteomics
- What is Proteomics and why is it important
- How to collect meaningful samples
- How to set up and develop a Proteomics' workflow
- Pitfalls in sample preparation
- LC-MS and LC-MS/MS as essential techniques in the workflow
- Multi-dimensional chromatography
- Sample preparation methods for a comprehensive analysis
- Quantiative Proteomics
- Post translational modificatiosn
- How do the individual components function
- Gel-based methods
- Liquid-chromatography based methods
- Mass sepctrometers
- Database searches
- Reporting tools
- What software tools are available to support teh workflow
- Organisation of the whole workflow
- Keeping track of the samples and follow experiments over a long period
- Databases for protein IDs
- Targeted Proteomics
- Develop targeted assays for protein analysis
Small molecule analysis/Metabolomics
- Basics of chromatography and LC-MS/LC-MS/MS
- Development of separation techniques and UV and MS based assays
- Data analysis
- Drug metabolomics
Other areas of workshops/seminars
- Chemical proteomics
- Identification of the protein targets of drugs
- Identification of off-targets and the reasons of side-effects
- Protein-interactions/Pathway analysis
- Identification of interacting proteins from cellular systems
- LC-MS analysis of glycans and oligos
- Biomarker discovery
- Collecting meaningful samples
- Talking to clinicians
- Sample preparation steps
- Idnetification, verification, and validation
- Publishing data
Hands-on in your lab
- The whole proteomics workflow
- From basics to the high end
- Performing the workflow with your instrumentation
- Using the available software for data analysis
- Optimising the workflow
- Understanding the results and validate them
- Avoid repeated and already done mistakes and errors
- Cell culture and molecular biology
