Regular Expression Based Pattern Matching for Gene Expression Data to Identify the Abnormality Gnome

被引：3

作者：

Sharmila, L. ^{[1
]}

Sakthi, U. ^{[2
]}

Geethanjali, A. ^{[3
]}

Sagadevan, Suresh ^{[4
]}

机构：

[1] Sathyabama Univ, Dept Comp Sci & Engn, Fac CSE, Madras, Tamil Nadu, India

[2] St Josephs Inst Technol, Dept Comp Sci & Engn, Madras, Tamil Nadu, India

[3] Alpha Coll Engn, Dept Comp Sci & Engn, Madras, Tamil Nadu, India

[4] AMET Univ, Dept Phys, Madras, Tamil Nadu, India

来源：

2017 SECOND INTERNATIONAL CONFERENCE ON RECENT TRENDS AND CHALLENGES IN COMPUTATIONAL MODELS (ICRTCCM) | 2017年

关键词：

Pattern Matching; Regular Expression; Gene Expression Data; Clustering; Data Mining; MOUSE-BRAIN; IDENTIFICATION; ATLAS; MODEL;

D O I：

10.1109/ICRTCCM.2017.71

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The main idea of this paper is to detect and extract an input pattern from a gene expression dataset. Human behavior and health conditions can be identified and classified through their genomic data in accurate manner. In this paper it is motivated to search and identify the abnormal pattern availability in a gene expression data. To do this a Regular Expression based Pattern Matching (REPM) method is proposed for detecting, identifying and counting number of abnormal pattern occurrences in a given dataset. This approach is experimented in MATLAB software the results verified to check the efficiency of REPM method.

引用

页码：301 / 305

页数：5

共 36 条

[1] Linkage of cDNA expression profiles of mesencephalic dopaminergic neurons to a genome-wide in situ hybridization database
Alavian, Kambiz N.
Simon, Horst H.
[J]. MOLECULAR NEURODEGENERATION, 2009, 4
[2] [Anonymous], PATTERN DETECTION DI
[3] Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy
Bohland, Jason W.
Bokil, Hemant
Pathak, Sayan D.
Lee, Chang-Kyu
Ng, Lydia
Lau, Christopher
Kuan, Chihchau
Hawrylycz, Michael
Mitra, Partha P.
[J]. METHODS, 2010, 50 (02) : 105 - 112
[4] Identification of a set of genes showing regionally enriched expression in the mouse brain
D'Souza, Cletus A.
Chopra, Vikramjit
Varhol, Richard
Xie, Yuan-Yun
Bohacec, Slavita
Zhao, Yongjun
Lee, Lisa L. C.
Bilenky, Mikhail
Portales-Casamar, Elodie
He, An
Wasserman, Wyeth W.
Goldowitz, Daniel
Marra, Marco A.
Holt, Robert A.
Simpson, Elizabeth M.
Jones, Steven J. M.
[J]. BMC NEUROSCIENCE, 2008, 9 (1)
[5] A tool for identification of genes expressed in patterns of interest using the Allen Brain Atlas
Davis, Fred P.
Eddy, Sean R.
[J]. BIOINFORMATICS, 2009, 25 (13) : 1647 - 1654
[6] Genomic-anatomic evidence for distinct functional domains in hippocampal field CA1
Dong, Hong-Wei
Swanson, Larry W.
Chen, Lin
Fanselow, Michael S.
Toga, Arthur W.
[J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2009, 106 (28) : 11794 - 11799
[7] Relationships between Gene Expression and Brain Wiring in the Adult Rodent Brain
French, Leon
Pavlidis, Paul
[J]. PLOS COMPUTATIONAL BIOLOGY, 2011, 7 (01)
[8] Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring
Golub, TR
Slonim, DK
Tamayo, P
Huard, C
Gaasenbeek, M
Mesirov, JP
Coller, H
Loh, ML
Downing, JR
Caligiuri, MA
Bloomfield, CD
Lander, ES
[J]. SCIENCE, 1999, 286 (5439) : 531 - 537
[9] Cell-type-based model explaining coexpression patterns of genes in the brain
Grange, Pascal
Bohland, Jason W.
Okaty, Benjamin W.
Sugino, Ken
Bokil, Hemant
Nelson, Sacha B.
Ng, Lydia
Hawrylycz, Michael
Mitra, Partha P.
[J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2014, 111 (14) : 5397 - 5402
[10] Expression profile of the entire family of Adhesion G protein-coupled receptors in mouse and rat
Haitina, Tatjana
Olsson, Fredrik
Stephansson, Olga
Alsio, Johan
Roman, Erika
Ebendal, Ted
Schioth, Helgi B.
Fredriksson, Robert
[J]. BMC NEUROSCIENCE, 2008, 9 (1)

← 1 2 3 4 →