Cargando…

Biological Network Approaches and Applications in Rare Disease Studies

Network biology has the capability to integrate, represent, interpret, and model complex biological systems by collectively accommodating biological omics data, biological interactions and associations, graph theory, statistical measures, and visualizations. Biological networks have recently been sh...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Peng, Itan, Yuval
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6827097/
https://www.ncbi.nlm.nih.gov/pubmed/31614842
http://dx.doi.org/10.3390/genes10100797
_version_ 1783465246236606464
author Zhang, Peng
Itan, Yuval
author_facet Zhang, Peng
Itan, Yuval
author_sort Zhang, Peng
collection PubMed
description Network biology has the capability to integrate, represent, interpret, and model complex biological systems by collectively accommodating biological omics data, biological interactions and associations, graph theory, statistical measures, and visualizations. Biological networks have recently been shown to be very useful for studies that decipher biological mechanisms and disease etiologies and for studies that predict therapeutic responses, at both the molecular and system levels. In this review, we briefly summarize the general framework of biological network studies, including data resources, network construction methods, statistical measures, network topological properties, and visualization tools. We also introduce several recent biological network applications and methods for the studies of rare diseases.
format Online
Article
Text
id pubmed-6827097
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-68270972019-11-18 Biological Network Approaches and Applications in Rare Disease Studies Zhang, Peng Itan, Yuval Genes (Basel) Review Network biology has the capability to integrate, represent, interpret, and model complex biological systems by collectively accommodating biological omics data, biological interactions and associations, graph theory, statistical measures, and visualizations. Biological networks have recently been shown to be very useful for studies that decipher biological mechanisms and disease etiologies and for studies that predict therapeutic responses, at both the molecular and system levels. In this review, we briefly summarize the general framework of biological network studies, including data resources, network construction methods, statistical measures, network topological properties, and visualization tools. We also introduce several recent biological network applications and methods for the studies of rare diseases. MDPI 2019-10-12 /pmc/articles/PMC6827097/ /pubmed/31614842 http://dx.doi.org/10.3390/genes10100797 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Zhang, Peng
Itan, Yuval
Biological Network Approaches and Applications in Rare Disease Studies
title Biological Network Approaches and Applications in Rare Disease Studies
title_full Biological Network Approaches and Applications in Rare Disease Studies
title_fullStr Biological Network Approaches and Applications in Rare Disease Studies
title_full_unstemmed Biological Network Approaches and Applications in Rare Disease Studies
title_short Biological Network Approaches and Applications in Rare Disease Studies
title_sort biological network approaches and applications in rare disease studies
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6827097/
https://www.ncbi.nlm.nih.gov/pubmed/31614842
http://dx.doi.org/10.3390/genes10100797
work_keys_str_mv AT zhangpeng biologicalnetworkapproachesandapplicationsinrarediseasestudies
AT itanyuval biologicalnetworkapproachesandapplicationsinrarediseasestudies