Autonomous Experimentation for Systems Biology
- Towards Applied System Biology
- Scouting Algorithm
Towards Applied Systems Biology
Quantitative, predictive understanding of biology requires comprehensive
information. High-throughput methods and laboratory automation technology
have the potential to deliver the necessary data density. To harvest this
potential, however, experimental design has to become dynamic and adaptive.
Together with three application examples to demonstrate the versatility, we
present a novel algorithm for autonomously developing empirical
conducting experiments. One advantage of this technique (called scouting) is that no a priori knowledge about the systems is required. Perplexing
complexity originating from intricate and manifold interplay of components is, therefore, preserved. Predicting systems behavior is a primary
application of the empirically constructed data-driven model. Such a model replete with quantitative details can substitute preconceived
understanding follows application.
The scouting algorithm combines evolutionary computing with information theory to concentrate resources on areas of the experimentation space where
prediction and observation deviate. An experiment is conducted according to experiment specification x generated by an evolution process and the
observation r will be obtained. At the same time, an expectation r' based on the experience database is derived. The surprise value is the deviation
between r and r', which is assigned to x as its fitness value. Observations are stored in the experience database so that in the end, it constitutes
an empirical model.
- Evolutionary experimentation for exploration
- Test outcomes immediately affect what test is performed next.
In Vitro: enzyme response surface
The effect of divalent cations on the activity of malate dehydrogenase (MDH) is
measured by monitoring NADH absorption over time. Enzyme activity analysis
signals Products concentration L-Malate NADH Oxalacetate H+ NAD+ Mg Citrate 2+
MDH Concentration of Mg2+ and citrate is used as a chemical signal to be
controlled by the scouting algorithm, and NADH absorption is observed as enzyme
response to the signals. The experience database constitutes an empirical model
of the enzyme s activity modulation.
In Silico: chemical signature
Coordinates Chemical composition An artificial planetary sphere has been
implemented with a cellular automaton, simulating chemical dynamics. Biota
introduce inhomogeneity into the system. When coordinates are specified, the
chemical substance composition in this area is returned as the observation. The
scouting algorithm has been successfully used to autonomously localize unusual
Deterministic Model: HIV immunology
A deterministic model of the relationship between HIV and the immune system was constructed by Wodarz and Nowak (1999). The scouting algorithm
specifies initial states of the model, and the model returns the final states. 2000 observations in the experience database of scouting are analyzed.
Surprise values are represented by colors. When the CTL precursors and
effectors are chosen as the axis of the graph, a regular pattern was discovered, and this matches to the border of two behaviors of this model (i.e.,
virus is defeated and the immune system is destroy).
[Photo credit:© NIAID and AVERT]