Opendata, web and dolomites

OptimHist SIGNED

Optimization and historical contingency in living systems: a biophysical approach

Total Cost €


EC-Contrib. €






Project "OptimHist" data sheet

The following table provides information about the project.


Organization address
address: BATIMENT CE 3316 STATION 1
postcode: 1015

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Switzerland [CH]
 Total cost 1˙498˙214 €
 EC max contribution 1˙498˙214 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2019-STG
 Funding Scheme ERC-STG
 Starting year 2020
 Duration (year-month-day) from 2020-03-01   to  2025-02-28


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Populations of living organisms are pushed to optimality by evolution, but may also be shaped by the contingency of their evolutionary history. The recent explosion of sequence data gives us access to the outcomes of molecular evolution, and controlled microbial evolution experiments allow us to analyze the predictability of evolution. In this exciting context, I aim to explore quantitatively the importance of optimization and contingency both at the molecular scale and at the scale of populations of microorganisms, using a theoretical biophysical approach.

First, I will assess how functional optimization and evolutionary history, i.e. phylogeny, shape protein sequences. Importantly, correlations arising from phylogeny are a double-edged sword, often confounding signal from functional optimization, but sometimes providing useful complementary information. I will improve sequence-based predictions for protein-protein interactions by exploiting information both from phylogeny and from the required complementarity of interacting residues. I will disentangle the collective modes of correlations in protein sequences due to optimization from those due to phylogeny, and investigate the importance of functional sectors as an organizing principle of proteins. This will be a breakthrough in our understanding of the sequence-function relationship of proteins.

Second, I will analyze the impact of optimization and contingency on the evolution of microbial populations. I will study microorganisms with a rugged fitness landscape presenting several optima. In these realistic cases, populations tend to remain trapped in local optima. However, most real populations possess specific geographic structures. I will quantitatively study how structure helps populations to explore model and real rugged fitness landscapes. I will build a universal model of structured populations. I will then focus on important applications to antimicrobial resistance evolution and to expanding populations.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "OPTIMHIST" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email ( and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "OPTIMHIST" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.1.)

BABE (2018)

Why is the world green: testing top-down control of plant-herbivore food webs by experiments with birds, bats and ants

Read More  

EnTER (2020)

Enhanced Mass Transport in Electrochemical Systems for Renewable Fuels and Clean Water

Read More  


Using hidden genealogical structure to study the architecture of human disease

Read More