Barcelona Supercomputing Center
Prof Dr. Alfonso Valencia
ICREA Research Professor & BSC Life Sciences Department Director
ICREA & Barcelona Supercomputing Center (BSC)
The multilayer community structure of rare diseases
Multilayer networks consist of multiple layers of entities and features connected through relational associations. This graph framework has proven striking analytical advantages for heterogeneous data integration, especially the effective detection of communities of bio-entities, such as genes, to infer functional relationships and candidate drug targets based on multiple evidence sources. We have recently implemented a new methodology to identify groups of genes that are systematically found in the same multilayer communities at different levels of modularity resolution. Genes that are consistently found in the same multilayer communities can be deemed functionally associated based on the distinct layers of evidence. We have applied this approach to patient stratification in a number of rare diseases, including medulloblastoma, a childhood brain tumor, and congenital myasthenic syndromes, a group of conditions characterized by muscle weakness. Such models based on multilayer networks exhibit a high level of explainability as they explicitly inform on the multiple associations that characterize each condition enabling a mechanistic interpretation of the results and actionable insights.
Núñez-Carpintero I, Petrizzelli M, Zinovyev A, Cirillo D, Valencia A. The multilayer community structure of medulloblastoma. iScience. 2021;24(4):102365. PMID: 33889829. doi:10.1016/j.isci.2021.102365
Davide Cirillo, Ph.D. is a postdoctoral researcher at Barcelona Supercomputing Center (BSC) Computational Biology group, Life Sciences Department. Davide Cirillo received the MSc degree in Pharmaceutical Biotechnology from University of Roma ‘La Sapienza’, Italy, and the PhD degree in Biomedicine from Universitat Pompeu Fabra (UPF) and Center for Genomic Regulation (CRG) of Barcelona, Spain. His research is devoted to the development and application of computational methods in Precision Medicine with a special emphasis on Machine Learning and Artificial Intelligence.