This book is concerned with recent advances in fitness landscapes. The concept of fitness landscapes originates from theoretical biology and refers to a framework for analysing and visualizing the relationships between genotypes, phenotypes and fitness. These relationships lay at the centre of attempts to mathematically describe evolutionary processes and evolutionary dynamics.

The book addresses recent advances in the understanding of fitness landscapes in evolutionary biology and evolutionary computation. In the volume, experts in the field of fitness landscapes present these findings in an integrated way to make it accessible to a number of audiences: senior undergraduate and graduate students in computer science, theoretical biology, physics, applied mathematics and engineering, but also researcher looking for a reference or/and entry point into using fitness landscapes for analysing algorithms. Also practitioners wanting to employ fitness landscape techniques for evaluating bio- and nature-inspired computing algorithms can find valuable material in the book. For teaching proposes, the book could also be used as a reference handbook.

This book presents an overview of a variety of contemporary statistical, mathematical and computer science techniques which are used to further the knowledge in the medical domain. The authors focus on applying data mining to the medical domain, including mining the sets of clinical data typically found in patient's medical records, image mining, medical mining, data mining and machine learning applied to generic genomic data and more. This work also introduces modeling behavior of cancer cells, multi-scale computational models and simulations of blood flow through vessels by using patient-specific models. The authors cover different imaging techniques used to generate patient-specific models. This is used in computational fluid dynamics software to analyze fluid flow. Case studies are provided at the end of each chapter. Professionals and researchers with quantitative backgrounds will find Computational Medicine in Data Mining and Modeling useful as a reference. Advanced-level students studying computer science, mathematics, statistics and biomedicine will also find this book valuable as a reference or secondary text book.

The first edition of "Geometric Morphometrics for Biologists" has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to biologists who approach the study of shape from a variety of perspectives, from clinical to evolutionary, because they incorporate the geometry of organisms throughout the data analysis. The second edition of this book retains the emphasis on accessible explanations, and the copious illustrations and examples of the first, updating the treatment of both theory and practice. The second edition represents the current state-of-the-art and adds new examples and summarizes recent literature, as well as provides an overview of new software and step-by-step guidance through details of carrying out the analyses.
Contains updated coverage of methods, especially for sampling complex curves and 3D forms and a new chapter on applications of geometric morphometrics to forensicsOffers a reorganization of chapters to streamline learning basic conceptsPresents detailed instructions for conducting analyses with freely available, easy to use software Provides numerous illustrations, including graphical presentations of important theoretical concepts and demonstrations of alternative approaches to presenting results

This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.

The application of methodological approaches and mathematical formalisms proper to Physics and Engineering to investigate and describe biological processes and design biological structures has led to the development of many disciplines in the context of computational biology and biotechnology. The best known applicative domain is tissue engineering and its branches. Recent domains of interest are in the field of biophysics, e.g.: multiscale mechanics of biological membranes and films and filaments; multiscale mechanics of adhesion; biomolecular motors and force generation.

Modern hypotheses, models, and tools are currently emerging and resulting from the convergence of the methods and phylosophycal apporaches of the different research areas and disciplines. All these emerging approaches share the purpose of disentangling the complexity of organisms, tissues, and cells and mimiking the function of living systems.

The contributions presented in this book are current research highlights of six challenging and representative applicative domains of phyisical, engineering, and computational approaches in medicine and biology, i.e tissue engineering, modelling of molecular structures, cell mechanics and cell adhesion processes, cancer physics, and physico-chemical processes of metabolic interactions. Each chapter presents a compendium or a review of the original results achieved by authors in the last years. Furthermore, the book also wants to pinpoint the questions that are still open and that could propel the future research.

The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015.

This volume reviews the current metabolic engineering tools and technologies from a practical point of view, and guides researchers as they overcome challenges at various stages of organism and bioprocess development. Microbes have been engineered to produce a variety of industrial products such as fuels, basic chemicals, fine chemicals, nutritional supplements, and pharmaceutical intermediates, and new tools such as gene synthesis, advanced cloning techniques, 'omics' analysis, and mathematical modeling have greatly accelerated the pace of innovation in the field. Written by leading experts in the field from both academia and industry, key topics include synthetic biology, pathway engineering, metabolic flux manipulation, adaptive evolution, and fermentation process scale-up. It is suitable for non-specialists, and is a valuable resource for anyone embarking on the exciting path to harnessing the metabolic potential of microorganisms.

While a sharp debate is emerging about whether conventional biometric technology offers society any significant advantages over other forms of identification, and whether it constitutes a threat to privacy, technology is rapidly progressing. Politicians and the public are still discussing fingerprinting and iris scan, while scientists and engineers are already testing futuristic solutions. Second generation biometrics - which include multimodal biometrics, behavioural biometrics, dynamic face recognition, EEG and ECG biometrics, remote iris recognition, and other, still more astonishing, applications - is a reality which promises to overturn any current ethical standard about human identification. Robots which recognise their masters, CCTV which detects intentions, voice responders which analyse emotions: these are only a few applications in progress to be developed.

This book is the first ever published on ethical, social and privacy implications of second generation biometrics. Authors include both distinguished scientists in the biometric field and prominent ethical, privacy and social scholars. This makes this book an invaluable tool for policy makers, technologists, social scientists, privacy authorities involved in biometric policy setting. Moreover it is a precious instrument to update scholars from different disciplines who are interested in biometrics and itswider social, ethical and political implications.

This is the first book to compare eight LDFs by different types of datasets, such as Fisher's iris data, medical data with collinearities, Swiss banknote data that is a linearly separable data (LSD), student pass/fail determination using student attributes, 18 pass/fail determinations using exam scores, Japanese automobile data, and six microarray datasets (the datasets) that are LSD. We developed the 100-fold cross-validation for the small sample method (Method 1) instead of the LOO method. We proposed a simple model selection procedure to choose the best model having minimum M2 and Revised IP-OLDF based on MNM criterion was found to be better than other M2s in the above datasets. We compared two statistical LDFs and six MP-based LDFs. Those were Fisher's LDF, logistic regression, three SVMs, Revised IP-OLDF, and another two OLDFs. Only a hard-margin SVM (H-SVM) and Revised IP-OLDF could discriminate LSD theoretically (Problem 2). We solved the defect of the generalized inverse matrices (Problem 3). For more than 10 years, many researchers have struggled to analyze the microarray dataset that is LSD (Problem 5). If we call the linearly separable model "Matroska," the dataset consists of numerous smaller Matroskas in it. We develop the Matroska feature selection method (Method 2). It finds the surprising structure of the dataset that is the disjoint union of several small Matroskas. Our theory and methods reveal new facts of gene analysis.

Due to the failing "one-drug-fits-all" model, it has become increasingly necessary to develop personalized medicine that treats whole systems and brings the right drug to the right patient with the right dosages. In Systems Biology in Drug Discovery and Development: Methods and Protocols, leading experts provide a practical, state-of-the-art, and holistic view of the translation of systems biology into better drug discovery and personalized medical practice. While the first part of the book describes cutting-edge technologies and methods in the field, the second part illustrates how the technologies can be applied in science for disease understanding and therapeutic discovery. As a volume in the highly successful Methods in Molecular Biology (TM) series, this collection provides the kind of detailed description and implementation advice that is crucial for getting optimal results. Authoritative and up-to-date, Systems Biology in Drug Discovery and Development: Methods and Protocols covers topics from fundamental concepts to advanced technologies in order to best serve biomedical students and professionals at all levels who are interested in vital integrative studies in molecular biology, genetics, bioinformatics, bioengineering, biochemistry, physiology, pathology, microbiology, immunology, pharmacology, toxicology, drug discovery, and clinical medicine.

Analysis and Control of Boolean Networks presents a systematic new approach to the investigation of Boolean control networks. The fundamental tool in this approach is a novel matrix product called the semi-tensor product (STP). Using the STP, a logical function can be expressed as a conventional discrete-time linear system. In the light of this linear expression, certain major issues concerning Boolean network topology - fixed points, cycles, transient times and basins of attractors - can be easily revealed by a set of formulae. This framework renders the state-space approach to dynamic control systems applicable to Boolean control networks. The bilinear-systemic representation of a Boolean control network makes it possible to investigate basic control problems including controllability, observability, stabilization, disturbance decoupling etc.

Biological and biomedical studies have entered a new era over the past two decades thanks to the wide use of mathematical models and computational approaches. A booming of computational biology, which sheerly was a theoretician's fantasy twenty years ago, has become a reality. Obsession with computational biology and theoretical approaches is evidenced in articles hailing the arrival of what are va- ously called quantitative biology, bioinformatics, theoretical biology, and systems biology. New technologies and data resources in genetics, such as the International HapMap project, enable large-scale studies, such as genome-wide association st- ies, which could potentially identify most common genetic variants as well as rare variants of the human DNA that may alter individual's susceptibility to disease and the response to medical treatment. Meanwhile the multi-electrode recording from behaving animals makes it feasible to control the animal mental activity, which could potentially lead to the development of useful brain-machine interfaces. - bracing the sheer volume of genetic, genomic, and other type of data, an essential approach is, ?rst of all, to avoid drowning the true signal in the data. It has been witnessed that theoretical approach to biology has emerged as a powerful and st- ulating research paradigm in biological studies, which in turn leads to a new - search paradigm in mathematics, physics, and computer science and moves forward with the interplays among experimental studies and outcomes, simulation studies, and theoretical investigations.

This manual offers a stand-alone reading companion, unique in simplifying the practical components of Bioinformatics in a unique and user-friendly manner. It covers the practical component of syllabi used at most leading universities and discusses the most extensively used tools and methodologies in Bioinformatics. Research in the biological sciences has made tremendous strides in recent years due in part to the increased automation in data generation. At the same time, storing, managing and interpreting huge volumes of data has become one of the most challenging tasks for scientists. These two aspects have ultimately necessitated the application of computers, giving rise to a highly interdisciplinary discipline-Bioinformatics. Despite the richness of bioinformatics resources and methods, the exposure of life sciences undergraduates and postgraduates to bioinformatics is extremely limited. Though the internet offers various tools for free, and provides guides for using them, it fails to help users interpret the processed data. Moreover, most sites fail to update their help pages to accommodate software upgrades. Though the market is flooded with books discussing the theoretical concepts in Bioinformatics, a manual of this kind is rarely found. The content developed to meet the needs of readers from diverse background and to incorporate the syllabi of undergraduate and postgraduate courses at various universities.

This unique textbook/reference presents unified coverage of bioinformatics topics relating to both biological sequences and biological networks, providing an in-depth analysis of cutting-edge distributed algorithms, as well as of relevant sequential algorithms. In addition to introducing the latest algorithms in this area, more than fifteen new distributed algorithms are also proposed. Topics and features: reviews a range of open challenges in biological sequences and networks; describes in detail both sequential and parallel/distributed algorithms for each problem; suggests approaches for distributed algorithms as possible extensions to sequential algorithms, when the distributed algorithms for the topic are scarce; proposes a number of new distributed algorithms in each chapter, to serve as potential starting points for further research; concludes each chapter with self-test exercises, a summary of the key points, a comparison of the algorithms described, and a literature review.

The book deals with various clinical aspects of cytochrome P450 2E1 (CYP2E1), which is a potent source for oxidative stress. Oxidative stress is critical for pathogenesis of diseases and CYP2E1 is a major contributor for oxidative stress. Several clinical disorders are associated with changes in regulation of CYP2E1 and the consequent abnormalities, which include alcoholic liver disease, alcoholic pancreatitis, carcinogenesis, non-alcoholic fatty liver disease, non-alcoholic steatohepatitis, obesity, hepatitis C virus infection, reproductive organ toxicity, hepatocellular and cholestatic liver cirrhosis, inhibition of bone repair, cross- tolerance in smokers and people treated with nicotine, disorders of the central nervous system, changes in metabolism of protoxicants in the circulatory system and susceptibility to human papillomavirus infection. Hence, CYP2E1 emerges as a new and potent player in aggravating injury and furthering disease complications.

The book is based on lectures presented on the International Summer School on Biophysics held in Croatia in September 2009. The advantage of the School is that it provides advanced training in very broad scope of areas related to biophysics contrary to other similar schools or workshops that are centered mainly on one topic or technique. In this volume, tenth in the row, the papers in the field of biophysics are presented. The topics are biological phenomena from single protein to macromolecular aggregations structure by using variant physical methods (NMR, EPR, FTIR, Mass Spectrometry, etc.). The interrelationship of supramolecular structures and their functions is enlightened by applications of principals of these physical methods in the biophysical and molecular biology context.

MATLAB(r) in bioscience and biotechnology presents an introductory Matlab course oriented towards various collaborative areas of biotechnology and bioscience. It concentrates on Matlab fundamentals and gives examples of its application to a wide range of current bioengineering problems in computational biology, molecular biology, bio-kinetics, biomedicine, bioinformatics, and biotechnology. In the last decade Matlab has been presented to students as the first computer program they learn. Consequently, many non-programmer students, engineers and scientists have come to regard it as user-friendly and highly convenient in solving their specific problems. Numerous books are available on programming in Matlab for engineers in general, irrespective of their specialization, or for those specializing in some specific area, but none have been designed especially for such a wide, interdisciplinary, and topical area as bioengineering. Thus, in this book, Matlab is presented with examples and applications to various school-level and advanced bioengineering problems - from growing populations of microorganisms and population dynamics, reaction kinetics and reagent concentrations, predator-prey models, mass-transfer and flow problems, to sequence analysis and sequence statistics.
This is the first book intended as a manual introducing biologists and other biotechnology engineers to work with MatlabIt is suitable for beginners and inexperienced users; however, applications of Matlab to advanced problems such as the Monte Carlo method, curve fitting, and reliable machine diagnostics make the book relevant to university teachers as wellThe book is different in that it assumes a modest mathematical background for the reader and introduces the mathematical or technical concepts with a somewhat traditional approach; Matlab is then used as a tool for subsequent computer solution

Focusing on new methods and techniques developed to address longstanding questions about the Golgi complex, this volume explores a diverse set of chapters, ranging from live and fixed cell imaging techniques to in vitro biochemical reconstitution systems. Each chapter provides a detailed set of specific instructions, which should enable anyone to successfully complete the assays. Written for the highly successful Methods in Molecular Biology series program, chapters include brief introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips from the experts on troubleshooting and avoiding known pitfalls. Practical and detailed, The Golgi Complex: Methods and Protocols will aid both new and established researchers in the field by providing strong hands-on instructions that can be directly applied to their research programs.

The current volume, "Medicinal and Aromatic Plants of the Middle-East" brings together chapters on selected, unique medicinal plants of this region, known to man since biblical times. Written by leading researchers and scientists, this volume covers both domesticated crops and wild plants with great potential for cultivation. Some of these plants are well-known medicinally, such as opium poppy and khat, while others such as apharsemon and citron have both ritual and medicinal uses. All have specific and valuable uses in modern society. As such, it is an important contribution to the growing field of medicinal and aromatic plants. This volume is intended to bring the latest research to the attention of the broad range of botanists, ethnopharmacists, biochemists, plant and animal physiologists and others who will benefit from the information gathered therein. Plants know no political boundaries, and bringing specific folklore to general medical awareness can only be for the benefit of all.

This book addresses in detail multifaceted approaches to boosting nutrient use efficiency (NUE) that are modified by plant interactions with environmental variables and combine physiological, microbial, biotechnological and agronomic aspects. Conveying an in-depth understanding of the topic will spark the development of new cultivars and strains to induce NUE, coupled with best management practices that will immensely benefit agricultural systems, safeguarding their soil, water, and air quality. Written by recognized experts in the field, the book is intended to provide students, scientists and policymakers with essential insights into holistic approaches to NUE, as well as an overview of some successful case studies. In the present understanding of agriculture, NUE represents a question of process optimization in response to the increasing fragility of our natural resources base and threats to food grain security across the globe. Further improving nutrient use efficiency is a prerequisite to reducing production costs, expanding crop acreage into non-competitive marginal lands with low nutrient resources, and preventing environmental contamination. The nutrients most commonly limiting plant growth are N, P, K, S and micronutrients like Fe, Zn, B and Mo. NUE depends on the ability to efficiently take up the nutrient from the soil, but also on transport, storage, mobilization, usage within the plant and the environment. A number of approaches can help us to understand NUE as a whole. One involves adopting best crop management practices that take into account root-induced rhizosphere processes, which play a pivotal role in controlling nutrient dynamics in the soil-plant-atmosphere continuum. New technologies, from basic tools like leaf color charts to sophisticated sensor-based systems and laser land leveling, can reduce the dependency on laboratory assistance and manual labor. Another approach concerns the development of crop plants through genetic manipulations that allow them to take up and assimilate nutrients more efficiently, as well as identifying processes of plant responses to nutrient deficiency stress and exploring natural genetic variation. Though only recently introduced, the ability of microbial inoculants to induce NUE is gaining in importance, as the loss, immobilization, release and availability of nutrients are mediated by soil microbial processes.

This book compiles and presents new developments in statistical causal inference. The accompanying data and computer programs are publicly available so readers may replicate the model development and data analysis presented in each chapter. In this way, methodology is taught so that readers may implement it directly. The book brings together experts engaged in causal inference research to present and discuss recent issues in causal inference methodological development. This is also a timely look at causal inference applied to scenarios that range from clinical trials to mediation and public health research more broadly. In an academic setting, this book will serve as a reference and guide to a course in causal inference at the graduate level (Master's or Doctorate). It is particularly relevant for students pursuing degrees in statistics, biostatistics, and computational biology. Researchers and data analysts in public health and biomedical research will also find this book to be an important reference.

The aim of this manual is to provide a comprehensive guide to the methods involved in collecting, preparing and screening plants for bioactive properties for manipulating key ruminal fermentation pathways and against gastrointestinal pathogens. The manual will better equip the reader with methodological approaches to initiate screening programmes to test for bioactivity in native plants and find natural alternatives to chemicals for manipulating ruminal fermentation and gut health. The manual provides isotopic and non-isotopic techniques to efficiently screen plants or plant parts for a range of potential bioactives for livestock production. Each chapter has been contributed by experts in the field and methods have been presented in a format that is easily reproducible in the laboratory. It is hoped that this manual will be of great value to students, researchers and those involved in developing efficient and environmentally friendly livestock production systems."

r ed Algae in Genome Age book most people reading this book have childhood memories about being enthralled at the beach with those rare and mysterious living forms we knew as seaweeds. We were fascinated at that time by their range of red hues and textures, and most of all, their exotic beauty. t o a scientist, red algae represent much more than apparent features. t heir complex forms have attracted morphologists for centuries; their intricate life cycles have brought more than one surprise to plant biologists familiar only with ferns and fowering plants; their unusual tastes have been appreciated for mill- nia, and their valuable chemical constituents have been exploited for nearly as long, most recently by biotech companies; their diversity in marine, freshwater, and t- restrial environments has offered centuries of engaging entertainment for botanists eager to arrange them in orderly classifcation systems; still, the red algae continue to teach us how many more challenges need to be overcome in order to understand their biodiversity, biological functions, and evolutionary histories.