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EvoSysBio in 10 Slides

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posted on 02.01.2016, 09:39 authored by Laurence LoeweLaurence Loewe

Evolutionary Systems Biology is a new and growing field that  builds on the successes of evolutionary biology and systems biology in order to quantify evolution better. More thorough introductions can be found elsewhere (see refs on the last slide).

The purpose of this presentation is to summarize an extraordinarily rich conceptual framework in a nutshell of 10 slides to provide a quick overview. The guiding assumption is that the complete quantification of full fitness landscapes can be seen as a keystone that rests on and requires most or all other results from biology. Since biology has quite some way to go before this goal comes into reach, EvoSysBio is defining a framework for Landscapes of Incomplete Fitness Traits (LIFTs) to accelerate progress towards understanding evolution better and predicting it more accurately. LIFTs are like the building blocks of full fitness landscapes, which can also be seen as full fitness causality networks. Since LIFTs are much easier to observe and simulate, it should become possible to develop standardized forms in which to collect LIFT observations in order to help combine them into more comprehensive fitness causality networks.

EvoSysBio has a very long way to go before the ambitious goals presented here will come into reach for more complex systems, but we have to start somewhere. It took about 30 years from publishing faster sequencing methods to the era of genomics ...

These slides update and clarify the conceptual framework for EvoSysBio as presented elsewhere (eg. Loewe 2009, see ref below, which still contains the most thorough review of work demonstrating the feasibility of computationally predicting all LIFT types; however, please use the improved nomenclature presented on the slides here).

Many of the goals of EvoSysBio are too difficult to attain without an advanced programming language that supports biological concepts well. This realization has inspired the author to develop the new programming language Evolvix, which is being designed to enable EvoSysBio analyses and simultaneously make biological modelling easier in general (development of Evolvix is currently under way).

Producing these slides helped to clarify the long-term goals and a wide net of biology-related requirements, which drive the practical work on developing Evolvix as supported by the National Science Foundation.


National Science Foundation CAREER Award 1149123 to LL.