Complex diseases as altered biological networks

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Complex diseases as altered biological networks
GRAPH (V,E) Vertices Biological entities
(with attributes) Edges Relation between
entities (QUANTITATIVE!!)
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Complex diseases as dynamic systems
INPUT VAR Information of the patient Genetic,
immunologic...OUTPUT VAR Diagnosis-prognosis.T
HE GOAL Input into the model, Simulate, Output
the result
I N P U T
O U T P U T
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Modelling the biological network/system
MODELS AND SUBMODELS From the cell to a subsystem
VERTICES Microarray data analysis, model
KOs...EDGES Biochemical/molecular studies,
microarray data analysis, text mining, proteomic
data analysis... We should obtain a set of
equations for each edge.INPUT SNPs, DNA
polymorphisms, epidemiological, physiological,
immunological data... OUTPUT Probability
distribution/values to predict evolution of the
disease, possible treatments...
(remember Pareto's Law most of the consequences
stems from a few causes)
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Integrating heterogeneous data in the model
EXPERIMENTAL
STANDARD
INTEGRATED
INFO
PROGRAMMING LANGUAGE
INFERENCE/DESCRIPTIVE MODEL (BAYESIAN, MCMC,
EQUATIONS...)