Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications

Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications

Limin Angela Liu (Shanghai Jiao Tong University, China), Dongqing Wei (Shanghai Jiao Tong University, China), Yixue Li (Shanghai Jiao Tong University, China) and Huimin Lei (Shanghai Jiao Tong University, China)
Indexed In: SCOPUS View 1 More Indices
Release Date: March, 2011|Copyright: © 2011 |Pages: 776
ISBN13: 9781609604912|ISBN10: 1609604911|EISBN13: 9781609604929|DOI: 10.4018/978-1-60960-491-2

Description

The biological sciences have been among the most exciting and intensely pursued fields of science for the past several decades. The advancement of high-throughput technologies that generate large scale biological data as well as the development of related computational tools has enabled global efforts at understanding complex biological systems and brought revolutionary changes to biological research.

Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications summarizes some of the most recent research carried out in computational biology and systems biology to encourage and guide future study. Submissions to this comprehensive text present methods, tools, and applications developed and considered by many leading experts around the globe.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Biclustering of DNA microarray data
  • Detecting epistasis in genome-wide association studies
  • DNA microarray data
  • Genomic DNA sequence
  • Granger causality
  • Predictive and personalized medicine
  • Privacy considerations for systems biology applications
  • Vaccine development
  • Virtual screening
  • Visualization of protein 3d structures

Reviews and Testimonials

This book, with its well-done illustrations and contributions from leading experts, will be of immense help for novices and researchers interested in this field.

– Omer Iqbal, MD, FACC, FESC, Loyola University Medical Center. Doody's Book Review 2011.

Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications has been developed to summarize and present some of the most recent research carried out in these fields to encourage and guide future research. During the book development process, several hundred world-leading scientists and researchers in computational biology and systems biology were invited to contribute a chapter to the book. Each submitted manuscript was reviewed by at least three reviewers in a double-blind review process. The reviewers may be Editorial Advisory Board members, contributing authors, or external reviewers. From the forty-three submissions, twenty-eight were accepted to appear in the book. The final book is a collection of eighteen thorough reviews and ten original research articles on the state-of-the-art development in the fields of computational biology and systems biology. Methods, tools, and applications of these fields are presented by many leading experts around the globe. The book chapters are written with the objective that novices in these fields will be able to learn the concepts and apply the techniques in their own studies and research. Active researchers in these fields may also appreciate the timely and in-depth review of existing literature and may be inspired to carry out innovative work to move biological sciences forward.

– Limin Angela Liu, Shanghai Jiao Tong University, China; Dongqing Wei, Shanghai Jiao Tong University, China; and Yixue Li, Shanghai Jiao Tong University, China

Table of Contents and List of Contributors

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Preface

The biological sciences have been among the most exciting and intensely pursued fields of science for the past several decades. The advancement of high-throughput technologies that generate large scale biological data, as well as the development of related computational tools, has enabled global efforts at understanding complex biological systems and brought revolutionary changes to biological research. Increasingly, biologists work with scientists and engineers from a broad spectrum of disciplines to unravel how complex biological systems work. Biological phenomena are often studied quantitatively and on the scale of the whole organism. Such types of interdisciplinary research, broadly defined as computational biology and systems biology, are helping the transformation of biological science from a more descriptive and qualitative field to a more quantitative and precise science.

Here, we define computational biology broadly as an interdisciplinary field that applies computational methods developed in mathematics, statistics, computer science, etc., to the modeling and analysis of biological data. Structural modeling of biological molecules, sequence analysis and functional annotation, mathematical modeling of biological systems, et cetera, are a few examples of research work in this field. Computational biology has been instrumental in the interpretation of experimental findings and the elucidation of the mechanisms of many biological phenomena. In addition, it can provide predictions that help define research directions for both experimentalists and theoreticians.

We define systems biology as an interdisciplinary field that studies biological systems by examining the interactions of all relevant components of the living organisms simultaneously. A living organism is a complex and intricate system consisting of many inter-related components, such as nucleic acids, proteins, metabolites, and so on. The function of the living organism is realized by the proper interactions and organizations among these components and between these components and the environment. The success of systems biology relies on advances in both experimental technologies and computational models and tools. The former would include novel high-throughput experiments that allow all of the necessary molecular entities to be examined. The latter would include analytical tools for data interpretation and mathematical modeling that may encapsulate the biological system and allow explanations and predictions of biological behaviors.

One ultimate goal of computational biology and systems biology is to find cures for complex diseases such as cancer and to enable personalized medical diagnosis and treatment taking into account each individual’s genetic makeup, metabolic level, and drug disposition. Despite rapid progress that we have made in biological and medical sciences, our understanding of biological systems remains limited, and we are still far from achieving this goal. Therefore, continued improvement in technology, theory, and computing tools in these interdisciplinary fields is much needed.

Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications” has been developed to summarize and present some of the most recent research carried out in these fields to encourage and guide future research. During the book development process, several hundred world-leading scientists and researchers in computational biology and systems biology were invited to contribute a chapter to the book. Each submitted manuscript was reviewed by at least three reviewers in a double-blind review process. The reviewers may be Editorial Advisory Board members, contributing authors, or external reviewers. From the forty-three submissions, twenty-eight were accepted to appear in the book.

The final book is a collection of eighteen thorough reviews and ten original research articles on the state-of-the-art development in the fields of computational biology and systems biology. Methods, tools, and applications of these fields are presented by many leading experts around the globe. The book chapters are written with the objective that novices in these fields will be able to learn the concepts and apply the techniques in their own studies and research. Active researchers in these fields may also appreciate the timely and in-depth review of existing literature and may be inspired to carry out innovative work to move biological sciences forward.

ORGANIZATION OF THE BOOK

A broad range of topics in systems biology and computational biology is covered by the book. The twenty-eight chapters of the book are divided into four sections:


  • Drug Development and Medicine (4 Chapters)
  • Method Development in Bioinformatics (5 Chapters)
  • Biological Networks and Pathways (14 Chapters)
  • Structural and Mathematical Modeling (5 chapters)

Section 1: Drug Development and Medicine contains four chapters summarizing the efforts and the challenges related to a wide range of research in drug discovery and medicine.

Chapter 1 provides a review and discussion of the ethical and privacy issues related to predictive and personalized medicine in the post-genomic era, as increasing amount of personal medical data are now stored electronically and accessed over the Internet.

Chapter 2 presents a thorough review of prevalent computational methods used for virtual screening in drug discovery, such as docking, QSAR, pharmacophore model, et cetera. The authors also offer their expert opinions on the advantages and limitations of each method and indicate important future research directions.

Chapter 3 reviews the recent efforts in vaccine development using systems biology approaches. Many successful vaccine development examples are presented. Various resources for epitope predictions and immunoinformatics research are summarized. New directions for vaccine research, such as through synthetic whole organism vaccines, are discussed.

Chapter 4 comprehensively reviews recent method development and applications in biomarker discovery in genomics, proteomics, transcriptomics, and metabolomics. The advantages and limitations of existing computational and experimental techniques are discussed.

Section 2: Method Development in Bioinformatics
contains five chapters that review the most recent advances in method development in sequence and high-throughput data analysis.

Chapter 5 reviews the genome-wide association studies of human single nucleotide polymorphisms with their quantitative complex diseases and traits.

Chapter 6 reviews several computational methods in genome-wide association studies and presents a novel approach to detecting epistatic interactions by employing expert knowledge, such as pathway and protein-protein interaction information.

Chapter 7 reviews in depth the theory, strengths and limitations of existing biclustering methods for the analysis of DNA microarray data. Several important applications to drug discovery and various problems in systems biology are also summarized.

Chapter 8 reviews computational methods for the prediction of epigenetic target sites from DNA sequences based on nucleosome positioning, histone modification, and DNA methylation.

Chapter 9 presents an original research paper describing a novel method for protein sequence analysis. Evolutionary, structural, and functional information are taken into consideration to improve protein structure and function prediction. Application to the prestin protein is discussed.

Section 3: Biological Networks and Pathways contains fourteen chapters, including four method reviews providing introductory material for this field, five specialized reviews, and five original research articles that focus on specific types of biological problems.

Chapter 10 reviews the basic concepts of biological pathways and networks in detail, as well as available databases and tools for their storage and analysis. Integration of knowledge and data is presented with several applications to target discovery and disease pathway analysis.

Chapter 11 thoroughly reviews existing computational methods to identify modules in biological networks. Their applications in a variety of important biological problems, such as protein function and interaction predictions and disease studies, are also discussed in detail.

Chapter 12 reviews methods for constructing a functional linkage network (FLN) that consists of genes that are functionally associated. Two important applications to disease study, including prediction of disease gene and disease-disease association, are discussed.

Chapter 13 reviews network-driven analysis methods with a special focus on drug target identification.

Chapter 14 reviews an important and helpful pathway analysis tool, the Rat Genome Database (RGD). The novel pathway ontology for gene annotation adopted by RGD is explained and examples of pathway visualization and analysis are demonstrated using their Web service.

Chapter 15 reviews several novel methods that model cellular signaling networks, where signaling network perturbation data are analyzed by integrating multivariate measurement data to gain much needed information and knowledge about these networks.

Chapter 16 reviews recent advances in the experimental and computational analysis of MAPK (mitogen-activated protein kinase) cascades, providing original insights to these important signal transduction networks.

Chapter 17 reviews computational methods for the classification of cancer subtypes and the identification of deregulated pathways in different cancer subtypes.

Chapter 18 reviews novel computational methods based on structures and sequences of biosynthesis enzymes in the modeling of secondary metabolite biosynthetic pathways.

Chapter 19 presents an original research paper describing the analysis and prediction of metastatic relapse in breast cancer by sub-network extraction. A novel interactome-transcriptome integration method for extracting sub-networks is presented by integrating protein-protein interaction and gene expression data.

Chapter 20 presents an original research article describing a novel analysis method of time-course microarray data to predict transcription factors that temporally regulate differentially expressed genes under diverse stimuli.

Chapter 21 presents an original research article on the dynamic modeling and parameter optimization of the DNA damage and repair network.

Chapter 22 presents an original research paper in which a novel model for building causal biological networks based on high-throughput data is described. The model is built by unifying two complimentary methods (Granger Causality Model and Dynamic Causal Model). An application to the analysis of microarray data for gene circuit construction is presented.

Chapter 23 presents an original research paper that describes the development of microfluidic cell arrays for high-throughput examination of host-pathogen interactions. A prototype is presented that enables the study of the infection of human cells by up to 16 different bacterial strains.

Section 4: Structural and Mathematical Modeling contains five chapters, including three chapters on the structural modeling of biological molecules and two chapters on the mathematical modeling of specific biological phenomena.

Chapter 24 reviews state-of-the-art methods for non-coding RNA identification based on structural alignment of RNAs and with full consideration of pseudoknots.

Chapter 25 presents an original research paper on the computational modeling of RNA folding based on both folding kinetics and energetic considerations.

Chapter 26 presents an original research paper demonstrating a novel method for a reduced representation of protein structure in the application of ligand binding site modeling and screening.

Chapter 27 presents an original research paper on modeling the rolling of a cell on the surface of the extracellular matrix by simulating the successive attachment and detachment processes.

Chapter 28 presents an original research paper describing the modeling of chemotactic axon guidance, an important neurological process, at both microscopic and macroscopic scales.

These twenty-eight chapters represent only a small portion of the research work conducted in computational biology and systems biology. Nonetheless, we hope the readers may get a sense regarding the status of these fields from reading these chapters and become interested in carrying out additional research work to expand our understanding of biology.

August, 2010

Limin Angela Liu
Shanghai Jiao Tong University, Shanghai, China
Dong-Qing Wei
Shanghai Jiao Tong University, Shanghai, China
Yixue Li
Shanghai Jiao Tong University, Shanghai, China
Huimin Lei
Shanghai Jiao Tong University, Shanghai, China

Author(s)/Editor(s) Biography

Limin Angela Liu, PhD, obtained her BSc degree from Tsinghua University, Beijing and her PhD degree from Carnegie Mellon University, USA. After postdoctoral research at Johns Hopkins University, USA, she became Associate Professor at Shanghai Jiao Tong University. Her recent work includes the establishment of an ab initio method for the prediction of transcription factor binding sites and a novel “tethered-hopping model” for describing the effects of protein-protein interactions on the formation and stability of ternary protein-DNA complexes.
Dongqing Wei, PhD, is the acting head of the Department of Bioinformatics and Biostatistics, College of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, China, the editor-in-Chief of the journal “Interdisciplinary Sciences - Computational Life Sciences”, and the chairman of the International Association of Scientists in the Interdisciplinary Areas (IASIA). Prof. Wei’s research is in the general area of structural bioinformatics. He is best known for his ground-breaking work on theory of complicated liquids. He, along with Prof. Gren Patey, has found that strongly interacting dipolar spheres can form a ferroelectric nematic phase. This was the first demonstration that dipolar forces alone can create an orientationally ordered liquid state. It is also the first time that the existence of a ferroelectric nematic phase has been established for a model liquid. This discovery solved a long standing problem in theoretical physics, and created a new direction in search for new liquid crystal materials (Phys. Rev. Lett. 68, 2043, 1992, cited about 180 times). In recent years, Prof. Wei has developed tools of molecular simulation and applied them to study biological systems with relevance to computer-aided drug design and structural biology. With more than 150 journal papers and greater than 2000 citations (Science Citation Index), he is becoming a leading figure in the area of structural bioinformatics.
Yixue Li, PhD, was born in Xinjiang, China. Currently, he is the director in Shanghai Center for Bioinformation Technology, vice director and a full research professor of Key Laboratory of Systems Biology at Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. Dr. Li received his BSc. and Msc. degrees in theoretical physics from Xinjiang University, China, in 1982 and 1987, respectively, and his Ph.D. degree in theoretical physics from the University of Heidelberg, Germany, in 1996. After Dr. Li got his Ph.D. degree he worked as a bioinformatics research staff in European Molecular Biology Laboratory (EMBL) from 1997-2000, and came back to Shanghai, China in the middle of 2000. Dr.Li's research interests include bioinformatics, systems biology and computational biology. Dr. Li has published more than 100 journal papers in various international scientific journals, such as Science, Nature Genetics, Nature Biotechnology, PNAS, Bioinformatics, NAR, Plos Computational Biology, Plos One, Molecular Systems Biology, Molecular Cellular Proteomics, Oncogene, BMC Bioinformatics, Genome Biology, etc., and his research results have been cited by more than 1500 researchers worldwide in books, theses, journal and conference papers. Dr. Li has served as an editorial board member for 5 scientific journals.
Huimin Lei, MD, obtained her degree from Inner Mongolia University of Science and Technology, China in 2004. She then became a lecturer and academic advisor for medical students at Baotou Health School,China. Since 2008, she became an Assistant Editor for the journal “Interdisciplinary Sciences – Computational Life Sciences” and an office administrator of Prof. Dongqing Wei’s lab at Shanghai Jiao Tong University. She has served on the organizing committees of several international conferences, including “Theory and Applications of Computational Chemistry – 2008” (TACC2008) and the annual “International Conference on Computational and Systems Biology” (ICCSB) meeting series.

Indices

Editorial Board

  • Tatsuya Akutsu, Kyoto University, Japan
  • Joel Bader, Johns Hopkins University, USA
  • Paola Causin, Universita' degli Studi di Milano, Italy
  • Kun-Mao Chao, National Taiwan University, Taiwan
  • Flávio Codeço Coelho, Gulbenkian Institute of Science, Portugal
  • Pietro Cortona, Propriété et Modélisation des Solides, France
  • Yongsheng Ding, Donghua University, China
  • Todor Dudev, Academia Sinica, Taiwan
  • Andreas Fuerholz, Nestlé Research Center, Switzerland
  • Dietlind Gerloff, University of California, Santa Cruz, USA
  • Haijun Gong, Carnegie Mellon University, USA
  • James A. Holzwarth, Nestlé Research Center, Switzerland
  • Timo Jacob, Universität Ulm, Germany
  • Igor Jurisica, University of Toronto, Canada
  • Yiannis N. Kaznessis, University of Minnesota, USA
  • Samee Ullah Khan, North Dakota State University, USA
  • Jens Lagergren, Stockholm Bioinformatics Center, Sweden
  • Qi Liu, Shanghai Jiao Tong University, China
  • Thomas Manke, Max Planck Institute for Molecular Genetics, Germany
  • Jason McDermott, Pacific Northwest National Laboratory, USA
  • Satoru Miyano, University of Tokyo, Japan
  • Kiran Mukhyala, Genentech, Inc., USA
  • Madhusudan Natarajan, Pfizer Research Technology Center, USA
  • Victoria Petri, Medical College of Wisconsin, USA
  • Piotr Piecuch, Michigan State University, USA
  • Jean-Philip Piquemal, Université Pierre et Marie Curie, France
  • George V. Popescu, University Politehnica of Bucharest, Romania
  • Zimei Rong, Queen Mary University of London, UK
  • Dennis R. Salahub, University of Calgary, Canada
  • Reinhard Schneider, EMBL, Germany
  • Alexander Schoenhuth, University of California at Berkeley, USA
  • Ora Schueler-Furman, Hebrew University, Israel
  • Russell Schwartz, Carnegie Mellon University, USA
  • Temple F. Smith, Boston University, USA
  • Fengzhu Sun, University of Southern California, USA
  • Jerzy Tiuryn, University of Warsaw, Poland
  • Jack Tuszynski, University of Alberta, Canada
  • Esko Ukkonen, University of Helsinki, Finland
  • Lusheng Wang, City University of Hong Kong, Hong Kong
  • Zhuo Wang, Shanghai Jiao Tong University, China
  • Limsoon Wong, National University of Singapore, Singapore
  • Yu (Brandon) Xia, Boston University, USA
  • Zhaolei Zhang, University of Toronto, Canada
  • Deyou Zheng, Albert Einstein College of Medicine of Yeshiva University, USA
  • Xianghong Jasmine Zhou, University of Southern California, USA