Improved tree view for visualising microarray gene expression data

被引:0
|
作者
Prasad T.V. [1 ]
Ahson S.I. [2 ]
机构
[1] Lingaya's University
[2] Patna University, Patna 800 005, Bihar
关键词
Bioinformatics; Data mining; Microarray gene expression data; Tree view; Visualisation;
D O I
10.1504/IJICT.2010.034974
中图分类号
学科分类号
摘要
The tree view visualisation provides basis for phylogenetic analysis as well as relationship between various elements in a set or collection. It also presents one of the most elegant representations of microarray data analysis results. The classical Eisen Tree View software is the most widely used software for visualisation of microarray gene expression data. Certain anomalies in the software were found, which have been brought out and improved through newly developed software called Gene Expression Data Analysis Suite (GEDAS). Further, the algorithm has been modified to represent duplicate entries, if any, present in the dataset. A method of conversion of tree view output into cluster view form is another highlight. Through this paper, certain other features of such tree representations have been discussed. Copyright © 2010 Inderscience Enterprises Ltd.
引用
收藏
页码:323 / 330
页数:7
相关论文
共 50 条
  • [31] Bayesian models for gene expression with DNA microarray data
    Ibrahim, JG
    Chen, MH
    Gray, RJ
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2002, 97 (457) : 88 - 99
  • [32] Statistical Quality Control of Microarray Gene Expression Data
    Lu, Shen
    Segall, Richard S.
    WMSCI 2011: 15TH WORLD MULTI-CONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL I, 2011, : 206 - 211
  • [33] MIDGET:Detecting differential gene expression on microarray data
    Angelescu, Radu
    Dobrescu, Radu
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2021, 211
  • [34] Quick hierarchical biclustering on microarray gene expression data
    Ji, Liping
    Mock, Kenneth Wei-Liang
    Tan, Kian-Lee
    BIBE 2006: SIXTH IEEE SYMPOSIUM ON BIOINFORMATICS AND BIOENGINEERING, PROCEEDINGS, 2006, : 110 - +
  • [35] A genetic approach for gene selection on microarray expression data
    Kim, YH
    Lee, SY
    Moon, BR
    GENETIC AND EVOLUTIONARY COMPUTATION - GECCO 2004, PT 1, PROCEEDINGS, 2004, 3102 : 346 - 355
  • [36] An efficient approach for classification of gene expression microarray data
    Sreepada, Rama Syamala
    Vipsita, Swati
    Mohapatra, Puspanjali
    2014 FOURTH INTERNATIONAL CONFERENCE OF EMERGING APPLICATIONS OF INFORMATION TECHNOLOGY (EAIT), 2014, : 344 - 348
  • [37] Differential analysis of DNA microarray gene expression data
    Hatfield, GW
    Hung, SP
    Baldi, P
    MOLECULAR MICROBIOLOGY, 2003, 47 (04) : 871 - 877
  • [38] AVA: visual analysis of gene expression microarray data
    Zhou, YH
    Liu, JD
    BIOINFORMATICS, 2003, 19 (02) : 293 - 294
  • [39] Covariance structure models for gene expression microarray data
    Xie, J
    Bentler, PM
    STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, 2003, 10 (04) : 566 - 582
  • [40] The Impact of Gene Selection on Imbalanced Microarray Expression Data
    Kamal, Abu H. M.
    Zhu, Xingquan
    Pandya, Abhijit S.
    Hsu, Sam
    Shoaib, Muhammad
    BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, PROCEEDINGS, 2009, 5462 : 259 - 269