RT Journal Article
T1 Deepening the knowledge of rare diseases dependent on angiogenesis through semantic similarity clustering and network analysis.
A1 Pagano-Márquez, Raquel
A1 Córdoba-Caballero, José
A1 Martínez-Poveda, Beatriz
A1 Quesada, Ana R
A1 Rojano, Elena
A1 Seoane, Pedro
A1 Ranea, Juan A G
A1 Ángel Medina, Miguel
K1 angiogenesis
K1 disease clustering
K1 rare diseases
K1 semantic similarity
K1 systems biology
AB Angiogenesis is regulated by multiple genes whose variants can lead to different disorders. Among them, rare diseases are a heterogeneous group of pathologies, most of them genetic, whose information may be of interest to determine the still unknown genetic and molecular causes of other diseases. In this work, we use the information on rare diseases dependent on angiogenesis to investigate the genes that are associated with this biological process and to determine if there are interactions between the genes involved in its deregulation. We propose a systemic approach supported by the use of pathological phenotypes to group diseases by semantic similarity. We grouped 158 angiogenesis-related rare diseases in 18 clusters based on their phenotypes. Of them, 16 clusters had traceable gene connections in a high-quality interaction network. These disease clusters are associated with 130 different genes. We searched for genes associated with angiogenesis througth ClinVar pathogenic variants. Of the seven retrieved genes, our system confirms six of them. Furthermore, it allowed us to identify common affected functions among these disease clusters. https://github.com/ElenaRojano/angio_cluster. seoanezonjic@uma.es and elenarojano@uma.es.
YR 2022
FD 2022
LK http://hdl.handle.net/10668/19705
UL http://hdl.handle.net/10668/19705
LA en
DS RISalud
RD Apr 9, 2025