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Methods of Microarray Data Analysis V 2007 ed. [Kõva köide]

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  • Formaat: Hardback, 176 pages, kõrgus x laius: 235x155 mm, kaal: 990 g, 115 Illustrations, black and white; XIV, 176 p. 115 illus., 1 Hardback
  • Ilmumisaeg: 07-Nov-2006
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 038734568X
  • ISBN-13: 9780387345680
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  • Formaat: Hardback, 176 pages, kõrgus x laius: 235x155 mm, kaal: 990 g, 115 Illustrations, black and white; XIV, 176 p. 115 illus., 1 Hardback
  • Ilmumisaeg: 07-Nov-2006
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 038734568X
  • ISBN-13: 9780387345680
Teised raamatud teemal:
As studies using microarray technology have evolved, so have the data analysis methods used to analyze these experiments. The CAMDA (Critical Assessment of Microarray Data Analysis) conference was the first to establish a forum for a cross section of researchers to look at a common data set and apply innovative analytical techniques to microarray data. Methods of Microarray Analysis V includes selected papers from CAMDA'04, and focuses on data sets relating to a significant global health issue, malaria. Previous books focused on classification (V. I), pattern recognition (V. II), quality control issues (V. III), and associating array data with a survival endpoint, lung cancer, (V. IV). The contributions come from research fields including statistics, biology, computer science and mathematics. Part of the book is devoted to review papers, which provide a more general look at various analytical approaches. It also presents some background readings for the advanced topics discussed in the CAMDA papers.

This book is dedicated solely to the analysis of microarray data. Its unique approach of presenting different methods by analyzing the same data set shows the strengths and weakness of each method. Part of the book is devoted to review papers, which provide a more general look at various analytical approaches. It also presents some background readings for the advanced topics discussed in the CAMDA papers.
Contributors vii
Introduction xi
Acknowledgements xiii
Data Mining of Malaria Parasite Gene Expression for Possible Translational Research
1(10)
Raphael D. Isokpehi
Constructing Probabilistic Genetic Networks of Plasmodium falciparum from Dynamical Expression Signals of the Intraerythrocytic Development Cycle
11(16)
Junior Barrera
Roberto M. Cesar Jr.
David C. Martins Jr.
Ricardo Z.N. Vencio
Emilio F. Merino
Marcio M. Yamamoto
Florencia G. Leonardi
Carlos A. de B. Pereira
Hernando A. del Portillo
Simple Methods for Peak and Valley Detection in Time Series Microarray Data
27(18)
A. Sboner
A. Romanel
A. Malossini
F. Ciocchetta
F. Demichelis
I. Azzini
E. Blanzieri
R. Dell'Anna
Oxidative Stress Genes in Plasmodium falciparum as Indicated by Temporal Gene Expression
45(14)
J. Noyola-Martinez
C. Shaw
B. Christian
G. Fox
M. Stevens
N. Garg
M.C. Gustin
R. Guerra
Identifying Stage-Specific Genes by Combining Information from Two Different Types of Oligonucleotide Arrays
59(16)
Yin Liu
Ning Sun
Junfeng Liu
Liang Chen
Michael McIntosh
Liangbiao Zheng
Hongyu Zhao
Construction of Malaria Gene Expression Network Using Partial Correlations
75(14)
Raya Khanin
Ernst Wit
Detecting Network Motifs in Gene Co-expression Networks Through Integration of Protein Domain Information
89(14)
Xinxia Peng
Michael A. Langston
Arnold M. Saxton
Nicole E. Baldwin
Jay R. Snoddy
Chromosomal Clustering of Periodically Expressed Genes in Plasmodium falciparum
103(18)
Pingzhao Hu
Celia M.T. Greenwood
Cyr Emile M'lan
Joseph Beyene
PlasmoTFBM: An Intelligent Queriable Database for Predicted Transcription Factor Binding Motifs in Plasmodium falciparum
121(16)
Chengyong Yang
Erliang Zeng
Kalai Mathee
Giri Narasimhan
Linking Gene Expression Patterns and Transcriptional Regulation in Plasmodium falciparum
137(20)
Aidan J. Peterson
Andrew V. Kossenkov
Michael F. Ochs
Chromosomal Spatial Correlation of Gene Expression in Plasmodium falciparum
157(16)
J.B. Christian
C. Shaw
J. Noyola-Martinez
M.C. Gustin
D.W. Scott
R. Guerra
Index 173