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Content archived on 2024-06-18

Computational methods for biological sequence analysis with application to evolution of yeast mitochondrial genomes

Objective

Modern molecular biology relies on high-throughput technologies to generate large quantities of data about components of living cells and on sophisticated mathematical and computational techniques for analyzing this data. We will develop new algorithms and probabilistic models in areas of comparative genomics, gene finding, and homology search. In particular, we propose a new class of evolutionary models for modeling changes in exon structure of protein coding genes. These models have applications in gene finding and ancestral sequence reconstruction. We will also develop more efficient methods for homology search in large databases containing families of related sequences. Finally, we will apply both existing and new methods to comparative analysis of mitochondrial genomes in Candida genus. Some of these genomes have linear chromosomes terminated with telomere-like structures similar to eukaryotic nuclear chromosomes, yet of independent evolutionary origin. By studying these sequences, we aim to address fundamental questions of evolution of linear genomes and telomeric regions, and evolution of binding specificity in DNA binding proteins. This interdisciplinary project will be carried out in cooperation with researchers from both computer science and biology at Comenius University in Bratislava.

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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

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Call for proposal

FP7-PEOPLE-IRG-2008
See other projects for this call

Coordinator

UNIVERZITA KOMENSKEHO V BRATISLAVE
EU contribution
€ 100 000,00
Address
SAFARIKOVO NAM 6
814 99 Bratislava
Slovakia

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Region
Slovensko Bratislavský kraj Bratislavský kraj
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data
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