Lopes H.S., Cruz L.M. (eds.) Computational Biology and Applied Bioinformatics
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COMPUTATIONAL
BIOLOGY AND APPLIED
BIOINFORMATICS
Edited by Heitor Silvério Lopes
and Leonardo Magalhães Cruz
Computational Biology and Applied Bioinformatics
Edited by Heitor Silvério Lopes and Leonardo Magalhães Cruz
Published by InTech
Janeza Trdine 9, 51000 Rijeka, Croatia
Copyright © 2011 InTech
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Image Copyright Gencay M. Emin, 2010. Used under license from Shutterstock.com
First published August, 2011
Printed in Croatia
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Additional hard copies can be obtained from orders@intechweb.org
Computational Biology and Applied Bioinformatics,
Edited by Heitor Silvério Lopes and Leonardo Magalhães Cruz
p. cm.
ISBN 978-953-307-629-4
free online editions of InTech
Books and Journals can be found at
www.intechopen.com
Contents
Preface IX
Part 1 Reviews 1
Chapter 1 Molecular Evolution & Phylogeny:
What, When, Why & How? 3
Pandurang Kolekar, Mohan Kale and Urmila Kulkarni-Kale
Chapter 2 Understanding Protein Function - The Disparity
Between Bioinformatics and Molecular Methods 29
Katarzyna Hupert-Kocurek and Jon M. Kaguni
Chapter 3 In Silico Identification
of Regulatory Elements in Promoters 47
Vikrant Nain, Shakti Sahi and Polumetla Ananda Kumar
Chapter 4 In Silico Analysis of Golgi Glycosyltransferases:
A Case Study on the LARGE-Like Protein Family 67
Kuo-Yuan Hwa, Wan-Man Lin and Boopathi Subramani
Chapter 5 MicroArray Technology - Expression Profiling
of MRNA and MicroRNA in Breast Cancer 87
Aoife Lowery, Christophe Lemetre, Graham Ball and Michael Kerin
Chapter 6 Computational Tools for Identification
of microRNAs in Deep Sequencing Data Sets 121
Manuel A. S. Santos and Ana Raquel Soares
Chapter 7 Computational Methods in Mass
Spectrometry-Based Protein 3D Studies 133
Rosa M. Vitale, Giovanni Renzone,
Andrea Scaloni and Pietro Amodeo
Chapter 8 Synthetic Biology & Bioinformatics
Prospects in the Cancer Arena 159
Lígia R. Rodrigues and Leon D. Kluskens
VI Contents
Chapter 9 An Overview of Hardware-Based
Acceleration of Biological Sequence Alignment 187
Laiq Hasan and Zaid Al-Ars
Part 2 Case Studies 203
Chapter 10 Retrieving and Categorizing Bioinformatics
Publications through a MultiAgent System 205
Andrea Addis, Giuliano Armano,
Eloisa Vargiu and Andrea Manconi
Chapter 11 GRID Computing and Computational Immunology 223
Ferdinando Chiacchio and Francesco Pappalardo
Chapter 12 A Comparative Study of Machine Learning
and Evolutionary Computation Approaches
for Protein Secondary Structure Classification 239
César Manuel Vargas Benítez, Chidambaram Chidambaram,
Fernanda Hembecker and Heitor Silvério Lopes
Chapter 13 Functional Analysis of the Cervical Carcinoma Transcriptome:
Networks and New Genes Associated to Cancer 259
Mauricio Salcedo, Sergio Juarez-Mendez,
Vanessa Villegas-Ruiz, Hugo Arreola, Oscar Perez,
Guillermo Gómez, Edgar Roman-Bassaure,
Pablo Romero, Raúl Peralta
Chapter 14 Number Distribution of Transmembrane
Helices in Prokaryote Genomes 279
Ryusuke Sawada and Shigeki Mitaku
Chapter 15 Classifying TIM Barrel Protein Domain Structure
by an Alignment Approach
Using Best Hit Strategy and PSI-BLAST 287
Chia-Han Chu, Chun Yuan Lin,
Cheng-Wen Chang, Chihan Lee and Chuan Yi Tang
Chapter 16 Identification of Functional Diversity
in the Enolase Superfamily Proteins 311
Kaiser Jamil and M. Sabeena
Chapter 17 Contributions of Structure Comparison Methods
to the Protein Structure Prediction Field 329
David Piedra, Marco d'Abramo and Xavier de la Cruz
Chapter 18 Functional Analysis of Intergenic
Regions for Gene Discovery
345
Li M. Fu
Contents VII
Chapter 19 Prediction of Transcriptional Regulatory
Networks for Retinal Development 357
Ying Li, Haiyan Huang and Li Cai
Chapter 20 The Use of Functional Genomics in
Synthetic Promoter Design 375
Michael L. Roberts
Chapter 21 Analysis of Transcriptomic
and Proteomic Data in Immune-Mediated Diseases 397
Sergey Bruskin, Alex Ishkin, Yuri Nikolsky,
Tatiana Nikolskaya
and Eleonora Piruzian
Chapter 22 Emergence of the Diversified Short ORFeome
by Mass Spectrometry-Based Proteomics 417
Hiroko Ao-Kondo, Hiroko Kozuka-Hata and Masaaki Oyama
Chapter 23 Acrylamide Binding to Its Cellular Targets:
Insights from Computational Studies 431
Emmanuela Ferreira de Lima and Paolo Carloni
Preface
Nowadays it is difficult to imagine an area of knowledge that can continue developing
without the use of computers and informatics. It is not different with biology, that has
seen an unpredictable growth in recent decades, with the rise of a new discipline,
bioinformatics, bringing together molecular biology, biotechnology and information
technology. More recently, the development of high throughput techniques, such as
microarray, mass spectrometry and DNA sequencing, has increased the need of
computational support to collect, store, retrieve, analyze, and correlate huge data sets
of complex information. On the other hand, the growth of the computational power
for processing and storage has also increased the necessity for deeper knowledge in
the field. The development of bioinformatics has allowed now the emergence of
systems biology, the study of the interactions between the components of a biological
system, and how these interactions give rise to the function and behavior of a living
being.
Bioinformatics is a cross-disciplinary field and its birth in the sixties and seventies
depended on discoveries and developments in different fields, such as: the proposed
double helix model of DNA by Watson and Crick from X-ray data obtained by
Franklin and Wilkins in 1953; the development of a method to solve the phase problem
in protein crystallography by Perutz's group in 1954; the sequencing of the first protein
by Sanger in 1955; the creation of the ARPANET in 1969 at Stanford UCLA; the
publishing of the Needleman-Wunsch algorithm for sequence comparison in 1970; the
first recombinant DNA molecule created by Paul Berg and his group in 1972; the
announcement of the Brookhaven Protein DataBank in 1973; the establishment of the
Ethernet by Robert Metcalfe in the same year; the concept of computers network and
the development of the Transmission Control Protocol (TCP) by Vint Cerf and Robert
Khan in 1974, just to cite some of the landmarks that allowed the rise of bioinformatics.
Later, the Human Genome Project (HGP), started in 1990, was also very important for
pushing the development of bioinformatics and related methods of analysis of large
amount of data.
This book presents some theoretical issues, reviews, and a variety of bioinformatics
applications. For better understanding, the chapters were grouped in two parts. It was
not an easy task to select chapters for these parts, since most chapters provide a mix of
review and case study. From another point of view, all chapters also have extensive
X Preface
biological and computational information. Therefore, the book is divided into two
parts. In Part I, the chapters are more oriented towards literature review and
theoretical issues. Part II consists of application-oriented chapters that report case
studies in which a specific biological problem is treated with bioinformatics tools.
Molecular phylogeny analysis has become a routine technique not only to understand
the sequence-structure-function relationship of biomolecules but also to assist in their
classification. The first chapter of Part I, by Kolekar et al., presents the theoretical basis,
discusses the fundamental of phylogenetic analysis, and a particular view of steps and
methods used in the analysis.
Methods for protein function and gene expression are briefly reviewed in Hupert-
Kocurek and Kaguni’s chapter, and contrasted with the traditional approach of
mapping a gene via the phenotype of a mutation and deducing the function of the
gene product, based on its biochemical analysis in concert with physiological studies.
An example of experimental approach is provided that expands the current
understanding of the role of ATP binding and its hydrolysis by DnaC during the
initiation of DNA replication. This is contrasted with approaches that yield large sets
of data, providing a different perspective on understanding the functions of sets of
genes or proteins and how they act in a network of biochemical pathways of the cell.
Due to the importance of transcriptional regulation, one of the main goals in the post-
genomic era is to predict how the expression of a given gene is regulated based on the
presence of transcription factor binding sites in the adjacent genomic regions. Nain et
al. review different computational approaches for modeling and identification of
regulatory elements, as well as recent advances and the current challenges.
In Hwa et al., an approach is proposed to group proteins into putative functional
groups by designing a workflow with appropriate bioinformatics analysis tools, to
search for sequences with biological characteristics belonging to the selected protein
family. To illustrate the approach, the workflow was applied to LARGE-like protein
family.
Microarray technology has become one of the most important technologies for
unveiling gene expression profiles, thus fostering the development of new
bioinformatics methods and tools. In the chapter by Lowery et al. a thorough review of
microarray technology is provided, with special focus on MRNA and microRNA
profiling of breast cancer.
MicroRNAs are a class of small RNAs of approximately 22 nucleotides in length that
regulate eukaryotic gene expression at the post-transcriptional level. Santos and Soares
present several tools and computational pipelines for miRNA identification, discovery
and expression from sequencing data.
Currently, the mass spectroscopy-based methods represent very important and
flexible tools for studying the dynamic features of proteins and their complexes. Such