With an emphasis on applications of computational models for solving modern challenging problems in biomedical and life sciences, this book aims to bring collections of articles from biologists, medical/biomedical and health science researchers together with computational scientists to focus on problems at the frontier of biomedical and life sciences. The goals of this book are to build interactions of scientists across several disciplines and to help industrial users apply advanced computational techniques for solving practical biomedical and life science problems. This book is for users in the fields of biomedical and life sciences who wish to keep abreast with the latest techniques in signal and image analysis. The book presents a detailed description to each of the applications. It can be used by those both at graduate and specialist levels.

These papers on Intelligent Data Analysis and Management (IDAM) examine issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of disciplines. The papers derive from the 2013 IDAM conference in Kaohsiung ,Taiwan. It is an interdisciplinary research field involving academic researchers in information technologies, computer science, public policy, bioinformatics, medical informatics, and social and behavior studies, etc. The techniques studied include (but are not limited to): data visualization, data pre-processing, data engineering, database mining techniques, tools and applications, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and post-processing, etc.

This book presents an overview of the RNA networks controlling gene expression in fungi highlighting the remaining questions and future challenges in this area.

It covers several aspects of the RNA-mediated mechanisms that regulate gene expression in model yeasts and filamentous fungi, organisms of great importance for industry, medicine and agriculture. It is estimated that there are more than one million fungal species on the Earth. Despite their diversity (saprophytic, parasitic and mutualistic), fungi share common features distinctive from plants and animals and have been grouped taxonomically as an independent eukaryotic kingdom. In this book, 15 chapters written by experts in their fields cover the RNA-dependent processes that take place in a fungal cell ranging from formation of coding and non-coding RNAs to mRNA translation, ribosomal RNA biogenesis, gene silencing, RNA editing and epigenetic regulation.

The papers in this volume represent a broad, applied swath of advanced contributions to the 2015 ICSA/Graybill Applied Statistics Symposium of the International Chinese Statistical Association, held at Colorado State University in Fort Collins. The contributions cover topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. Each papers was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe.

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.

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 volume details several important databases and data mining tools. Data Mining Techniques for the Life Sciences, Second Edition guides readers through archives of macromolecular three-dimensional structures, databases of protein-protein interactions, thermodynamics information on protein and mutant stability, "Kbdock" protein domain structure database, PDB_REDO databank, erroneous sequences, substitution matrices, tools to align RNA sequences, interesting procedures for kinase family/subfamily classifications, new tools to predict protein crystallizability, metabolomics data, drug-target interaction predictions, and a recipe for protein-sequence-based function prediction and its implementation in the latest version of the ANNOTATOR software suite. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Data Mining Techniques for the Life Sciences, Second Edition aims to ensure successful results in the further study of this vital field.

This book contributes to better understand how lifestyle modulations can effectively halt the emergence and progression of human diseases. The book will allow the reader to gain a better understanding of the mechanisms by which the environment interferes with the bio-molecular regulatory processes underlying the emergence and progression of complex diseases, such as cancer. Focusing on key and early cellular bio-molecular events giving rise to the emergence of degenerative chronic disease, it builds on previous experience on the development of multi-cellular organisms, to propose a mathematical and computer based framework that allows the reader to analyze the complex interplay between bio-molecular processes and the (micro)-environment from an integrative, mechanistic, quantitative and dynamical perspective. Taking the wealth of empirical evidence that exists it will show how to build and analyze models of core regulatory networks involved in the emergence and progression of chronic degenerative diseases, using a bottom-up approach.

Microbial relationships with all life forms can be as free living, symbiotic or pathogenic. Human beings harbor 10 times more microbial cells than their own. Bacteria are found on the skin surface, in the gut and other body parts. Bacteria causing diseases are the most worrisome. Most of the infectious diseases are caused by bacterial pathogens with an ability to form biofilm. Bacteria within the biofilm are up to 1000 times more resistant to antibiotics. This has taken a more serious turn with the evolution of multiple drug resistant bacteria. Health Departments are making efforts to reduce high mortality and morbidity in man caused by them. Bacterial Quorum sensing (QS), a cell density dependent phenomenon is responsible for a wide range of expressions such as pathogenesis, biofilm formation, competence, sporulation, nitrogen fixation, etc. Majority of these organisms that are important for medical, agriculture, aquaculture, water treatment and remediation, archaeological departments are: Aeromonas, Acinetobacter, Bacillus, Clostridia, Enterococcus, Pseudomonas, Vibrio and Yersinia spp. Biosensors and models have been developed to detect QS systems. Strategies for inhibiting QS system through natural and synthetic compounds have been presented here. The biotechnological applications of QS inhibitors (QSIs) in diverse areas have also been dealt with. Although QSIs do not affect growth and are less likely to impose selective pressure on bacteria, however, a few reports have raised doubts on the fate of QSIs. This book addresses a few questions. Will bacteria develop mechanisms to evade QSIs? Are we watching yet another defeat at the hands of bacteria? Or will we be acting intelligently and survive the onslaughts of this Never Ending battle?

This book provides a framework for computational researchers studying the basics of cancer through comparative analyses of omic data. It discusses how key cancer pathways can be analyzed and discovered to derive new insights into the disease and identifies diagnostic and prognostic markers for cancer. Chapters explain the basic cancer biology and how cancer develops, including the many potential survival routes. The examination of gene-expression patterns uncovers commonalities across multiple cancers and specific characteristics of individual cancer types. The authors also treat cancer as an evolving complex system, explore future case studies, and summarize the essential online data sources. Cancer Bioinformatics is designed for practitioners and researchers working in cancer research and bioinformatics. It is also suitable as a secondary textbook for advanced-level students studying computer science, biostatistics or biomedicine.

The work described in this book is an excellent example of interdisciplinary research in systems biology. It shows how concepts and approaches from the field of physics can be efficiently used to answer biological questions and reports on a novel methodology involving creative computer-based analyses of high-throughput biological data. Many of the findings described in the book, which are the result of collaborations between the author (a theoretical scientist) and experimental biologists and between different laboratories, have been published in high-quality peer-reviewed journals such as Molecular Cell and Nature. However, while those publications address different aspects of post-transcriptional gene regulation, this book provides readers with a complete, coherent and logical view of the research project as a whole. The introduction presents post-transcriptional gene regulation from a distinct angle, highlighting aspects of information theory and evolution and laying the groundwork for the questions addressed in the subsequent chapters, which concern the regulation of the transcriptome as the primary functional carrier of active genetic information.

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.

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.

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.

This book provides a multifaceted look into the world of stem cells and explains the similarities and differences between plant and human stem cells. It explores the intersection between animals and plants and explains their cooperative role in bioengineering studies. The book treats both theoretical and practical aspects of stem cell research. It covers the advantages and limitations of many common applications related to stem cells: their sources, categories, engineering of these cells, reprogramming of their functions, and their role as novel cellular therapeutic approach. Written by experts in the field, the book focuses on aspects of stem cells ranging from expansion-propagation to metabolic reprogramming. It introduces the emergence of cancer stem cells and different modalities in targeted cancer stem cell therapies. It is a valuable source of fresh information for academics and researchers, examining molecular mechanisms of animal and plant stem cell regulation and their usage for therapeutic applications. Students at all levels of medical or engineering backgrounds will enjoy the case studies that illustrate and explain mechanisms, interactions, targeted effects, and multimodal therapeutic approaches. Academics, researchers, and professionals who want to expand their knowledge in this field will find this book an exceptional resource.

A RADIO 4 BOOK OF THE WEEK 'Full of delightful nuggets' Guardian online 'Entertaining, informative and philosphical ... An essential read' All About History 'Extraordinary range ... All the world and more is here' Evening Standard 165 million years ago saw the birth of rhythm. 66 million years ago came the first melody. 40 thousand years ago Homo sapiens created the first musical instrument. Today music fills our lives. How we have created, performed and listened to music throughout history has defined what our species is and how we understand who we are. Yet it is an overlooked part of our origin story. The Musical Human takes us on an exhilarating journey across the ages - from Bach to BTS and back - to explore the vibrant relationship between music and the human species. With insights from a wealth of disciplines, world-leading musicologist Michael Spitzer renders a global history of music on the widest possible canvas, from global history to our everyday lives, from insects to apes, humans to artificial intelligence. 'Michael Spitzer has pulled off the impossible: a Guns, Germs and Steel for music' Daniel Levitin 'A thrilling exploration of what music has meant and means to humankind' Ian Bostridge

This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.

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.

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 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.

This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and funded by the Science Foundation Ireland under its Mathematics Initiative.

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.

An edited volume describing the latest developments in approaching the problem of polymer sequence analysis, with special emphasis on the most relevant biopolymers (peptides and DNA) but not limited to them. The chapters will include peptide sequence analysis, DNA sequence analysis, analysis of biopolymers and nonpolymers, sequence alignment problems, and more.