Advances in Biobanking Practice Through Public and Private Collaborations presents an analysis of methods and current models of partnership between public and private organizations designed to improve biobanking practices in European countries. Chapters describe the state-of-the-art of public-private collaborations in biobanking on a global scale, innovative approaches to public-private partnership the role of a quality management system in biobanking collaborations, quality standard criteria specifically shaped for tumor biobanks, theoretical and practical access conditions to biobanks, the general legal framework governing biobanks at national, European and international levels and a concrete public-private partnership model for managing sample requests. The contributions in this book include examples of established biobanking institutions (such as Spanish National Cancer Research Centre, National Institute of Health, Italy, and 3C-R, France among others) which serve to give readers a concrete perspective on current biobanking practices and relevant legal and ethical issues that shape the field. This book is an ideal handbook for all medical researchers, healthcare professionals and biobanking stakeholders seeking information about international biobanking practices and business models.

Bioinformatics, and by extension omic sciences – the collective disciplines that are dependent on the use of extensive datasets of biological information – present a challenge of data management for researchers all over the world. Big data collected as part of research projects and experiments can be complex, with several kinds of variables involved. Coupled with continuously changing bioinformatics and information technology tools, there is a need to bring a multidisciplinary approach into these fields. Advances in Bioinformatics, Biostatistics and Omic Sciences attempts to realize an integrated approach between all omic sciences, exploring innovative bioinformatics and biostatistical methodologies which enable researchers to unveil hidden sides of biological phenomena. This volume presents reviews on the following topics which give a glimpse of recent advances in the field: - New Integrated Mitochondrial DNA Bioinformatics Pipeline to Improve Quality Assessment of Putative Pathogenic Variants from NGS Experiments - Variant Calling on RNA Sequencing Data: State of Art and Future Perspectives - An innovative Gene Prioritization Pipeline for WES analyses - New Integrated Differential Expression Approach for RNA-Seq Data Analysis - Innovations in Data Visualization for Straightforward Interpretation of Nucleic Acid Omics Outcomes This volume serves as a guide for graduate students in bioinformatics as well as researchers planning new projects as a part of their professional and academic activities.

Better Life and Business: Cell, Brain, Mind and Sex Universal Laws is an e-book that defines the fascinating new discipline: BRAINLIFEBIZ . BRAINLIFEBIZ combines new discoveries in neurobiology, behavior and medicine with novel concepts related to conscious software programming, automation, system adaptation, module selection , self -organization and automatic discovery. In other words, BRAINLIFEBIZ is a science of the consciousness, bio quantum / random chaos computations, self-organized event trains and processes with several conditions (continuous and discrete; without leadership and central control etc.). The goal of BRAINLIFEBIZ is to create a perfect computer model that simulates animal and human behavior in a computerized experimental setting. This volume presents simulations of the firefly, cricket, katydid, frog, bird and human prefrontal cortex. The book breaks across the lines that separate scientific disciplines. It explains the global nature of the specific intelligent systems outlined above. These intelligent systems features include learning, self- organization, fuzzy logic, high speed signal processing and process control. These features are employed to generate an intelligence map. The map presents figures and equations, curves and data for major ‘Elementary Processes’: aggression, mimicry, chaos , trains, pile up, attractions, courting, mating, emotion, reasoning and consciousness . ‘Elementary Processes’ are then simulated to interact with each other and form millions of complex processes explained by universal laws behind the cell, brain, mind, sex. These laws explain, in a new way, natural selection and reproductive success in the local and global society and business. These laws can be applied in a variety of situations - from everyday stress-free life, to intelligent business decision making, but with a solid biomedical and scientific foundation. The theory behind intelligent systems can be viewed as a complement to the genetic DNA code. The brain generates various brain event trains which allow it to store information in dispersed neural networks (biologically speaking, in 25 billions of neurons some of which with thousands of synapses dispersed over the cortex). The book explains the fast, precise and clear neural diagnostic processas well as the extremely flexible powerful leader mind. Better Life and Business: Cell, Brain, Mind and Sex Universal Laws is, therefore, a valuable reference for researchers to the fascinating world of natural and man -made intelligent systems and their applications in business situations and personal lives.

The exponential increase in computing power in the late twentieth century has allowed researchers to gather, process and analyze large volumes of information and construct rational paradigms of systems. Life sciences are no exception and computing advances have led to the birth of fields such as functional genomics and bioinformatics and facilitated an expansion of our understanding of biological systems. Biological Systems: Complexity and Artificial Life is an essential primer on systems biology for biologists and researchers having a multidisciplinary background. The volume covers a variety of theoretical models explaining biological processes. The book starts with an introductory chapter on the classical molecular biology paradigm and progresses towards concepts related to enzyme kinetics, non equilibrium dynamics, cellular thermodynamics, molecular motion in cells and more. The book concludes with a philosophical note on the concept of the biological system.

Computational biology in combination with large-scale biology has played a critical role in exploring the great potentials of embryonic stem cells, resulting in significant discoveries. This e-book brings together reviews and essays from different aspects of the embryonic stem cell research thus providing a comprehensive and updated introduction and reference specifically for computational biology of embryonic stem cells. Selected topics include focused analyses of the genome, transcriptome, epigenome, proteome, and regulatory network of embryonic stem cells, the theories and tools of computational biology used in these studies, and newly available databases and on-line resources for bioinformatics research. Future perspectives of related research activities are also addressed by various authors in this e- book. The book is a valuable reference and handbook for researchers and clinicians conducting stem cell research, as well as students and medical professionals interested in regenerative medicine, developmental biology, bioinformatics and computational biology.

Most findings about molecular interactions and cellular regulatory events are published in peer-reviewed scientific literature in the form of scientific jargon. The computerized text-mining algorithms are used to convert free grammar of human language into a set of formalized relationships between biological concepts in order to use this wealth of information. The compendium of such interactions extracted from an entire set of biomedical literature is a called knowledge network. Knowledge networks are the first step in the process of digitizing molecular biological knowledge. The next step is building molecular models depicting principal molecular events that govern various biological processes. Data mining in knowledge networks is the essence of building new biological models. The purpose is to elucidate major pathways of information flow through a molecular physical interaction network that happens during a disease, a cell process or an experiment. Such models contain key proteins involved in the process and can be used for prioritizing disease targets, for understanding of drug action and prevention of drug-induced toxicities, for analysis of patient predispositions and design of personalized therapies, for design of diagnostic biomarkers and analysis of patient molecular data. This e-book contains detailed examples illustrating the path to the digital biology and computerized drug development for personalized medicine. It provides conceptual principals for building biological models and for applying the models to make predictions relevant for drug development and translational medicine. The e-book will also be useful for researchers who use high-throughput technologies for molecular profiling of disease and drug action. It provides examples for analysis of gene expression microarrays to infer biological models, to find biomarkers for drug response and for applications of high-throughput molecular profiling technologies for personalized medicine. Scientists in academia, in pharmaceutical industry as well as graduate students will benefit from reading this book. The illustrations from the book can also be readily used in taught courses for molecular biology and pharmacology.

An understanding of biological systems at cellular and molecular levels helps researchers to model cellular behavior in different experimental conditions. This, in turn, can lead to insights about the influence of cell culture environment and the effect of knockout gene research when studying mutations that affect specific metabolic pathways. A systems biology approach, therefore, allows researchers to simulate experimental observations in order to predict outcomes at the cellular level. Fundamentals of Systems Analysis and Modeling of Biosystems and Metabolism presents the basic concepts required for a systems biology approach towards cellular modeling. The book is intended as a primer for systems biology and biomedical engineering graduates and researchers. The text introduces readers to concepts related to cellular metabolism and its regulation, (enzymatic regulation and transcriptional regulation) which are also incorporated into a main metabolic model of a cell. The book also has chapters dedicated to identifying and incorporating steady-state and dynamic characteristics when considering a biological model for a computer simulation. Readers will be able to (1) understand the basis of systems analysis towards creating appropriate biological models and simulations, (2) develop useful kinetic models based on cellular transport phenomena and metabolic regulation, (3) understand how to simulate a cell growth phenotype, and analyze it with experimental data.

Computer-aided drug design and in silico screening have contributed to the discovery of several compounds that have either reached the market or entered clinical trials. In silico Lead Discovery is a compilation of the efforts of several experts on bioinformatics and drug design in developing the latest advances of in silico approaches for lead discovery. It contains an overview of structure-based, ligand-based methods and current fragment-based methods as well as examples for successful applications of such methods in discovering new hit/lead molecules for important therapeutic targets. Treatment of receptor flexibility - which is one of the most important challenges for in silico screening today – has also been highlighted in the eBook. Biomedical scientists, biologists and chemists can find valuable information here that could help them to initiate or to complete chemical biology projects with the goal of designing new hit-to-lead molecules or chemical probes for chemogenomics projects..

This e-book provides readers a short introductory MATLAB® course oriented towards various collaborative areas of biotechnology and bioscience. The text concentrates on MATLAB® fundamentals and gives examples of its application for various problems in computational biology, molecular biology, biokinetics, biomedicine, bioinformatics, and biotechnology. MATLAB® is presented with examples and applications to various school-level and advanced life science / bioengineering problems - from growing populations of microorganisms and population dynamics, reaction kinetics and reagent concentrations, predator-prey models, to data fitting and time series analysis. The book is divided into 6 chapters containing material carefully selected and tailored to teaching several groups of biotechnology students. The topics are presented in a manner that allows readers to proceed sequentially on the strength of the preceding material. Primary MATLAB® for Life Sciences: A Guide for Beginners is essentially a concise and comprehensive text that provides an easy grasp and to-the-point access to the MATLAB® tool to the community of life sciences and bioengneering undergraduates and specialists.

Bioinformatics allows researchers to answer biological questions with advanced computational methods which involves the application of statistics and mathematical modeling. Structural bioinformatics enables the prediction and analysis of 3D structures of macromolecules while Computer Aided Drug Designing (CADD) assists scientists to design effective active molecules against diseases. However, the concepts in structural bioinformatics and CADD can be complex to understand for students and educated laymen. This quick guideline is intended as a basic manual for beginner students and instructors involved in bioinformatics and computational chemistry courses. Readers will learn the basics of structural bioinformatics, primary and secondary analysis and prediction, structural visualization, structural analysis and molecular docking. The book provides the reader an easy to read summary of the tools and techniques in structural bioinformatics as well as their limitations. In this revised edition, the authors have updated information in a number of chapters with a specific focus on the section on protein structure visualization and evaluation. Additional information on protein-ligand interaction studies has also been provided in this new edition. Therefore, the book is a useful handbook for aspiring scholars who wish to learn the basic concepts in computational analysis of biomolecules.