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93,382 result(s) for "Variation (Biology)"
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Biological individuality : integrating scientific, philosophical, and historical perspectives
Individuals are things that everybody knows or thinks they do. Yet even scholars who practice or analyze the biological sciences often cannot agree on what an individual is and why. One reason for this disagreement is that the many important biological individuality concepts serve very different purposes defining, classifying, or explaining living structure, function, interaction, persistence, or evolution. Indeed, as the contributors to Biological Individuality reveal, nature is too messy for simple definitions of this concept, organisms too quirky in the diverse ways they reproduce, function, and interact, and human ideas about individuality too fraught with philosophical and historical meaning. Bringing together biologists, historians, and philosophers, this book provides a multifaceted exploration of biological individuality that identifies leading and less familiar perceptions of individuality both past and present, what they are good for, and in what contexts. Biological practice and theory recognize individuals at myriad levels of organization, from genes to organisms to symbiotic systems. We depend on these notions of individuality to address theoretical questions about multilevel natural selection and Darwinian fitness; to illuminate empirical questions about development, function, and ecology; to ground philosophical questions about the nature of organisms and causation; and to probe historical and cultural circumstances that resonate with parallel questions about the nature of society.
Molecular panbiogeography of the tropics
Molecular studies reveal highly ordered geographic patterns in plant and animal distributions. The tropics illustrate these patterns of community immobilism leading to allopatric differentiation, as well as other patterns of mobilism, range expansion, and overlap of taxa. Integrating Earth history and biogeography, Molecular Panbiogeography of the Tropics is an alternative view of distributional history in which groups are older than suggested by fossils and fossil-calibrated molecular clocks. The author discusses possible causes for the endemism of high-level taxa in tropical America and Madagascar, and overlapping clades in South America, Africa, and Asia. The book concludes with a critique of adaptation by selection, founded on biogeography and recent work in genetics.
Reproducibility of animal research in light of biological variation
Context-dependent biological variation presents a unique challenge to the reproducibility of results in experimental animal research, because organisms’ responses to experimental treatments can vary with both genotype and environmental conditions. In March 2019, experts in animal biology, experimental design and statistics convened in Blonay, Switzerland, to discuss strategies addressing this challenge. In contrast to the current gold standard of rigorous standardization in experimental animal research, we recommend the use of systematic heterogenization of study samples and conditions by actively incorporating biological variation into study design through diversifying study samples and conditions. Here we provide the scientific rationale for this approach in the hope that researchers, regulators, funders and editors can embrace this paradigm shift. We also present a road map towards better practices in view of improving the reproducibility of animal research.In this Perspective, Hanno Würbel and colleagues argue that a disregard for incorporating biological variation in study design is an important cause of poor reproducibility in animal research. They put the case for the use of systematic heterogenization of study samples and conditions in studies to improve reproducibility.
The diversity and evolution of ecological and environmental citizen science
Citizen science-the involvement of volunteers in data collection, analysis and interpretation-simultaneously supports research and public engagement with science, and its profile is rapidly rising. Citizen science represents a diverse range of approaches, but until now this diversity has not been quantitatively explored. We conducted a systematic internet search and discovered 509 environmental and ecological citizen science projects. We scored each project for 32 attributes based on publicly obtainable information and used multiple factor analysis to summarise this variation to assess citizen science approaches. We found that projects varied according to their methodological approach from 'mass participation' (e.g. easy participation by anyone anywhere) to 'systematic monitoring' (e.g. trained volunteers repeatedly sampling at specific locations). They also varied in complexity from approaches that are 'simple' to those that are 'elaborate' (e.g. provide lots of support to gather rich, detailed datasets). There was a separate cluster of entirely computer-based projects but, in general, we found that the range of citizen science projects in ecology and the environment showed continuous variation and cannot be neatly categorised into distinct types of activity. While the diversity of projects begun in each time period (pre 1990, 1990-99, 2000-09 and 2010-13) has not increased, we found that projects tended to have become increasingly different from each other as time progressed (possibly due to changing opportunities, including technological innovation). Most projects were still active so consequently we found that the overall diversity of active projects (available for participation) increased as time progressed. Overall, understanding the landscape of citizen science in ecology and the environment (and its change over time) is valuable because it informs the comparative evaluation of the 'success' of different citizen science approaches. Comparative evaluation provides an evidence-base to inform the future development of citizen science activities.
Trade-off between conservation of biological variation and batch effect removal in deep generative modeling for single-cell transcriptomics
Background Single-cell RNA sequencing (scRNA-seq) technology has contributed significantly to diverse research areas in biology, from cancer to development. Since scRNA-seq data is high-dimensional, a common strategy is to learn low-dimensional latent representations better to understand overall structure in the data. In this work, we build upon scVI, a powerful deep generative model which can learn biologically meaningful latent representations, but which has limited explicit control of batch effects. Rather than prioritizing batch effect removal over conservation of biological variation, or vice versa, our goal is to provide a bird’s eye view of the trade-offs between these two conflicting objectives. Specifically, using the well established concept of Pareto front from economics and engineering, we seek to learn the entire trade-off curve between conservation of biological variation and removal of batch effects. Results A multi-objective optimisation technique known as Pareto multi-task learning (Pareto MTL) is used to obtain the Pareto front between conservation of biological variation and batch effect removal. Our results indicate Pareto MTL can obtain a better Pareto front than the naive scalarization approach typically encountered in the literature. In addition, we propose to measure batch effect by applying a neural-network based estimator called Mutual Information Neural Estimation (MINE) and show benefits over the more standard maximum mean discrepancy measure. Conclusion The Pareto front between conservation of biological variation and batch effect removal is a valuable tool for researchers in computational biology. Our results demonstrate the efficacy of applying Pareto MTL to estimate the Pareto front in conjunction with applying MINE to measure the batch effect.
Robustness and Evolvability in Living Systems
All living things are remarkably complex, yet their DNA is unstable, undergoing countless random mutations over generations. Despite this instability, most animals do not grow two heads or die, plants continue to thrive, and bacteria continue to divide.Robustness and Evolvability in Living Systemstackles this perplexing paradox. The book explores why genetic changes do not cause organisms to fail catastrophically and how evolution shapes organisms' robustness. Andreas Wagner looks at this problem from the ground up, starting with the alphabet of DNA, the genetic code, RNA, and protein molecules, moving on to genetic networks and embryonic development, and working his way up to whole organisms. He then develops an evolutionary explanation for robustness. Wagner shows how evolution by natural selection preferentially finds and favors robust solutions to the problems organisms face in surviving and reproducing. Such robustness, he argues, also enhances the potential for future evolutionary innovation. Wagner also argues that robustness has less to do with organisms having plenty of spare parts (the redundancy theory that has been popular) and more to do with the reality that mutations can change organisms in ways that do not substantively affect their fitness. Unparalleled in its field, this book offers the most detailed analysis available of all facets of robustness within organisms. It will appeal not only to biologists but also to engineers interested in the design of robust systems and to social scientists concerned with robustness in human communities and populations.