Designed for a one or two semester non-majors course in introductory biology taught at most two and four-year colleges. This course typically fulfills a general education requirement, and rather than emphasizing mastery of technical topics, it focuses on the understanding of biological ideas and concepts, how they relate to real life, and appreciating the scientific methods and thought processes. Given the authors' work in and dedication to science education, this text's writing style, pedagogy, and integrated support package are all based on classroom-tested teaching strategies and learning theory. The result is a learning program that enhances the effectiveness & efficiency of the teaching and learning experience in the introductory biology course like no other before it.

Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next-generation sequencing technologies, together with novel and constantly evolving, distinct types of omics data technologies, have created an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information and requires tools from the computational sciences. In the last few years, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance in boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. The PACBB’17 conference was intended to contribute to this effort and promote this fruitful interaction, with a technical program that included 39 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Further, the conference promoted the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists).

This book constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2009, held in Tübingen, Germany, in April 2009 colocated with the Evo* 2009 events. The 17 revised full papers were carefully reviewed and selected from 44 submissions. EvoBio is the premiere European event for experts in computer science meeting with experts in bioinformatics and the biological sciences, all interested in the interface between evolutionary computation, machine learning, data mining, bioinformatics, and computational biology. Topics addressed by the papers include biomarker discovery, cell simulation and modeling, ecological modeling, uxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and alignment, as well as systems biology.

This innovative book provides a completely fresh exploration of bioinformatics, investigating its complex interrelationship with biology and computer science. It approaches bioinformatics from a unique perspective, highlighting interdisciplinary gaps that often trap the unwary. The book considers how the need for biological databases drove the evolution of bioinformatics; it reviews bioinformatics basics (including database formats, data-types and current analysis methods), and examines key topics in computer science (including data-structures, identifiers and algorithms), reflecting on their use and abuse in bioinformatics. Bringing these disciplines together, this book is an essential read for those who wish to better understand the challenges for bioinformatics at the interface of biology and computer science, and how to bridge the gaps. It will be an invaluable resource for advanced undergraduate and postgraduate students, and for lecturers, researchers and professionals with an interest in this fascinating, fast-moving discipline and the knotty problems that surround it.

Here's the first focused book that puts the full range of cutting-edge biological text mining techniques and tools at your command. This comprehensive volume describes the methods of natural language processing (NLP) and their applications in the biological domain, and spells out in detail the various lexical, terminological, and ontological resources now at your disposal - and how best to utilize them.

The biological sciences cover a broad array of literature types, from younger fields like molecular biology with its reliance on recent journal articles, genomic databases, and protocol manuals to classic fields such as taxonomy with its scattered literature found in monographs and journals from the past three centuries. Using the Biological Litera

Exam Board: CCEA Level: A-level Subject: Biology First Teaching: September 2016 First Exam: June 2018 Reinforce students' understanding throughout their course; clear topic summaries with sample questions and answers will improve exam technique to achieve higher grades Written by examiners and teachers, Student Guides: · Help students identify what they need to know with a concise summary of the topics examined in the AS and A-level specification · Consolidate understanding with exam tips and knowledge check questions · Provide opportunities to improve exam technique with sample graded answers to exam-style questions · Develop independent learning and research skills · Provide the content for generating individual revision notes

Featuring a wealth of engaging content, this concept-based Course Book has been developed in cooperation with the IB to provide the most comprehensive support for the DP Biology specification, for first teaching from September 2023. Created by experienced IB authors, examiners and teachers, it is packed with activities, questions, and opportunities to regularly practice, plus extensive assessment preparation support. Use this print Course Book alongside the digital course on Oxford's Kerboodle platform for the best teaching and learning experience. Oxford's DP Science offer brings together the IB curriculum and future-facing functionality, enabling success in DP and beyond.

Mapping Biology Knowledge addresses two key topics in the context of biology, promoting meaningful learning and knowledge mapping as a strategy for achieving this goal. Meaning-making and meaning-building are examined from multiple perspectives throughout the book. In many biology courses, students become so mired in detail that they fail to grasp the big picture. Various strategies are proposed for helping instructors focus on the big picture, using the `need to know' principle to decide the level of detail students must have in a given situation. The metacognitive tools described here serve as support systems for the mind, creating an arena in which learners can operate on ideas. They include concept maps, cluster maps, webs, semantic networks, and conceptual graphs. These tools, compared and contrasted in this book, are also useful for building and assessing students' content and cognitive skills. The expanding role of computers in mapping biology knowledge is also explored.

The 12th International Symposium on Distributed Computing and Artificial Intelligence 2015 (DCAI 2015) is a forum to present applications of innovative techniques for studying and solving complex problems. The exchange of ideas between scientists and technicians from both the academic and industrial sector is essential to facilitate the development of systems that can meet the ever-increasing demands of today’s society. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This symposium is organized by the Osaka Institute of Technology, Qatar University and the University of Salamanca.