Potential topics that could be covered at our future training events and courses include:
Protein modelling
We anticipate that the training course on protein modelling will cover some or all of the following areas:
- Introduction to protein structure – structure data files and their manipulation
- Performing calculations on 3-d structures
- Differences between X-ray crystallographic and NMR structures
- Protein structure analysis, homology modelling, and simulation of effects of mutagenesis
- Mapping sequence variance onto 3-d structures
- Cavity analysis and surface modelling – electrostatic potentials
- Modelling of interaction surfaces
- Prediction of 3-d structures from sequences
Bioinformatics
Over time, we hope to develop a series of courses in this area, covering discrete areas of the subject, and developing into a coherent whole. It may be appropriate to ask several groups to combine to generate this programme. Single training courses could include:
- Protein structure analysis, homology modelling, simulation of effects of mutagenesis (see below also)
- Protein sequence analysis – alignments, prediction of function from sequence
- Analysis of protein interactomes
- Pathway modelling, mapping ‘omics’ data onto pathways
- Analysis of image data – from gels to cells – acceptable manipulation, quantification, image analysis (from Image to proprietary analysis)
Enzymology
We anticipate that the enzymology training event will cover some or all of the following areas:
- Principles of biocatalysis
- Analysis of enzyme kinetics, affinity and velocity
- Development of a robust enzyme assay
- Coupled enzyme systems
- Allostery
- Analysis of enzyme kinetic data
- Automated enzyme assays
- Inhibition
Metabolic flux
We anticipate that the metabolic flux training event will cover some or all of the following areas:
- Metabolic pathway concepts
- Flux through pathways
- Common metabolites and multiple routes of utilization
- Relationship between flux and metabolite concentration
- Analytic approaches to metabolite quantification/metabolomics
- Use of tracers to monitor flux through metabolic systems
- Introduction to metabolic pathway simulations
Experimental design
We anticipate that the training course on experimental design will cover some or all of the following areas:
- The problem of irreproducible science
- Design of controlled experiments
- Hypothesis falsification and outcome
- The value of negative results
- Power analysis, sampling strategies and study dimensions
- Understanding data: normality, heteroscedasticity
- The effect of the experimenter on the experimental outcome
- The consequences of data transformation
- The importance of ‘minimal information on an X experiment’ and of data standards
- The myth of p=0.05
- How to design a fully controlled experiment
- How to test a fully designed experiment
- The formalization of “Design of Experiments”
Data visualization
We anticipate that the data visualization training will cover some or all of the following areas:
- The relevance of data visualization, from simple data sets to complex, multidimensional data sets
- Coping with dynamic range and data normalization
- The use of different graphical paradigms
- Chartjunk
- Developing tools for effective visualization and communication of data
- Types of data from images to large tabular data sets
- Communication versus distortion of data
For further information and to apply, please contact Training >