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...
Autores principales: | , |
---|---|
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 |