This issue of International Review of Neurobiology is split over 2 volumes, bringing together cutting-edge research on Bioinformatics of Behavior. The 2 volumes review current knowledge and understanding, provide a starting point for researchers and practitioners entering the field, and build a platform for further research and discovery. - Leading authors review the state-of-the-art in their field of investigation, and provide their views and perspectives for future research - Chapters are extensively referenced to provide readers with a comprehensive list of resources on the topics covered - All chapters include comprehensive background information and are written in a clear form that is also accessible to the non-specialist

This issue of International Review of Neurobiology is split over 2 volumes, bringing together cutting-edge research on Bioinformatics of Behavior. The 2 volumes review current knowledge and understanding, provide a starting point for researchers and practitioners entering the field, and build a platform for further research and discovery. Leading authors review the state-of-the-art in their field of investigation, and provide their views and perspectives for future research Chapters are extensively referenced to provide readers with a comprehensive list of resources on the topics covered All chapters include comprehensive background information and are written in a clear form that is also accessible to the non-specialist

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

This issue of International Review of Neurobiology is split over 2 volumes, bringing together cutting-edge research on Bioinformatics of Behavior. The 2 volumes review current knowledge and understanding, provide a starting point for researchers and practitioners entering the field, and build a platform for further research and discovery.

Peterson's Graduate Programs in the Biological/Biomedical Sciences & Health-Related Medical Professions 2015 contains profiles of 6,750 graduate programs at over 1,200 institutions in the biological/biomedical sciences and health-related/medical professions. Informative data profiles are included for 6,750 graduate programs in every available discipline in the biological and biomedical sciences and health-related medical professions, including facts and figures on accreditation, degree requirements, application deadlines and contact information, financial support, faculty, and student body profiles. Two-page in-depth descriptions, written by featured institutions, offer complete details on specific graduate program, school, or department as well as information on faculty research and the college or university. Comprehensive directories list programs in this volume, as well as others in the graduate series.

Informatics can vastly assist progress in research and development in cell and molecular biology and biomedicine. However, many investigators are either unaware of the ways in which informatics can improve their research or find it inaccessible due to a feeling of "informatics anxiety." This sense of apprehension results from improper communication of the principles behind these approaches and of the value of the many tools available. In fact, many researchers are inherently distrustful of these tools. A more complete understanding of bioinformatics offered in A Bioinformatics Guide for Molecular Biologists will allow the reader to become comfortable with these techniques, encouraging their use-thus helping to make sense of the vast accumulation of data. To make these concepts more accessible, the editors approach the field of bioinformatics from the viewpoint of a molecular biologist, (1) arming the biologist with a basic understanding of the fundamental concepts in the field, (2) presenting approaches for using the tools from the standpoint of the data for which they are created, and (3) showing how the field of informatics is quickly adapting to the advancements in biology and biomedical technologies. All concepts are paired with recommendations for the appropriate programming environment and tools best suited to solve the particular problem at hand. It is a must-read for those interested in learning informatics techniques required for successful research and development in the laboratory.

Peterson's Graduate Programs in the Biological/Biomedical Sciences & Health-Related Medical Professions 2014 contains comprehensive profiles of nearly 6,800 graduate programs in disciplines such as, allied health, biological & biomedical sciences, biophysics, cell, molecular, & structural biology, microbiological sciences, neuroscience & neurobiology, nursing, pharmacy & pharmaceutical sciences, physiology, public health, and more. Up-to-date data, collected through Peterson's Annual Survey of Graduate and Professional Institutions, provides valuable information on degree offerings, professional accreditation, jointly offered degrees, part-time and evening/weekend programs, postbaccalaureate distance degrees, faculty, students, requirements, expenses, financial support, faculty research, and unit head and application contact information. There are helpful links to in-depth descriptions about a specific graduate program or department, faculty members and their research, and more. There are also valuable articles on financial assistance, the graduate admissions process, advice for international and minority students, and facts about accreditation, with a current list of accrediting agencies.