Algorithms for Genomic Sequence Analysis

Algorithms for Genomic Sequence Analysis group

Modern high throughput sequencing technologies allow impressively fast and cheap sequencing capacities, making a huge amount of genomic sequences available to the broad scientific community. This calls for sophisticated algorithms and data structures for their in silico investigation. We design and realize efficient algorithms for features discovery of large collections of biological sequences, trees, and graphs/networks.

Members

Projects

ALPACA (ALgorithms for PAngenome Computational Analysis)

EU funded Innovative Training Network (ITN), 2021.

(Abstract | Links)

ALPACA (ALgorithms for PAngenome Computational Analysis) is an EU funded Innovative Training Network for talented PhD Students.
In view of ultra-large amounts of genome sequence data emerging from rapidly advancing genome sequencing devices the driving, urgent question is: How can we arrange and analyze these data masses in a formally rigorous, computationally efficient and biomedically rewarding manner?
Graph based data structures have been pointed out to have disruptive benefits over traditional sequence based structures when representing pan-genomes. This paradigm shift from sequences to graphs requires to make substantial advances in terms of algorithms and data structures.

Metodi Informatici Integrati per la Biomedica

PRA – Progetti di Ricerca di Ateneo (Institutional Research Grants) - Project no. PRA_2020-2021_26 , 2020.

(Abstract)

This project aims at integrating different computer methodologies that contribute to interdisciplinary research in bioinformatics and, in particular, to its applications in the biomedical field. This in order to experiment the co-existence of algorithmic, modeling, and machine learning methods in the analysis of biomedical data and, at the same time, to refine the synergy of the many research groups that have been active in the Department of Computer Science for decades.