An Exploratory Application of Multilayer Networks and Pathway Analysis in Pharmacogenomics

被引:3
|
作者
Milano, Marianna [1 ,2 ]
Agapito, Giuseppe [2 ,3 ]
Cannataro, Mario [2 ,4 ]
机构
[1] Magna Graecia Univ Catanzaro, Dept Expt & Clin Med, I-88100 Catanzaro, Italy
[2] Magna Graecia Univ Catanzaro, Data Analyt Res Ctr, I-88100 Catanzaro, Italy
[3] Magna Graecia Univ Catanzaro, Dept Law Econ & Social Sci, I-88100 Catanzaro, Italy
[4] Magna Graecia Univ Catanzaro, Dept Med & Surg Sci, I-88100 Catanzaro, Italy
关键词
pharmacogenomics; network analysis; multilayer networks; community detection; pathway enrichment analysis; PROTEIN-PROTEIN INTERACTION; DRUG; IDENTIFICATION;
D O I
10.3390/genes14101915
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Over the years, network analysis has become a promising strategy for analysing complex system, i.e., systems composed of a large number of interacting elements. In particular, multilayer networks have emerged as a powerful framework for modelling and analysing complex systems with multiple types of interactions. Network analysis can be applied to pharmacogenomics to gain insights into the interactions between genes, drugs, and diseases. By integrating network analysis techniques with pharmacogenomic data, the goal consists of uncovering complex relationships and identifying key genes to use in pathway enrichment analysis to figure out biological pathways involved in drug response and adverse reactions. In this study, we modelled omics, disease, and drug data together through multilayer network representation. Then, we mined the multilayer network with a community detection algorithm to obtain the top communities. After that, we used the identified list of genes from the communities to perform pathway enrichment analysis (PEA) to figure out the biological function affected by the selected genes. The results show that the genes forming the top community have multiple roles through different pathways.
引用
收藏
页数:14
相关论文
共 50 条
  • [21] Application of MultiLayer Perceptron Networks in public key cryptography
    Yee, LP
    De Silva, LC
    PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3, 2002, : 1439 - 1443
  • [22] Application of MultiLayer Perceptron Networks in symmetric block ciphers
    Yee, LP
    De Silva, LC
    PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3, 2002, : 1455 - 1458
  • [23] Multilayer Aggregation with Statistical Validation: Application to Investor Networks
    Kęstutis Baltakys
    Juho Kanniainen
    Frank Emmert-Streib
    Scientific Reports, 8
  • [24] A Comprehensive Analysis of Multilayer Community Detection Algorithms for Application to EEG-Based Brain Networks
    Puxeddu, Maria Grazia
    Petti, Manuela
    Astolfi, Laura
    FRONTIERS IN SYSTEMS NEUROSCIENCE, 2021, 15
  • [25] Exploratory Factor Analysis of Pathway Copy Number Data with an Application Towards the Integration with Gene Expression Data
    Van Wieringen, Wessel N.
    Van De Wiel, Mark A.
    JOURNAL OF COMPUTATIONAL BIOLOGY, 2011, 18 (05) : 729 - 741
  • [26] Random hypernets in reliability analysis of multilayer networks
    Rodionov, Alexey
    Rodionova, Olga
    Lecture Notes in Electrical Engineering, 2015, 343 : 307 - 315
  • [27] Reliability analysis of multilayer multistage interconnection networks
    Fathollah Bistouni
    Mohsen Jahanshahi
    Telecommunication Systems, 2016, 62 : 529 - 551
  • [28] Modeling of Multilayer Networks for Fault Restoration Analysis
    Tsirakakis, George
    Clarkson, Trevor
    JOURNAL OF INTERNET TECHNOLOGY, 2009, 10 (01): : 73 - 78
  • [29] MuxViz: a tool for multilayer analysis and visualization of networks
    De Domenico, Manlio
    Porter, Mason A.
    Arenas, Alex
    JOURNAL OF COMPLEX NETWORKS, 2015, 3 (02) : 159 - 176
  • [30] Reliability analysis of multilayer multistage interconnection networks
    Bistouni, Fathollah
    Jahanshahi, Mohsen
    TELECOMMUNICATION SYSTEMS, 2016, 62 (03) : 529 - 551