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\f0\fs24 \cf2 \cb3 Ideas of distance kernels - to parameterise\
Susceptibility / transmissibility\
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General direction -\
	- reproduce statistics of epidemics ?\
	- infer distance kernel, assume kernel ?\
	- infer parameters ?\
	- ?\
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Make sparse ?!\
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Keeling Rohani Gridding method\
Selki construction\
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\f1\b \cf4 Mohammad: 
\b0 \cf0 \uc0\u8234 You will need to mention the account number, sort code, your compete address and signature.\uc0\u8236 \

\b \cf4 Mohammad: 
\b0 \cf0 \uc0\u8234 The address is\uc0\u8236 \

\b \cf4 Mohammad: 
\b0 \cf0 \uc0\u8234 Royal Priors\uc0\u8232 59 The Parade\u8232 Royal Leamington Spa\u8232 CV32 4ZX\uc0\u8236 \
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Vector causes evolutionary pressure to lower CpG\
Alpha don\'92t care about lymph nodes particularly\
Check CpG and C+G at different genes after alignment\
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Lower eta => immune evasion => rubella wants to be detected\
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Recalc eta for various viruses ?\
Arg a big part of rubella genome ? If so, induces high C+G and CpG\
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DiffEq ( ODE, PDE )\
Analysis ( real, complex, vector, matrix, functional )\
LinAlg\
Numerical Analysis\
Bifurcation theory\
Fourier analysis\
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Augment Jess\'92s file :\
	- C\
	- G\
	- C+G per sequence\
	- CpG\
	- gene chunk ID\
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Plots :\
	- Alignment DONE\
	- change in C, G, C+G, CpG PER CHUNK DONE\
	- Map of average C+G, CpG, C, G \
	- Video ?\
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Text :\
	- Significance of CpG, C+G\
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7742 - 8619\
9642 - 10582\
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\f2\b0 \cf0 FIVE FOUR CLUB\
EXP0XA25CHK
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INTRO
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\b Context :
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Histopathology evaluates the state of the organ\
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\b Sheep :
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Population dynamics demonstrating crashes\
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\'93Gross pathology\'94 applied - Gulland, Parasitology, 1992. \'93Post-mortem findings in\'85\'94, \'93The liver was friable, \'85\'94; Graham et al\
No histology !\
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Interesting question : cause of death ? Immunosuppression \'97> worms ?\
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Nutrition - potential cause of death. 
\b If we want to evaluate potential link between nutrition and histology 
\b0 - automate, blah.\

\b Want to be able to use histo as a quantitative variable \
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1. Method to get histo as a quantitative variable, not user biased. Humans impossible to standardise, reproducibility zero\
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PRIOR INFORMATION :\
- Sheep have worms\
- Sheep with high protein levels are more likely to survive\
- Liver state is a good indicator of malnutrition\
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INFERENCE :\
IF we find a positive correlation between liver and proteins\
THEN high protein levels => healthy liver => cause of death probably not malnutrition\
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IF we find no correlation\
THEN high protein levels =/=> healthy liver => can\'92t say anything about CoD\
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WANT TO SEPARATE \
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Parasites / immunity or nutrition\
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Histo : gives us information that allows this distinction to be made\
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\b \cf0 Motivation :
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\b Proposal :
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\b METHODS
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