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This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.
The Nobel Prizes m natural sciences have achieved the reputation of being the ultimate accolade for scientific achievements. This honk gives a unique insight into the selection of Nobel Prize recipients, in particular the life sciences. The evolving mechanisms of selection of prize recipients are illustrated by reference to archives, which have remained secret for 1) years. Many of the prizes subjected to particular evaluation concern awards given for discoveries in the field of infectious diseases and the interconnected field of genetics. The book illustrates the individuals and environments that are conducive to scientific creativity. Nowhere is this enigmatic activity'-- the mime mover in advancing the human condition highlighted as lucidly as by identification individuals worthy of Nobel Prizes. --Book Jacket.
Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working
Each chapter has three types of learning aides for students: open-ended questions, multiple-choice questions, and quantitative problems. There is an average of about 50 per chapter. There are also a number of worked examples in the chapters, averaging over 5 per chapter, and almost 600 photos and line drawings.
The second half of the twentieth century brought extraordinary transformations in knowledge and practice of the life sciences. In an era of decolonization, mass social welfare policies, and the formation of new international institutions such as UNESCO and the WHO, monumental advances were made in both theoretical and practical applications of the life sciences, including the discovery of life’s molecular processes and substantive improvements in global public health and medicine. Combining perspectives from the history of science and world history, this volume examines the impact of major world-historical processes of the postwar period on the evolution of the life sciences. Contributors consider the long-term evolution of scientific practice, research, and innovation across a range of fields and subfields in the life sciences, and in the context of Cold War anxieties and ambitions. Together, they examine how the formation of international organizations and global research programs allowed for transnational exchange and cooperation, but in a period rife with competition and nationalist interests, which influenced dramatic changes in the field as the postcolonial world order unfolded.
A clear and concise survey of the major themes and theories embedded in the history of life science, this book covers the development and significance of scientific methodologies, the relationship between science and society, and the diverse ideologies and current paradigms affecting the evolution and progression of biological studies. The author discusses cell theory, embryology, physiology, microbiology, evolution, genetics, and molecular biology; the Human Genome Project; and genomics and proteomics. Covering the philosophies of ancient civilizations to modern advances in genomics and molecular biology, the book is a unique and comprehensive resource.
The potential misuse of advances in life sciences research is raising concerns about national security threats. Dual Use Research of Concern in the Life Sciences: Current Issues and Controversies examines the U.S. strategy for reducing biosecurity risks in life sciences research and considers mechanisms that would allow researchers to manage the dissemination of the results of research while mitigating the potential for harm to national security.
This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.
Broad perspective on collectivity in the life sciences, from microorganisms to human consensus, and the theoretical and empirical opportunities and challenges. Many researchers and scholars in the life sciences have become increasingly critical of the traditional methodological focus on the individual. This volume counters such methodological individualism by exploring recent and influential work in the life sciences that utilizes notions of collectivity, sociality, rich interactions, and emergent phenomena as essential explanatory tools to handle numerous persistent scientific questions in the life sciences. The contributors consider case studies of collectivity that range from microorganisms to human consensus, discussing theoretical and empirical challenges and the innovative methods and solutions scientists have devised. The contributors offer historical, philosophical, and biological perspectives on collectivity, and describe collective phenomena seen in insects, the immune system, communication, and human collectivity, with examples ranging from cooperative transport in the longhorn crazy ant to the evolution of autobiographical memory. They examine ways of explaining collectivity, including case studies and modeling approaches, and explore collectivity's explanatory power. They present a comprehensive look at a specific case of collectivity: the Holobiont notion (the idea of a multi-species collective, a host and diverse microorganisms) and the hologenome theory (which posits that the holobiont and its hologenome are a unit of adaption). The volume concludes with reflections on the work of the late physicist Eshel Ben-Jacob, pioneer in the study of collective phenomena in living systems. Contributors Oren Bader, John Beatty, Dinah R. Davison, Daniel Dor, Ofer Feinerman, Raghavendra Gadagkar, Scott F. Gilbert, Snait B. Gissis, Deborah M. Gordon, James Griesemer, Zachariah I. Grochau-Wright, Erik R. Hanschen, Eva Jablonka, Mohit Kumar Jolly, Anat Kolumbus, Ehud Lamm, Herbert Levine, Arnon Levy, Xue-Fei Li, Elisabeth A. Lloyd, Yael Lubin, Eva Maria Luef, Ehud Meron, Richard E. Michod, Samir Okasha, Simone Pika, Joan Roughgarden, Eugene Rosenberg, Ayelet Shavit, Yael Silver, Alfred I. Tauber, Ilana Zilber-Rosenberg
“I thoroughly enjoyed reading this book as it has taken me on a journey through time, across the globe and through multiple disciplines. Indeed, we need to be thinking about these concepts and applying them every day to do our jobs better.” Farah Magrabi, Macquarie University, Australia “The reader will find intriguing not only the title but also the content of the book. I’m also pleased that public health, and even more specifically epidemiology has an important place in this ambitious discussion.” Elena Andresen, Oregon Health & Science University, USA “This book is very well written and addresses an important topic. It presents many reasons why basic scientists/researchers should establish collaborations and access information outside traditional means and not limit thinking but rather expand such and perhaps develop more innovative and translational research ventures that will advance science and not move it laterally.” Gerald Pepe, Eastern Virginia Medical School, USA “This book gathers logically and presents interestingly (with many examples) the qualities and attitudes a researcher must possess in order to become successful. On the long run, the deep and carefully reexamined research will be the one that lasts.” Zoltán Néda, Babeş-Bolyai University, Romania “I really liked the five pillars delineating the components of humanism in research. This book has made a major contribution to the research ethics literature.” David Fleming, University of Missouri, USA A comprehensive review of the research phase of life sciences from design to discovery with suggestions to improve innovation This vital resource explores the creative processes leading to biomedical innovation, identifies the obstacles and best practices of innovative laboratories, and supports the production of effective science. Innovative Research in Life Sciences draws on lessons from 400 award-winning scientists and research from leading universities. The book explores the innovative process in life sciences and puts the focus on how great ideas are born and become landmark scientific discoveries. The text provides a unique resource for developing professional competencies and applied skills of life sciences researchers. The book examines what happens before the scientific paper is submitted for publication or the innovation becomes legally protected. This phase is the most neglected but most exciting in the process of scientific creativity and innovation. The author identifies twelve competencies of innovative biomedical researchers that described and analyzed. This important resource: Highlights the research phase from design to discovery that precedes innovation disclosure Offers a step by step explanation of how to improve innovation Offers solutions for improving research and innovation productivity in the life sciences Contains a variety of statistical databases and a vast number of stories about individual discoveries Includes a process of published studies and national statistics of biomedical research and reviews the performance of research labs and academic institutions Written for academics and researchers in biomedicine, pharmaceutical science, life sciences, drug discovery, pharmacology, Innovative Research in Life Sciences offers a guide to the creative processes leading to biomedical innovation and identifies the best practices of innovative scientists and laboratories.