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Biochemistry Seminar | Alex Gavryushkin, Department of Computer Science

Fitness landscapes, genetic interactions, and inexact data

In this talk I will present a mathematical approach (no background in mathematics will be necessary) to fitness landscapes. The approach is applicable to any (one-­‐dimensional) quantitative measure (phenotype) associated to genotypes, not necessarily fitness. The approach allows to characterise fitness landscapes in terms of their "shapes" and opens up a rich toolbox of (statistical) algebraic geometry available to analyse the landscapes. 

A fitness landscape carries comprehensive information about the genetic system with respect to the phenotype under consideration. In particular, genetic interaction, including higher-­‐order, are encoded into the landscape.

However, due to the imprecise nature of fitness (phenotype) measurements, statistical uncertainty makes fitness landscape inference a challenging problem.

Remarkably, several characteristics of fitness landscape, including higher‐order genetic interactions, can be robustly learned in highly uncertain scenarios.

I will demonstrate how this result can be used in practice, without any knowledge of mathematics.

Date Tuesday, 24 April 2018
Time 12:00pm - 1:00pm
Audience Public
Event Category Health Sciences
Event Type Seminar
LocationBiochemistry seminar rm 231

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