Ian G Brennan, Sonal Singhal, Ziad Al Bkhetan
pipesnake: generalized software for the assembly and analysis of phylogenomic datasets from conserved genomic loci
Bioinformatics (Oxford, England)
modern infectious disease epidemiology builds two independently developed fields classical epidemiology dynamical epidemiology past decade integration two fields increased research practice training options within fields remain distinct opportunities integration classroom annual clinic meaningful modeling epidemiological data mmed african institute mathematical sciences begun address gap mmed offers participants exposure broad range concepts techniques epidemiological traditions mmed 2010 developed pedagogical approach bridges traditional distinction classical dynamical epidemiology used multiple educational levels high school graduate level courses approach handson consisting realtime simulation stochastic outbreak course participants including realistic data reporting followed variety mathematical statistical analyses stemming epidemiological traditions exercise dynamical epidemiologists developed empirical skills study design learned concepts bias classical epidemiologists trained systems thinking began understand epidemics dynamic nonlinear processes believe type integrated educational tool prove extremely valuable training future infectious disease epidemiologists also believe interdisciplinary training critical local capacity building analytical epidemiology africa continues produce new cohorts welltrained mathematicians statisticians scientists lessons draw skills concepts many fields biologyfrom pathogen biology evolutionary dynamics hostpathogen interactions ecology infectious disease bioinformatics computational biology statisticsthis exercise incorporated broad array life sciences courses