Potential topics that could be covered at our future training events 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 event 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 
Lorenza Giannella, Training Manager.