Computer Aided Knowledge Discovery in Biomedicine

Computer Aided Knowledge Discovery in Biomedicine

Vanathi Gopalakrishnan (University of Pittsburgh, USA)
Copyright: © 2009 |Pages: 16
DOI: 10.4018/978-1-60566-076-9.ch007
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Abstract

This chapter provides a perspective on 3 important collaborative areas in systems biology research. These areas represent biological problems of clinical significance. The first area deals with macromolecular crystallization, which is a crucial step in protein structure determination. The second area deals with proteomic biomarker discovery from high-throughput mass spectral technologies; while the third area is protein structure prediction and complex fold recognition from sequence and prior knowledge of structure properties. For each area, successful case studies are revisited from the perspective of computer- aided knowledge discovery using machine learning and statistical methods. Information about protein sequence, structure, and function is slowly accumulating in standardized forms within databases. Methods are needed to maximize the use of this prior information for prediction and analysis purposes. This chapter provides insights into such methods by which available information in existing databases can be processed and combined with systems biology expertise to expedite biomedical discoveries.
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Background

Knowledge discovery in biomedicine in the current world is very often the result of computational analyses combined with interpretation by domain experts. Langley (1998) states that artificial intelligence researchers have tried to develop intelligent artifacts that replicate the act of discovery. There are distinct steps in the scientific discovery process discussed therein (Langley, 1998) during which developers or users can influence the behavior of a computational discovery system. Furthermore, Langley (1998) suggests that such intervention is the preferred approach for using discovery software. In this chapter, we present an approach to data modeling and discovery that is consistent with this viewpoint.

Jurisica and Wigle (2006) define knowledge discovery (KD) as the process of extracting novel, useful, understandable and usable information from large data sets. The authors review knowledge discovery in proteomics and present examples of such algorithms in the literature that aid protein crystallization. The case studies presented in this chapter reflect state-of-the-art challenges in proteomics along with computer-aided solutions. Quantitative and qualitative discoveries are described along with the methods by which they are arrived at. The KD process in complex real-world domains requires multi-disciplinary methods involving both artificial intelligence and statistics applied to databases (Jurisica & Wigle, 2006).

Proteomics can be defined simply as the study of protein composition in a protein complex, organelle, cell or entire organism (Russell, Old, Resing, & Hunter, 2004). Current high-throughput proteomic technologies require robotics and computational techniques to decipher signals within multitudes of data. It is becoming clear that the high dimensionality poses a serious challenge to existing artificial intelligence tools for knowledge discovery and reasoning (Jurisica & Wigle, 2006). The unavailability of large numbers of samples combined with the high dimensionality of the feature space limits the usefulness of models obtained from such data. Moreover, uncertain and missing values in the data combined with evolving knowledge of the underlying mechanisms requires an intelligent information system to be flexible and scalable (Jurisica & Wigle, 2006).

Key Terms in this Chapter

Clustering: The unsupervised grouping of data items in the absence of class labels.

Metabolomics: The study of small molecule metabolites and their expression within a system or organism.

Inductive Rule Learning: The development of IF-proposition-THEN-concept rule-based models from feature vectors, which are (attribute, value) pairs that describe the training examples. The rule-based models are expected to generalize to classify test examples accurately.

Supervised Machine Learning: The use of class labels as prior knowledge to learn discriminative models from training examples consisting of feature vectors descriptive of the target class.

Feature Extraction: The process of extracting and building features from raw data such as the amino acid sequence of a protein. Feature functions are utilized to extract and process informative features that are useful for prediction.

X-Ray Crystallography: The most general method for experimental determination of protein and other macromolecule three-dimensional structure. A good quality crystal is obtained first from a purified sample and then subjected to X-ray diffraction.

Conditional Random Fields (CRFs): These are undirected discriminative graphical models that directly compute the conditional likelihood of a hidden state sequence (y) given the observation sequence (x). This P(y|x) is proportional to the product of the potential functions over all the cliques in the graph. CRFs define the clique potential as an exponential function and guarantee finding of the global optimum since the optimization function is convex ( Lafferty et al., 2001 ). Forward and backward probability calculations are derived similar to HMMs. Unlike HMMs, no assumptions are made about independence of the observed features. The feature definition can also be arbitrary, including overlapping features and long-range interactions ( Liu et al., 2006 ).

Hidden Markov Models (HMMs): These are directed chain-structured probabilistic graphical models that are generative in nature. They assume that the data are generated by a particular model and compute the joint distribution, P(x, y) of the observation sequence x, and the hidden state sequence y.

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Table of Contents
Foreword
Ralf Herwig
Preface
Andriani Daskalaki
Acknowledgment
Andriani Daskalaki
Chapter 1
Peter Ghazal
An increasing number of biological experiments and more recently clinical based studies are being conducted using large-scale genomic, proteomic and... Sample PDF
Pathway Biology Approach to Medicine
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Chapter 2
Peter Wellstead, Sree Sreenath, Kwang-Hyun Cho
In this chapter the authors describe systems and control theory concepts for systems biology and the corresponding implications for medicine. The... Sample PDF
Systems and Control Theory for Medical Systems Biology
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Chapter 3
S. Nikolov
In this chapter we investigate how the inclusion of time delay alters the dynamic properties of (a) delayed protein cross talk model, (b) time delay... Sample PDF
Mathematical Description of Time Delays in Pathways Cross Talk
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Chapter 4
Elisabeth Maschke-Dutz
In this chapter basic mathematical methods for the deterministic kinetic modeling of biochemical systems are described. Mathematical analysis... Sample PDF
Deterministic Modeling in Medicine
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Chapter 5
Andrew Kuznetsov
Biologists have used a reductionist approach to investigate the essence of life. In the last years, scientific disciplines have merged with the aim... Sample PDF
Synthetic Biology as a Proof of Systems Biology
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Chapter 6
Tuan D. Pham
Computational models have been playing a significant role for the computer-based analysis of biological and biomedical data. Given the recent... Sample PDF
Computational Models for the Analysis of Modern Biological Data
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Chapter 7
Vanathi Gopalakrishnan
This chapter provides a perspective on 3 important collaborative areas in systems biology research. These areas represent biological problems of... Sample PDF
Computer Aided Knowledge Discovery in Biomedicine
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Chapter 8
Thomas Meinel
The function of proteins is a main subject of research in systems biology. Inference of function is now, more than ever, required by the upcoming of... Sample PDF
Function and Homology of Proteins Similar in Sequence: Phylogenetic Profiling
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Chapter 9
Nikolaos G. Sgourakis, Pantelis G. Bagos, Stavros J. Hamodrakas
GPCRs comprise a wide and diverse class of eukaryotic transmembrane proteins with well-established pharmacological significance. As a consequence of... Sample PDF
Computational Methods for the Prediction of GPCRs Coupling Selectivity
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Chapter 10
Pantelis G. Bagos, Stavros J. Hamodrakas
ß-barrel outer membrane proteins constitute the second and less well-studied class of transmembrane proteins. They are present exclusively in the... Sample PDF
Bacterial ß-Barrel Outer Membrane Proteins: A Common Structural Theme Implicated in a Wide Variety of Functional Roles
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Chapter 11
L.K. Flack
Clustering methods are used to place items in natural patterns or convenient groups. They can be used to place genes into clusters to have similar... Sample PDF
Clustering Methods for Gene-Expression Data
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Chapter 12
George Sakellaropoulos, Antonis Daskalakis, George Nikiforidis, Christos Argyropoulos
The presentation and interpretation of microarray-based genome-wide gene expression profiles as complex biological entities are considered to be... Sample PDF
Uncovering Fine Structure in Gene Expression Profile by Maximum Entropy Modeling of cDNA Microarray Images and Kernel Density Methods
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Chapter 13
Wasco Wruck
This chapter describes the application of the BeadArrayTM technology for gene expression profiling. It introduces the BeadArrayTM technology, shows... Sample PDF
Gene Expression Profiling with the BeadArrayTM Platform
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Chapter 14
Djork-Arné Clevert, Axel Rasche
Readers shall find a quick introduction with recommendations into the preprocessing of Affymetrix GeneChip® microarrays. In the rapidly growing... Sample PDF
The Affymetrix GeneChip® Microarray Platform
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Chapter 15
Jacek Majewski
Eukaryotic genes have the ability to produce several distinct products from a single genomic locus. Recent developments in microarray technology... Sample PDF
Alternative Isoform Detection Using Exon Arrays
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Chapter 16
Prerak Desai
The use of systems biology to study complex biological questions is gaining ground due to the ever-increasing amount of genetic tools and genome... Sample PDF
Gene Expression in Microbial Systems for Growth and Metabolism
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Chapter 17
Heike Stier
Alternative splicing is an important part of the regular process of gene expression. It controls time and tissue dependent expression of specific... Sample PDF
Alternative Splicing and Disease
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Chapter 18
Axel Kowald
Aging is a complex biological phenomenon that practically affects all multicellular eukaryotes. It is manifested by an ever increasing mortality... Sample PDF
Mathematical Modeling of the Aging Process
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Chapter 19
Evgenia Makrantonaki
This chapter introduces an in vitro model as a means of studying human hormonal aging. For this purpose, human sebaceous gland cells were maintained... Sample PDF
The Sebaceous Gland: A Model of Hormonal Aging
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Chapter 20
R. Seigneuric, N.A.W. van Riel, M.H.W. Starmans, A. van Erk
Complex diseases such as cancer have multiple origins and are therefore difficult to understand and cure. Highly parallel technologies such as DNA... Sample PDF
Systems Biology Applied to Cancer Research
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Chapter 21
Matej Orešic, Antonio Vidal-Puig
In this chapter the authors report on their experience with the analysis and modeling of data obtained from studies of animal models related to... Sample PDF
Systems Biology Strategies in Studies of Energy Homeostasis In Vivo
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Chapter 22
Axel Rasche
We acquired new computational and experimental prospects to seek insight and cure for millions of afflicted persons with an ancient malady. Type 2... Sample PDF
Approaching Type 2 Diabetes Mellitus by Systems Biology
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Chapter 23
Alia Benkahla, Lamia Guizani-Tabbane, Ines Abdeljaoued-Tej, Slimane Ben Miled, Koussay Dellagi
This chapter reports a variety of molecular biology informatics and mathematical methods that model the cell response to pathogens. The authors... Sample PDF
Systems Biology and Infectious Diseases
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Chapter 24
Daniela Albrecht, Reinhard Guthke
This chapter describes a holistic approach to understand the molecular biology and infection process of human-pathogenic fungi. It comprises the... Sample PDF
Systems Biology of Human-Pathogenic Fungi
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Chapter 25
Jessica Ahmed
Secretases are aspartic proteases, which specifically trim important, medically relevant targets such as the amyloid-precursor protein (APP) or the... Sample PDF
Development of Specific Gamma Secretase Inhibitors
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Chapter 26
Paul Wrede
Peptides fulfill many tasks in controlling and regulating cellular functions and are key molecules in systems biology. There is a great demand in... Sample PDF
In Machina Systems for the Rational De Novo Peptide Design
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Chapter 27
Ferda Mavituna, Raul Munoz-Hernandez, Ana Katerine de Carvalho Lima Lobato
This chapter summarizes the fundamentals of metabolic flux balancing as a computational tool of metabolic engineering and systems biology. It also... Sample PDF
Applications of Metabolic Flux Balancing in Medicine
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Chapter 28
Roberta Alfieri, Luciano Milanesi
This chapter aims to describe data integration and data mining techniques in the context of systems biology studies. It argues that the different... Sample PDF
Multi-Level Data Integration and Data Mining in Systems Biology
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Chapter 29
Hendrik Hache
In this chapter, different methods and applications for reverse engineering of gene regulatory networks that have been developed in recent years are... Sample PDF
Methods for Reverse Engineering of Gene Regulatory Networks
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Chapter 30
Alok Mishra
This chapter introduces the techniques that have been used to identify the genetic regulatory modules by integrating data from various sources. Data... Sample PDF
Data Integration for Regulatory Gene Module Discovery
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Chapter 31
Elizabeth Santiago-Cortés
Biological systems are composed of multiple interacting elements; in particular, genetic regulatory networks are formed by genes and their... Sample PDF
Discrete Networks as a Suitable Approach for the Analysis of Genetic Regulation
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Chapter 32
A. Maffezzoli
In this chapter, authors review main methods, approaches, and models for the analysis of neuronal network data. In particular, the analysis concerns... Sample PDF
Investigating the Collective Behavior of Neural Networks: A Review of Signal Processing Approaches
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Chapter 33
Paolo Vicini
This chapter describes the System for Population Kinetics (SPK), a novel Web service for performing population kinetic analysis. Population kinetic... Sample PDF
The System for Population Kinetics: Open Source Software for Population Analysis
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Chapter 34
Julia Adolphs
This chapter introduces the theory of optical spectra and excitation energy transfer of light harvesting complexes in photosynthesis. The light... Sample PDF
Photosynthesis: How Proteins Control Excitation Energy Transfer
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Chapter 35
Michael R. Hamblin
Photodynamic therapy (PDT) is a rapidly advancing treatment for multiple diseases. PDT involves the administration of a nontoxic drug or dye known... Sample PDF
Photodynamic Therapy: A Systems Biology Approach
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Chapter 36
Andriani Daskalaki
Photodynamic Therapy (PDT) involves administration of a photosensitizer (PS) either systemically or locally, followed by illumination of the lesion... Sample PDF
Modeling of Porphyrin Metabolism with PyBioS
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Chapter 37
Alexey R. Brazhe, Nadezda A. Brazhe, Alexey N. Pavlov, Georgy V. Maksimov
This chapter describes the application of interference microscopy and double-wavelet analysis to noninvasive study of cell structure and function.... Sample PDF
Interference Microscopy for Cellular Studies
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Chapter 38
Cathrin Dressler, Olaf Minet, Urszula Zabarylo, Jürgen Beuthan
This chapter deals with the mitochondrias’ stress response to heat, which is the central agent of thermotherapy. Thermotherapies function by... Sample PDF
Fluorescence Imaging of Mitochondrial Long-Term Depolarization in Cancer Cells Exposed to Heat-Stress
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Chapter 39
Athina Theodosiou, Charalampos Moschopoulos, Marc Baumann, Sophia Kossida
In previous years, scientists have begun understanding the significance of proteins and protein interactions. The direct connection of those with... Sample PDF
Protein Interactions and Diseases
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Chapter 40
Bernard de Bono
From a genetic perspective, disease can be interpreted in terms of a variation in molecular sequence or expression (dose) that impairs normal... Sample PDF
The Breadth and Depth of BioMedical Molecular Networks: The Reactome Perspective
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Chapter 41
Jorge Numata
Thermodynamics is one of the best established notions in science. Some recent work in biomolecular modeling has sacrificed its rigor in favor of... Sample PDF
Entropy and Thermodynamics in Biomolecular Simulation
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Chapter 42
Isabel Reinecke, Peter Deuflhard
In this chapter some model development concepts can be used for the mathematical modeling in physiology as well as a graph theoretical approach for... Sample PDF
Model Development and Decomposition in Physiology
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Chapter 43
Mohamed Derouich
Throughout the world, seasonal outbreaks of influenza affect millions of people, killing about 500,000 individuals every year. Human influenza... Sample PDF
A Pandemic Avian Influenza Mathematical Model
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Chapter 44
Mohamed Derouich
Dengue fever is a re-emergent disease affecting more than 100 countries. Its incidence rate has increased fourfold since 1970 with nearly half the... Sample PDF
Dengue Fever: A Mathematical Model with Immunization Program
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Chapter 45
Ross Foley
The field of histopathology has encountered a key transition point with the progressive move towards use of digital slides and automated image... Sample PDF
Automated Image Analysis Approaches in Histopathology
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About the Contributors