Literature DB >> 31382052

A paradigm shift in medicine: A comprehensive review of network-based approaches.

Federica Conte1, Giulia Fiscon2, Valerio Licursi3, Daniele Bizzarri4, Tommaso D'Antò5, Lorenzo Farina5, Paola Paci1.   

Abstract

Network medicine is a rapidly evolving new field of medical research, which combines principles and approaches of systems biology and network science, holding the promise to uncovering the causes and to revolutionize the diagnosis and treatments of human diseases. This new paradigm reflects the fact that human diseases are not caused by single molecular defects, but driven by complex interactions among a variety of molecular mediators. The complexity of these interactions embraces different types of information: from the cellular-molecular level of protein-protein interactions to correlational studies of gene expression and regulation, to metabolic and disease pathways up to drug-disease relationships. The analysis of these complex networks can reveal new disease genes and/or disease pathways and identify possible targets for new drug development, as well as new uses for existing drugs. In this review, we offer a comprehensive overview of network types and algorithms used in the framework of network medicine. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Dr. Federico Manuel Giorgi and Dr. Shaun Mahony.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Algorithms; Complex biological networks; Network medicine; Precision medicine

Year:  2019        PMID: 31382052     DOI: 10.1016/j.bbagrm.2019.194416

Source DB:  PubMed          Journal:  Biochim Biophys Acta Gene Regul Mech        ISSN: 1874-9399            Impact factor:   4.490


  31 in total

1.  The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets.

Authors:  Damian Szklarczyk; Annika L Gable; Katerina C Nastou; David Lyon; Rebecca Kirsch; Sampo Pyysalo; Nadezhda T Doncheva; Marc Legeay; Tao Fang; Peer Bork; Lars J Jensen; Christian von Mering
Journal:  Nucleic Acids Res       Date:  2021-01-08       Impact factor: 16.971

2.  An integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test case.

Authors:  Anup Mammen Oommen; Stephen Cunningham; Páraic S O'Súilleabháin; Brian M Hughes; Lokesh Joshi
Journal:  Sci Rep       Date:  2021-05-06       Impact factor: 4.379

Review 3.  Disease-specific interactome alterations via epichaperomics: the case for Alzheimer's disease.

Authors:  Stephen D Ginsberg; Thomas A Neubert; Sahil Sharma; Chander S Digwal; Pengrong Yan; Calin Timbus; Tai Wang; Gabriela Chiosis
Journal:  FEBS J       Date:  2021-06-12       Impact factor: 5.622

4.  Identifying Drug Targets in Pancreatic Ductal Adenocarcinoma Through Machine Learning, Analyzing Biomolecular Networks, and Structural Modeling.

Authors:  Wenying Yan; Xingyi Liu; Yibo Wang; Shuqing Han; Fan Wang; Xin Liu; Fei Xiao; Guang Hu
Journal:  Front Pharmacol       Date:  2020-04-30       Impact factor: 5.810

5.  Quiescent stem cell marker genes in glioma gene networks are sufficient to distinguish between normal and glioblastoma (GBM) samples.

Authors:  Shradha Mukherjee
Journal:  Sci Rep       Date:  2020-07-02       Impact factor: 4.379

Review 6.  Differential Co-Expression Analyses Allow the Identification of Critical Signalling Pathways Altered during Tumour Transformation and Progression.

Authors:  Aurora Savino; Paolo Provero; Valeria Poli
Journal:  Int J Mol Sci       Date:  2020-12-12       Impact factor: 5.923

7.  Personalized analysis of breast cancer using sample-specific networks.

Authors:  Ke Zhu; Cong Pian; Qiong Xiang; Xin Liu; Yuanyuan Chen
Journal:  PeerJ       Date:  2020-05-15       Impact factor: 2.984

8.  Bioinformatic Reconstruction and Analysis of Gene Networks Related to Glucose Variability in Diabetes and Its Complications.

Authors:  Olga V Saik; Vadim V Klimontov
Journal:  Int J Mol Sci       Date:  2020-11-18       Impact factor: 5.923

9.  Systems Level Analysis and Identification of Pathways and Key Genes Associated with Delirium.

Authors:  Yukiko Takahashi; Tomoyoshi Terada; Yoshinori Muto
Journal:  Genes (Basel)       Date:  2020-10-19       Impact factor: 4.096

10.  The risk of pancreatic adenocarcinoma following SARS-CoV family infection.

Authors:  Amin Ebrahimi Sadrabadi; Ahmad Bereimipour; Arsalan Jalili; Mazaher Gholipurmalekabadi; Behrouz Farhadihosseinabadi; Alexander M Seifalian
Journal:  Sci Rep       Date:  2021-06-21       Impact factor: 4.379

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