Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Deepening the knowledge of rare diseases dependent on angiogenesis through semantic similarity clustering and network analysis.

Briefings in bioinformatics - 18 Jul 2022

Pagano-Márquez Raquel, Córdoba-Caballero José, Martínez-Poveda Beatriz, Quesada Ana R, Rojano Elena, Seoane Pedro, Ranea Juan A G, Ángel Medina Miguel

Abstract excerpt

BACKGROUND: 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...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Algorithms
Share to Cluster Analysis

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Computational Biology

Share to Phenotype

Share to Rare Diseases

Share to Semantics

Source

Open in PubMed Open full text

Identifiers

PMID: 35731990
DOI: 10.1093/bib/bbac220
PMCID: PMC9294413

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Deepening the knowledge of rare diseases dependent on angiogenesis through semantic similarity clustering and network analysis.PMID 35731990Read ↗

Rare disease relations through common genes and protein interactions.Semantic proximity Read ↗

BfBio: a graph-based tool for the prediction of Angiogenic Stalk Cell genes using a Personalized PageRank algorithmSemantic proximity Read ↗

Gene expression integration and similarity score-based modeling improve risk stratification in idiopathic venous thrombophilia.Semantic proximity Read ↗

Detection of characteristic sub pathway network for angiogenesis based on the comprehensive pathway network.Semantic proximity Read ↗

Genome-wide profiling of angiogenic cis-regulatory elements unravels cis-regulatory SNPs for vascular abnormality.Semantic proximity Read ↗

Common denominator procedure: a novel approach to gene-expression data mining for identification of phenotype-specific genes.Semantic proximity Read ↗

Phenotypic categorization of genetic skin diseases reveals new relations between phenotypes, genes and pathways.Semantic proximity Read ↗

Integration of anatomy ontology data with protein-protein interaction networks improves the candidate gene prediction accuracy for anatomical entitiesSemantic proximity Read ↗

A Knowledge Graph Analytical Platform for Facial Phenotype-Genotype-Disease Associations in Rare Genetic DiseasesSemantic proximity Read ↗

Integration of anatomy ontology data with protein-protein interaction networks improves the candidate gene prediction accuracy for anatomical entities.Semantic proximity Read ↗

Omics meets hypothesis-driven research. Partnership for innovative discoveries in vascular biology and angiogenesis.Semantic proximity Read ↗

A phenotype driven integrative framework uncovers molecular mechanisms of a rare hereditary thrombophilia.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.