Computers have become an essential component of modern biology. They help to manage the vast and increasing amount of biological data and continue to play an integral role in the discovery of new biological relationships. This in silico approach to biology has helped to reshape the modern biological sciences. With the biological revolution now among us, it is imperative that each scientist develop and hone today’s bioinformatics skills, if only at a rudimentary level. Bioinformatics Methods and Protocols was conceived as part of the Methods in Molecular Biology series to meet this challenge and to provide the experienced user with useful tips and an up-to-date overview of current developments. It builds upon the foundation that was provided in the two-volume set published in 1994 entitled Computer Analysis of Sequence Data. We divided Bioinformatics Methods and Protocols into five parts, including a thorough survey of the basic sequence analysis software packages that are available at most institutions, as well as the design and implemen- tion of an essential introductory Bioinformatics course. In addition, we included sections describing specialized noncommercial software, databases, and other resources available as part of the World Wide Web and a stimul- ing discussion of some of the computational challenges biologists now face and likely future solutions.

This book constitutes the thoroughly refereed post-proceedings of the 7th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2010, held in Palermo, Italy, in September 2010. The 19 papers, presented together with 2 keynote speeches and 1 tutorial, were carefully reviewed and selected from 24 submissions. The papers are organized in topical sections on sequence analysis, promoter analysis and identification of transcription factor binding sites; methods for the unsupervised analysis, validation and visualization of structures discovered in bio-molecular data -- prediction of secondary and tertiary protein structures; gene expression data analysis; bio-medical text mining and imaging -- methods for diagnosis and prognosis; mathematical modelling and simulation of biological systems; and intelligent clinical decision support systems (i-CDSS).

Annotation. This book constitutes the thoroughly refereed post-conference proceedings of the Sixth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2009, held in Genova, Italy, in October 2009. The revised 23 full papers presented were carefully reviewed and selected from 57 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 tools for bioinformatics, gene expression analysis and new perspectives in bioinformatics together with 4 special sessions on using game-theoretical tools in bioinformatics, combining Bayesian and machine learning approaches in bioinformatics: state of the art and future perspectives, data clustering and bioinformatics (DCB 2009) and on intelligent systems for medical decisions support (ISMDS 2009).

Covering the latest developments in clinical omics, this volume details the algorithms currently used in publicly available software tools. It looks at statistics, algorithms, automated data retrieval, and experimental consideration in the various omics areas.

In Bioinformatics, leading researchers provide a selection of the most useful and widely applicable methods, able to be applied as is, or with minor variations, to many specific problems. Volume II: Structure, Function and Applications contains methods pertinent to the prediction of protein and RNA structures and the analysis and classification of structures, methods for inferring the function of previously identified genomic elements, chiefly protein-coding genes, medical applications in diagnostics and drug discovery, and "meta-methods" for developers of bioinformatics algorithms. Over 80 authors from around the globe have contributed to the two volumes.

This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible. Accordingly, the series presented here bring forward a wide range of artificial intelligence approaches and statistical methods that can be applied to imaging and genomics data sets to identify previously unrecognized features that are critical for cancer. Our hope is that these articles will serve as a foundation for future research as the field of cancer biology transitions to integrating electronic health record, imaging, genomics and other complex datasets in order to develop new strategies that improve the overall health of individual patients.

Microorganisms, like bacteria and fungi, are ubiquitous worldwide and can have different roles in human’s lives. Some will bring beneficial effects which are exploited and used in industrial and agricultural sectors. Contrariwise, some are responsible for several life-threatening diseases. Microbial analysis, surveillance and research is therefore crucial. Until recently, the classical culturing methods were widely used to study bacteria and fungi. However these methods, although considered the gold standard, are becoming now obsolete since they tend to be time-consuming, have low sensitivity and are unable to detect some cellular morphological states, as the viable but non-culturable (VBNC) state, leading to false negative results. Moving away from the classical methods, microbial detection is now evolving to new effective and rapid diagnostics.

This book provides an overview of the current state of research on development and application of methods, algorithms, tools and systems associated with the studies on man-machine interaction. Modern machines and computer systems are designed not only to process information, but also to work in dynamic environment, supporting or even replacing human activities in areas such as business, industry, medicine or military. The interdisciplinary field of research on man-machine interactions focuses on broad range of aspects related to the ways in which human make or use computational artifacts, systems and infrastructure. This monograph is the fourth edition in the series and presents new concepts concerning analysis, design and evaluation of man-machine systems. The selection of high-quality, original papers covers a wide scope of research topics focused on the main problems and challenges encountered within rapidly evolving new forms of human-machine relationships. The presented material is structured into following sections: human-computer interfaces, robot, control, embedded and navigation systems, bio-data analysis and mining, biomedical signal processing, image and motion data processing, decision support and expert systems, pattern recognition, fuzzy systems, algorithms and optimisation, computer networks and mobile technologies, and data management systems.

Systems biology is a term used to describe a number of trends in bioscience research and a movement that draws on those trends. This volume in the Methods in Enzymology series comprehensively covers the methods in systems biology. With an international board of authors, this volume is split into sections that cover subjects such as machines for systems biology, protein production and quantification for systems biology, and enzymatic assays in systems biology research. - This volume in the Methods in Enzymology series comprehensively covers the methods in systems biology - With an international board of authors, this volume is split into sections that cover subjects such as machines for systems biology, protein production and quantification for systems biology, and enzymatic assays in systems biology research

Thoroughly revised and updated, Exploring Bioinformatics: A Project-Based Approach, Second Edition is intended for an introductory course in bioinformatics at the undergraduate level. Through hands-on projects, students are introduced to current biological problems and then explore and develop bioinformatic solutions to these issues. Each chapter presents a key problem, provides basic biological concepts, introduces computational techniques to address the problem, and guides students through the use of existing web-based tools and software solutions. This progression prepares students to tackle the On-Your-Own Project, where they develop their own software solutions. Topics such as antibiotic resistance, genetic disease, and genome sequencing provide context and relevance to capture student interest.