Qualitative Analysis of Gene Regulatory Networks Based on Angular Discretization

被引:0
|
作者
Wang Xuesong [1 ]
Liu Qingfeng [1 ]
Cheng Yuhu [1 ]
Li Lijing [1 ]
机构
[1] China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221116, Peoples R China
来源
CHINESE JOURNAL OF ELECTRONICS | 2011年 / 20卷 / 04期
基金
中国国家自然科学基金;
关键词
Gene regulatory network; Angle; Discretization; Qualitative analysis;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
It is well known that there is a hypothesis in the analysis of gene regulatory networks, i.e., if two genes expression profiles change in a similar trend, a regulatory relationship may exists in these two genes. Therefore, the use of angular discretization to deal with gene expression data can reflect the changes of gene expression values in tendency and intensity, which makes it possible to analyze the regulatory relationship between genes qualitatively. At first, we draw a line between the neighboring gene expression data. Thus an angle between the connected line and a horizontal line is formed. Secondly, according to the defined rules of angular discretization, we discretize the angle into six states by carrying out several times of discretization operation. The six states reflect not only the trend but also the change degree of gene expression values. In the end, the genes having regulatory relationships will be identified by using the substruction and the relative frequency methods. Experimental results concerning on the Saccharomyces microarray dataset verify the validity of the proposed method.
引用
收藏
页码:646 / 650
页数:5
相关论文
共 50 条
  • [1] Qualitative Analysis of Gene Regulatory Networks using Network Motifs
    Ito, Sohei
    Ichinose, Takuma
    Shimakawa, Masaya
    Izumi, Naoko
    Hagihara, Shigeki
    Yonzezaki, Naoki
    BIOINFORMATICS 2013: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON BIOINFORMATICS MODELS, METHODS AND ALGORITHMS, 2013, : 15 - 24
  • [2] An algorithm for qualitative simulation of Gene Regulatory Networks with steep sigmoidal response functions
    Ironi, Liliana
    Panzeri, Luigi
    Plahte, Erik
    ALGEBRAIC BIOLOGY, PROCEEDINGS, 2008, 5147 : 110 - +
  • [3] Centrality Analysis Methods for Biological Networks and Their Application to Gene Regulatory Networks
    Koschutzki, Dirk
    Schreiber, Falk
    GENE REGULATION AND SYSTEMS BIOLOGY, 2008, 2 : 193 - 201
  • [4] Inference of gene regulatory networks based on directed graph convolutional networks
    Wei, Pi-Jing
    Guo, Ziqiang
    Gao, Zhen
    Ding, Zheng
    Cao, Rui-Fen
    Su, Yansen
    Zheng, Chun-Hou
    BRIEFINGS IN BIOINFORMATICS, 2024, 25 (04)
  • [5] Interactive Identification based Modelling of Gene Regulatory Networks
    Ding Jie
    Dong Chunrong
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 6500 - 6502
  • [6] The analysis of Gene Regulatory Networks in plant evo-devo
    Vialette-Guiraud, Aurelie C. M.
    Andres-Robin, Amelie
    Chambrier, Pierre
    Tavares, Raquel
    Scutt, Charles P.
    JOURNAL OF EXPERIMENTAL BOTANY, 2016, 67 (09) : 2549 - 2563
  • [7] Genetic Algorithm with Gene Regulatory Networks based Optimization Method for Distributed Video Analysis System
    Inoue, Seishiro
    Yamauchi, Masaaki
    Kominami, Daichi
    Shimonishi, Hideyuki
    Murata, Masayuki
    PROCEEDINGS OF THE 27TH CONFERENCE ON INNOVATION IN CLOUDS, INTERNET AND NETWORKS, ICIN, 2024, : 257 - 264
  • [8] Computational methods for Gene Regulatory Networks reconstruction and analysis: A review
    Delgado, Fernando M.
    Gomez-Vela, Francisco
    ARTIFICIAL INTELLIGENCE IN MEDICINE, 2019, 95 : 133 - 145
  • [9] Evolving Gene Regulatory Networks: A Sensitivity-Based Approach
    Hsiao, Yu-Ting
    Lee, Wei-Po
    BIO-INSPIRED COMPUTING AND APPLICATIONS, 2012, 6840 : 508 - 513
  • [10] Prediction of gene regulatory networks based on graph attention mechanisms
    Fei, Shi Huang
    Zhu, Yuan
    2024 16TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND COMPUTING, ICMLC 2024, 2024, : 147 - 152