Algorithms in Computational Molecular Biology. Techniques, Approaches and Applications

A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. Surveys the development of techniques and approaches on pattern recognition in biomolecular data Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.

A breakthrough guide employing knowledge that unites cheminformatics and bioinformatics as innovation for the future Bridging the gap between cheminformatics and bioinformatics for the first time, Computational Approaches in Cheminformatics and Bioinformatics provides insight on how to blend these two sciences for progressive research benefits. It describes the development and evolution of these fields, how chemical information may be used for biological relations and vice versa, the implications of these new connections, and foreseeable developments in the future. Using algorithms and domains as workflow tools, this revolutionary text drives bioinformaticians to consider chemical structure, and similarly, encourages cheminformaticians to consider large biological systems such as protein targets and networks. Computational Approaches in Cheminformatics and Bioinformatics covers: Data sources available for modelling and prediction purposes Developments of conventional Quantitative Structure-Activity Relationships (QSAR) Computational tools for manipulating chemical and biological data Novel ways of probing the interactions between small molecules and proteins Also including insight from public (NIH), academic, and industrial sources (Novartis, Pfizer), this book offers expert knowledge to aid scientists through industry and academic study. The invaluable applications for drug discovery, cellular and molecular biology, enzymology, and metabolism make Computational Approaches in Cheminformatics and Bioinformatics the essential guidebook for evolving drug discovery research and alleviating the issue of chemical control and manipulation of various systems.

Understanding, identifying and influencing the biological systems are the primary objectives of chemical biology. From this perspective, metal complexes have always been of great assistance to chemical biologists, for example, in structural identification and purification of essential biomolecules, for visualizing cellular organelles or to inhibit specific enzymes. This inorganic side of chemical biology, which continues to receive considerable attention, is referred to as inorganic chemical biology. Inorganic Chemical Biology: Principles, Techniques and Applications provides a comprehensive overview of the current and emerging role of metal complexes in chemical biology. Throughout all of the chapters there is a strong emphasis on fundamental theoretical chemistry and experiments that have been carried out in living cells or organisms. Outlooks for the future applications of metal complexes in chemical biology are also discussed. Topics covered include: • Metal complexes as tools for structural biology • IMAC, AAS, XRF and MS as detection techniques for metals in chemical biology • Cell and organism imaging and probing DNA using metal and metal carbonyl complexes • Detection of metal ions, anions and small molecules using metal complexes • Photo-release of metal ions in living cells • Metal complexes as enzyme inhibitors and catalysts in living cells Written by a team of international experts, Inorganic Chemical Biology: Principles, Techniques and Applications is a must-have for bioinorganic, bioorganometallic and medicinal chemists as well as chemical biologists working in both academia and industry.

A guide to using molecular biology and immunological methods for the analysis of food Many of the analytical problems that food chemists face in the lab cannot be solved by chemistry alone, and so analytical chemists are turning to molecular biology and immunology for alternative approaches. Molecular Biological and Immunological Techniques and Applications for Food Chemists comprehensively explains the most important molecular biology and immunology methods, and illustrates their application in food analysis. Written by a distinguished group of experts, the coverage includes: Molecular Biological Methods—techniques explained, laboratory layout, PCR, real-time PCR, RFLP, SSCP, and sequencing Molecular Biology Applications—meat, genetically modified organisms (GMOs), food allergens, offal, and fish Immunological Methods—techniques explained and antibody-based detection methods Immunology Applications—animal speciation, international food allergen regulations (except Japanese), Japanese regulations and buckwheat allergen detection, egg allergen detection, soy allergen detection, milk allergen detection, gluten allergen detection, nut allergen detection, fish allergen detection, lupin allergen detection, mustard allergen detection, and celery allergen detection Clearly written and consistently edited to provide information to a wide range of readers, Molecular Biological and Immunological Techniques and Applications for Food Chemists offers an up-to-date reference for food scientists in government and industry, policymakers, and graduate-level students of food science, technology, and engineering. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Introduces readers to the state of the art of omics platforms and all aspects of omics approaches for clinical applications This book presents different high throughput omics platforms used to analyze tissue, plasma, and urine. The reader is introduced to state of the art analytical approaches (sample preparation and instrumentation) related to proteomics, peptidomics, transcriptomics, and metabolomics. In addition, the book highlights innovative approaches using bioinformatics, urine miRNAs, and MALDI tissue imaging in the context of clinical applications. Particular emphasis is put on integration of data generated from these different platforms in order to uncover the molecular landscape of diseases. The relevance of each approach to the clinical setting is explained and future applications for patient monitoring or treatment are discussed. Integration of omics Approaches and Systems Biology for Clinical Applications presents an overview of state of the art omics techniques. These methods are employed in order to obtain the comprehensive molecular profile of biological specimens. In addition, computational tools are used for organizing and integrating these multi-source data towards developing molecular models that reflect the pathophysiology of diseases. Investigation of chronic kidney disease (CKD) and bladder cancer are used as test cases. These represent multi-factorial, highly heterogeneous diseases, and are among the most significant health issues in developed countries with a rapidly aging population. The book presents novel insights on CKD and bladder cancer obtained by omics data integration as an example of the application of systems biology in the clinical setting. Describes a range of state of the art omics analytical platforms Covers all aspects of the systems biology approach—from sample preparation to data integration and bioinformatics analysis Contains specific examples of omics methods applied in the investigation of human diseases (Chronic Kidney Disease, Bladder Cancer) Integration of omics Approaches and Systems Biology for Clinical Applications will appeal to a wide spectrum of scientists including biologists, biotechnologists, biochemists, biophysicists, and bioinformaticians working on the different molecular platforms. It is also an excellent text for students interested in these fields.

When trying to find new methods and problem-solving strategies for their research, scientists often turn to nature for inspiration. An excellent example of this is the application of Darwin's Theory of Evolution, particularly the notion of the 'survival of the fittest', in computer programs designed to search for optimal solutions to many kinds of problems. These 'evolutionary algorithms' start from a population of possible solutions to a given problem and, by applying evolutionary principles, evolve successive generations with improved characteristics until an optimal, or near-optimal, solution is obtained. This book highlights the versatility of evolutionary algorithms in areas of relevance to molecular design with a particular focus on drug design. The authors, all of whom are experts in their field, discuss the application of these computational methods to a wide range of research problems including conformational analysis, chemometrics and quantitative structure-activity relationships, de novo molecular design, chemical structure handling, combinatorial library design, and the study of protein folding. In addition, the use of evolutionary algorithms in the determination of structures by X-ray crystallography and NMR spectroscopy is also covered. These state-of-the-art reviews, together with a discussion of new techniques and future developments in the field, make this book a truly valuable and highly up-to-date resource for anyone engaged in the application or development of computer-assisted methods in scientific research.

An invaluable tool in Bioinformatics, this unique volume provides both theoretical and experimental results, and describes basic principles of computational intelligence and pattern analysis while deepening the reader's understanding of the ways in which these principles can be used for analyzing biological data in an efficient manner. This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques, either individually or in a hybridized manner. The purpose is to analyze biological data and enable extraction of more meaningful information and insight from it. Biological data for analysis include sequence data, secondary and tertiary structure data, and microarray data. These data types are complex and advanced methods are required, including the use of domain-specific knowledge for reducing search space, dealing with uncertainty, partial truth and imprecision, efficient linear and/or sub-linear scalability, incremental approaches to knowledge discovery, and increased level and intelligence of interactivity with human experts and decision makers Chapters authored by leading researchers in CI in biology informatics. Covers highly relevant topics: rational drug design; analysis of microRNAs and their involvement in human diseases. Supplementary material included: program code and relevant data sets correspond to chapters.

Optics is a science which covers a very large domain and is experiencing indisputable growth. It has enabled the development of a considerable number of instruments, the optical component or methodology of which is often the essential part of portent systems. This book sets out show how optical physical phenomena such as lasers – the basis of instruments of measurement – are involved in the fields of biology and medicine. Optics in Instruments: Applications in Biology and Medicine details instruments and measurement systems using optical methods in the visible and near-infrared, as well as their applications in biology and medicine, through looking at confocal laser scanning microscopy, the basis of instruments performing in biological and medical analysis today, and flow cytometry, an instrument which measures at high speed the parameters of a cell passing in front of one or more laser beams. The authors also discuss optical coherence tomography (OCT), which is an optical imaging technique using non-contact infrared light, the therapeutic applications of lasers, where they are used for analysis and care, and the major contributions of plasmon propagation in the field of life sciences through instrumental developments, focusing on propagating surface plasmons (PSP) and localized plasmons (LP). Contents: 1. Confocal Laser Scanning Microscopy, Thomas Olivier and Baptiste Moine. 2. Flow Cytometry (FCM) Measurement of Cells in Suspension, Odile Sabido. 3. Optical Coherence Tomography, Claude Boccara and Arnaud Dubois. 4. Therapeutic Applications of Lasers, Genevi?ve Bourg-Heckly and Serge Mordon. 5. Plasmonics, Emmanuel Fort. About the Authors Jean-Pierre Goure is Emeritus Professor of optics at Jean Monnet University in Saint-Etienne, France, and was previously director of the UMR 5516 laboratory linked with CNRS. He is the author of more than 100 publications in various fields, such as spectroscopy, instrumentation, sensors, optical fiber and optical communications. He was also previously deputy director in engineering science at CNRS and a member of several scientific associations such as the French Optical Society and the European Optical Society.

Optics is a science which covers a very large domain and is experiencing indisputable growth. It has enabled the development of a considerable number of instruments, the optical component or methodology of which is often the essential part of portent systems. This book sets out show how optical physical phenomena such as lasers – the basis of instruments of measurement – are involved in the fields of biology and medicine. Optics in Instruments: Applications in Biology and Medicine details instruments and measurement systems using optical methods in the visible and near-infrared, as well as their applications in biology and medicine, through looking at confocal laser scanning microscopy, the basis of instruments performing in biological and medical analysis today, and flow cytometry, an instrument which measures at high speed the parameters of a cell passing in front of one or more laser beams. The authors also discuss optical coherence tomography (OCT), which is an optical imaging technique using non-contact infrared light, the therapeutic applications of lasers, where they are used for analysis and care, and the major contributions of plasmon propagation in the field of life sciences through instrumental developments, focusing on propagating surface plasmons (PSP) and localized plasmons (LP). Contents: 1. Confocal Laser Scanning Microscopy, Thomas Olivier and Baptiste Moine. 2. Flow Cytometry (FCM) Measurement of Cells in Suspension, Odile Sabido. 3. Optical Coherence Tomography, Claude Boccara and Arnaud Dubois. 4. Therapeutic Applications of Lasers, Genevi?ve Bourg-Heckly and Serge Mordon. 5. Plasmonics, Emmanuel Fort. About the Authors Jean-Pierre Goure is Emeritus Professor of optics at Jean Monnet University in Saint-Etienne, France, and was previously director of the UMR 5516 laboratory linked with CNRS. He is the author of more than 100 publications in various fields, such as spectroscopy, instrumentation, sensors, optical fiber and optical communications. He was also previously deputy director in engineering science at CNRS and a member of several scientific associations such as the French Optical Society and the European Optical Society.

Machine Learning Algorithms  is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and deep learning techniques, with each chapter dealing with a novel approach of machine learning architecture for a specific application, and then compares the results with previous algorithms. The book discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, sentiment analysis, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the user can easily move from the equations in the book to a computer program.