fundamental principles (?) of biological data

Fundamental principles(?)of biological dataBen Bolker

13 December 2015

Fundamental principles (?) of biological data http://ms.mcmaster.ca/~bolker/misc/SLC_fundamental...

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connecting data with theory

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known, unknown, & unknowable

Gomory (1995), Levin (2003)(not Cheney "unknown unknowns")

what are the fundamental limits of biologicalknowledge?

how closely can we approach them?

what are the limiting factors?

examples: epistatic networks,community dynamics including plasticity/behaviour …

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fundamental limits

is there a useful general theory?

forward (prediction)

backward (reconstruction)

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chaos

irreducible stochasticity

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information horizons(e.g. most recent common ancestor)

diffusive processes

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potential solutions

aggregate/scale up (Levin, 2003); e.g. metapopulations

get more data(genomic, citizen science, robotics, image analysis)

combine heterogeneous data

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e.g. epidemiological + genomic,phylogenetic (Koelle et al., 2006)

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proximal limits

Wikipedia: 1, 2

industrial (high-throughput) vs. artisanalbiology

limitations

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data

computation

algorithms

code complexity

theory??? (Breiman,2001; Pigliucci, 2009)

judgement &creativity???

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scaling laws

shall we keep on doingwhat we're doing? (Crome,1997)

http://www.genome.gov/sequencingcosts/

information vs. amountof raw data

data vs. time/$:Moore's law/"Eroom'slaw"(Scannell et al., 2012)

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references

Breiman, L. (2001). Statistical Modeling: The Two Cultures. Statistical Science, 16(3), 199–215.Retrieved from http://www.jstor.org/stable/2676681

Crome, F. H. J. (1997). Researching tropical forest fragmentation: Shall we keep on doing whatwe’re doing? In W. F. Laurance & J. Richard O. Bierregard (Eds.), Tropical forest remnants:Ecology, management and conservation of fragmented communities (pp. 485–501). Chicago:University of Chicago Press.

Gomory, R. (1995). The Known, the Unknown and the Unknowable. Scientific American.Retrieved from https://web.archive.org/web/20000531021133/http://www.sloan.org/programs/scitech_essay.htm

Koelle, K., Cobey, S., Grenfell, B., & Pascual, M. (2006). Epochal Evolution Shapes thePhylodynamics of Interpandemic Influenza A (H3N2) in Humans. Science, 314(5807),1898–1903. http://doi.org/10.1126/science.1132745

Levin, S. (2003). Complex adaptive systems: Exploring the known, the unknown and theunknowable. Bulletin of the American Mathematical Society, 40(1), 3–19. Retrieved fromhttp://www.ams.org/bull/2003-40-01/S0273-0979-02-00965-5/

Pigliucci, M. (2009). The end of theory in science? EMBO Reports, 10(6), 534. http://doi.org/10.1038/embor.2009.111

Scannell, J. W., Blanckley, A., Boldon, H., & Warrington, B. (2012). Diagnosing the decline inpharmaceutical R&D efficiency. Nature Reviews Drug Discovery, 11(3), 191–200. http://doi.org/10.1038/nrd3681

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