What we do
The Applied Computational Genomics Team focuses on theoretical and computational aspects of modelling the process of genome evolution and adaptive change. With the growing size and complexity of molecular data, we strive to keep pace by providing accurate, scalable and practical computational solutions that enable a wide range of scientists to analyse patterns of evolution and natural selection in large genomic and omics data. We develop bioinformatic methods for real applications, ranging from biotechnology to biomedical research, ecology and agriculture.
More recently, we also worked on data integration as part of the NRP75 Bigdata project that aims at enabling sophisticated semantic queries across large, decentralized and heterogeneous databases via an intuitive interface.
As a follow-up of this project, we develop an automated Literature Based Discovery (LBD) system in the context of natural product drugs, using Semantic Web technologies.
Find out about the Group’s activities
Main publications 2020
- Delucchi M et al.
A New Census of Protein Tandem Repeats and Their Relationship with Intrinsic Disorder
Genes, 10.3390/genes11040407 - Maiolo M et al.
Accelerating phylogeny-aware alignment with indel evolution using short time Fourier transform
NAR Genomics and Bioinformatics, 10.1093/nargab/lqaa092 - Koroleva A et al.
Towards creating a new triple store for literature-based discovery
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12237), 10.1007/978-3-030-60470-7_5
