Computational methods with applications in bioinformatics analysis

by Ng, Ka-Lok Tsai, Jeffrey J. P.

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Title Statements

Full title :Computational methods with applications in bioinformatics analysis / editors, Jeffrey J.P. Tsai, Ka-Lok Ng, Asia University, Taiwan.

Summary

"This compendium contains 10 chapters written by world renowned researchers with expertise in semantic computing, genome sequence analysis, biomolecular interaction, time-series microarray analysis, and machine learning algorithms. The salient feature of this book is that it highlights eight types of computational techniques to tackle different biomedical applications. These techniques include unsupervised learning algorithms, principal component analysis, fuzzy integral, graph-based ensemble clustering method, semantic analysis, interolog approach, molecular simulations and enzyme kinetics. The unique volume will be a useful reference material and an inspirational read for advanced undergraduate and graduate students, computer scientists, computational biologists, bioinformatics and biomedical professionals."--Publisher's website.

Edition Statements

Publication Date:2017

Publication Statements

Publisher(s):World Scientific
Place of Publication:New Jersey
Language:eng
Publication Date:2017

The Physical Object

Description:1 online resource

Edition Identifiers

ISBN:9789813207981, 9813207981, 9789813207998, 981320799X
oclc:ocn992782758
LC Classification:QH324.2
Dewey Decimal:570.285

Preface; Acknowledgment; About the Authors; List of Contributors; Chapter 1. Unsupervised clustering of time series gene expression data based on spectrum processing and autoregressive modeling; 1.1 Introduction; 1.2 Literature Review; 1.2.1 Cluster Analysis of Time Series Gene Expression; 1.2.2 Clustering Algorithm; 1.2.2.1 K-Means; 1.2.2.2 Hierarchical; 1.2.2.3 SOM; 1.2.2.4 CRC; 1.3 Methods; 1.3.1 Data Processing Algorithm; 1.3.2 Data Preprocessing; 1.3.3 Spectrum Transform; 1.3.4 Singular Value Decomposition; 1.3.5 Autoregressive Modeling; 1.4 Experimental Results and Analysis

1.4.1 Evaluation Methods; 1.4.1.1 Silhouette Index; 1.4.1.2 Wilcoxon Rank-Sum Test; 1.4.2 Experimental Data; 1.4.2.1 Dataset #1: AD400_10_10 (Bandyopadhyay et al. [2]); 1.4.2.2 Dataset #2: Human Fibroblasts Serum (Eisen et al. [12]); 1.4.2.3 Dataset #3: Yeast sporulation (Chu et al. [8]); 1.4.2.4 Dataset #4: Rat CNS (Wen et al. [26]); 1.4.2.5 Dataset #5: S. cerevisiae (Cho et al. [7]); 1.4.2.6 Dataset #6: S. cerevisiae (Spellman et al. [22]); 1.4.3 Experimental Results; 1.4.3.1 Experimental Parameter Settings; 1.4.3.2 Analysis and Comparison of Experimental Results

1.4.4 Analysis of Correlation with Bio…