Objective
Reconstructing the historical (phylogenetic) interrelationships of biological entities (e.g. taxa, species, genes) is a substantial goal of evolutionary biology not least because knowledge of these relationships facilitates the interpretation of all comparative biological data. Due to continuing improvement of sequencing techniques and computational power within the last 20 years, molecular phylogenetic analyses have expanded steadily from single gene analyses of small taxon sets up to phylogenomic analyses of many hundreds of genes and taxa. However, this is not always a simple task – particularly when the data are subject to systematic biases that can mislead the most commonly relied upon methods. In such cases, increasing the amount of data can make recovering the correct relationships harder rather than easier. The main aim of this project is to develop and evaluate new intelligent tree reconstruction algorithms based on specific split pattern analyses among multiple sequence alignments and/or morphological character patterns that will enable a significantly more reliable and accurate reconstruction of phylogenetic trees, and ultimately the Tree of Life. The main focus is on overcoming the analytical difficulties or systematic biases resulting from branch specific heterogeneities of evolutionary substitution rates leading to the widespread analytical artefact known as Long Branch Attraction (LBA). It is anticipated that the strategies developed will have broad applicability, that they will complement existing methods and will help to resolve longstanding phylogenetic problems that appear to have been confounded by LBA. By facilitating the production of more accurate phylogenetic trees, it is expected that the new algorithms will help deliver better foundations for all branches of comparative biology. The new developed reconstruction algorithms will be implemented into an existing pipeline and thoroughly tested with both simulated and empirical data.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
FP7-PEOPLE-2013-IEF
See other projects for this call
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
SW7 5BD London
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.