Network Bioscience Volume Ii

The Extended Specimen highlights the research potential for ornithological specimens, and is meant to encourage ornithologists poised to initiate a renaissance in collections-based ornithological research. Contributors illustrate how collections and specimens are used in novel ways by adopting emerging new technologies and analytical techniques. Case studies use museum specimens and emerging and non-traditional types of specimens, which are developing new methods for making biological collections more accessible and "usable" for ornithological researchers. Published in collaboration with and on behalf of The American Ornithological Society, this volume in the highly-regarded Studies in Avian Biology series documents the power of ornithological collections to address key research questions of global importance.

Principles of Neurobiology, Second Edition presents the major concepts of neuroscience with an emphasis on how we know what we know. The text is organized around a series of key experiments to illustrate how scientific progress is made and helps upper-level undergraduate and graduate students discover the relevant primary literature. Written by a single author in a clear and consistent writing style, each topic builds in complexity from electrophysiology to molecular genetics to systems level in a highly integrative approach. Students can fully engage with the content via thematically linked chapters and will be able to read the book in its entirety in a semester-long course. Principles of Neurobiology is accompanied by a rich package of online student and instructor resources including animations, figures in PowerPoint, and a Question Bank for adopting instructors.

Network science has accelerated a deep and successful trend in research that influences a range of disciplines like mathematics, graph theory, physics, statistics, data science and computer science (just to name a few) and adapts the relevant techniques and insights to address relevant but disparate social, biological, technological questions. We are now in an era of 'big biological data' supported by cost-effective high-throughput genomic, transcriptomic, proteomic, metabolomic data collection techniques that allow one to take snapshots of the cells' molecular profiles in a systematic fashion. Moreover recently, also phenotypic data, data on diseases, symptoms, patients, etc. are being collected at nation-wide level thus giving us another source of highly related (causal) 'big data'. This wealth of data is usually modeled as networks (aka binary relations, graphs or webs) of interactions, (including protein-protein, metabolic, signaling and transcription-regulatory interactions). The network model is a key view point leading to the uncovering of mesoscale phenomena, thus providing an essential bridge between the observable phenotypes and 'omics' underlying mechanisms. Moreover, network analysis is a powerful 'hypothesis generation' tool guiding the scientific cycle of 'data gathering', 'data interpretation, 'hypothesis generation' and 'hypothesis testing'. A major challenge in contemporary research is the synthesis of deep insights coming from network science with the wealth of data (often noisy, contradictory, incomplete and difficult to replicate) so to answer meaningful biological questions, in a quantifiable way using static and dynamic properties of biological networks.

The concept of community-led research has taken off in recent years in a variety of fields, from archaeology and anthropology to social work and everything in between. Drawing on case studies from Australia, the Pacific and Southeast Asia, this book considers what it means to participate in community-led research, for both communities and researchers. How can researchers and communities work together well, and how can research be reimagined using the knowledge of First Nations peoples and other communities to ensure it remains relevant, sustainable, socially just and inclusive?

Systems Evolutionary Biology: Biological Network Evolution Theory, Stochastic Evolutionary Game Strategies, and Applications to Systems Synthetic Biology discusses the evolutionary game theory and strategies of nonlinear stochastic biological networks under random genetic variations and environmental disturbances and their application to systematic synthetic biology design. The book provides more realistic stochastic biological system models to mimic the real biological systems in evolutionary process and then introduces network evolvability, stochastic evolutionary game theory and strategy based on nonlinear stochastic networks in evolution. Readers will find remarkable, revolutionary information on genetic evolutionary biology that be applied to economics, engineering and bioscience. Explains network fitness, network evolvability and network robustness of biological networks from the systematic perspective Discusses the evolutionary noncooperative and cooperative game strategies of biological networks Offers detailed diagrams to help readers understand biological networks, their systematic behaviors and the simulational results of evolutionary biological networks Includes examples in every chapter with computational simulation to illustrate the solution procedure of evolutionary theory, strategy and results

The living world runs on genomic software - what Dawn Field and Neil Davies call the 'biocode' - the sum of all DNA on Earth. In Biocode, they tell the story of a new age of scientific discovery: the growing global effort to read and map the biocode, and what that might mean for the future. The structure of DNA was identified in 1953, and the whole human genome was mapped by 2003. Since then the new field of genomics has mushroomed and is now operating on an industrial scale. Genomes can now be sequenced rapidly and increasingly cheaply. The genomes of large numbers of organisms from mammals to microbes, have been mapped. Getting your genome sequenced is becoming affordable for many. You too can check paternity, find out where your ancestors came from, or whether you are at risk of some diseases. Some check out the pedigree of their pets, while others turn genomes into art. A stray hair is enough to crudely reconstruct the face of the owner. From reading to constructing: the first steps to creating artificial life have already been taken. Some may find the rapidity of developments, and the potential for misuse, alarming. But they also open up unprecedented possibilities. The ability to read DNA has changed how we view ourselves and understand our place in nature. From the largest oceans, to the insides of our guts, we are able to explore the biosphere as never before, from the genome up. Sequencing technology has made the invisible world of microbes visible, and biodiversity genomics is revealing whole new worlds within us and without. The findings are transformational: we are all ecosystems now. Already the first efforts at 'barcoding' entire ecological communities and creating 'genomic observatories' have begun. The future, the authors argue, will involve biocoding the entire planet.