Book Summary :

This book constitutes the thoroughly refereed post-conference proceedings of the Fifth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2008, held in Vietri sul Mare, Italy, in October 2008. The 23 revised full papers presented together with 3 invited lectures were carefully reviewed and selected from 69 submissions. The main goal of the CIBB meetings is to provide a forum open to researchers from different disciplines to present and discuss problems concerning computational techniques in bioinformatics, systems biology and medical informatics with a particular focus on neural networks, machine learning, fuzzy logic, and evolutionary computation methods.

Book Summary :

Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.

Book Summary :

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.

Book Summary :

The study of brain function is one of the most fascinating pursuits of m- ern science. Functional neuroimaging is an important component of much of the current research in cognitive, clinical, and social psychology. The exci- ment of studying the brain is recognized in both the popular press and the scienti?c community. In the pages of mainstream publications, including The New York Times and Wired, readers can learn about cutting-edge research into topics such as understanding how customers react to products and - vertisements (“If your brain has a ‘buy button,’ what pushes it?”, The New York Times,October19,2004),howviewersrespondtocampaignads(“Using M. R. I. ’s to see politics on the brain,” The New York Times, April 20, 2004; “This is your brain on Hillary: Political neuroscience hits new low,” Wired, November 12,2007),howmen and womenreactto sexualstimulation (“Brain scans arouse researchers,”Wired, April 19, 2004), distinguishing lies from the truth (“Duped,” The New Yorker, July 2, 2007; “Woman convicted of child abuse hopes fMRI can prove her innocence,” Wired, November 5, 2007), and even what separates “cool” people from “nerds” (“If you secretly like Michael Bolton, we’ll know,” Wired, October 2004). Reports on pathologies such as autism, in which neuroimaging plays a large role, are also common (for - stance, a Time magazine cover story from May 6, 2002, entitled “Inside the world of autism”).

Book Summary :

Foreword by Walter J. Freeman. The induction of unconsciousness using anesthetic agents demonstrates that the cerebral cortex can operate in two very different behavioral modes: alert and responsive vs. unaware and quiescent. But the states of wakefulness and sleep are not single-neuron properties---they emerge as bulk properties of cooperating populations of neurons, with the switchover between states being similar to the physical change of phase observed when water freezes or ice melts. Some brain-state transitions, such as sleep cycling, anesthetic induction, epileptic seizure, are obvious and detected readily with a few EEG electrodes; others, such as the emergence of gamma rhythms during cognition, or the ultra-slow BOLD rhythms of relaxed free-association, are much more subtle. The unifying theme of this book is the notion that all of these bulk changes in brain behavior can be treated as phase transitions between distinct brain states. Modeling Phase Transitions in the Brain contains chapter contributions from leading researchers who apply state-space methods, network models, and biophysically-motivated continuum approaches to investigate a range of neuroscientifically relevant problems that include analysis of nonstationary EEG time-series; network topologies that limit epileptic spreading; saddle--node bifurcations for anesthesia, sleep-cycling, and the wake--sleep switch; prediction of dynamical and noise-induced spatiotemporal instabilities underlying BOLD, alpha-, and gamma-band Hopf oscillations, gap-junction-moderated Turing structures, and Hopf-Turing interactions leading to cortical waves.

Book Summary :

This book constitutes the proceedings of the 16th International Symposium on Bioinformatics Research and Applications, ISBRA 2020, held in Moscow, Russia, in December 2020. The 23 full papers and 18 short papers presented in this book were carefully reviewed and selected from 131 submissions. They were organized in topical sections named: genome analysis; systems biology; computational proteomics; machine and deep learning; and data analysis and methodology.

Book Summary :

This book presents applications of bioinformatics tools that experimental research scientists use in "daily practice." Its interdisciplinary approach combines computational and experimental methods to solve scientific problems. The book begins with reviews of computational methods for protein sequence-structure-function analysis, followed by methods that use experimental data obtained in the laboratory to improve functional predictions.

Book Summary :

This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.

Book Summary :

This book explores the exciting world of theoretical biology and is divided into three sections. The first section examines the roles played by renowned scientists such as Jacob, Monod, Rosen, Turing, von Bertalanffy, Waddington and Woodger in developing the field of theoretical biology. The second section, aided with numerous examples, supports the idea that logic and computing are suitable formal languages to describe and understand biological phenomena. The third and final section is, without doubt, the most intellectually challenging and endeavors to show the possible paths we could take to compute a cell - the basic unit of life - or the conditions required for a predictive theory of biological evolution; ultimately, a theory of life in the light of modern Systems Biology. The work aims to show that modern biology is closer than ever to making Goethe's dream come true and that we have reached a point where synthetic and analytical traditions converge to shed light on the living being as a whole.

Book Summary :

This book clearly defines ways to maximize the allelopathic potential of important field crops for controlling weeds, either in the same crop or others. Compared to the use of herbicides, allelopathy is an attractive option to control weeds naturally under field conditions. The book highlights the allelopathic potential of several important cereals (wheat, maize, rice, barley, sorghum, rye) and two oilseed crops [sunflower and canola (as well as some other member of Brassicaceae family)]. Further, the book explains how the allelopathic potential of these crops can be manipulated under field conditions to suppress weeds. This is possible by growing allelopathic crop cultivars, using mulches from allelopathic crops, intercropping an allelopathic crop with a non-allelopathic crop, including allelopathic crops in crop rotation, or using allelopathic crops as cover crops. Equipped with several basic concepts of allelopathy, this book will be highly useful for the farming community as well as students and researchers.

Book Summary :

Weed management Decision Support Systems (DSS) are increasingly important computer-based tools for modern agriculture. Nowadays, extensive agriculture has become highly dependent on external inputs and both economic costs, as well the negative environmental impact of agricultural activities, demands knowledge-based technology for the optimization and protection of non-renewable resources. In this context, weed management strategies should aim to maximize economic profit by preserving and enhancing agricultural systems. Although previous contributions focusing on weed biology and weed management provide valuable insight on many aspects of weed species ecology and practical guides for weed control, no attempts have been made to highlight the forthcoming importance of DSS in weed management. This book is a first attempt to integrate `concepts and practice’ providing a novel guide to the state-of-art of DSS and the future prospects which hopefully would be of interest to higher-level students, academics and professionals in related areas.

Book Summary :

This book presents established and new approaches to perform calculations of electrostatic interactions at the nanoscale, with particular focus on molecular biology applications. It is based on the proceedings of the Computational Electrostatics for Biological Applications international meeting, which brought together researchers in computational disciplines to discuss and explore diverse methods to improve electrostatic calculations. Fostering an interdisciplinary approach to the description of complex physical and biological problems, this book encompasses contributions originating in the fields of geometry processing, shape modeling, applied mathematics, and computational biology and chemistry. The main topics covered are theoretical and numerical aspects of the solution of the Poisson-Boltzmann equation, surveys and comparison among geometric approaches to the modelling of molecular surfaces and related discretization and computational issues. It also includes a number of contributions addressing applications in biology, biophysics and nanotechnology. The book is primarily intended as a reference for researchers in the computational molecular biology and chemistry fields. As such, it also aims at becoming a key source of information for a wide range of scientists who need to know how modeling and computing at the molecular level may influence the design and interpretation of their experiments.