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Statistical Population Genomics
This open access volume presents state-of-the-art inference methods in population genomics, focusing on data analysis based on rigorous statistical techniques. After introducing general concepts related to the biology of genomes and their evolution, the book covers state-of-the-art methods for the analysis of genomes in populations, including demography inference, population structure analysis and detection of selection, using both model-based inference and simulation procedures. Last but not least, it offers an overview of the current knowledge acquired by applying such methods to a large variety of eukaryotic organisms. Written in the highly successful Methods in Molecular Biology series f...
Rabbit Hole
'I fell down Rabbit Hole in an obsessive spiral' KATE REED PETTY, AUTHOR OF TRUE STORY 'A mindblowing debut' HEATHER DARWENT, author of THE THINGS WE DO TO OUR FRIENDS ________________________________ A deliciously dark and twisted debut about family secrets, true crime, and destructive obsession – by a striking new talent Teddy Angstrom is no stranger to morbid public interest in her family's tragedies. And when her father dies suddenly, ten years to the day after her sister Angie's disappearance, she intends to maintain as much privacy as she always has. Clearing out her father's office, however, Teddy discovers her father's double life: a decade-long investigation into wild conspiracies...
Gene Network Inference
This book presents recent methods for Systems Genetics (SG) data analysis, applying them to a suite of simulated SG benchmark datasets. Each of the chapter authors received the same datasets to evaluate the performance of their method to better understand which algorithms are most useful for obtaining reliable models from SG datasets. The knowledge gained from this benchmarking study will ultimately allow these algorithms to be used with confidence for SG studies e.g. of complex human diseases or food crop improvement. The book is primarily intended for researchers with a background in the life sciences, not for computer scientists or statisticians.
Fodder Oats
Background to fodder oats worldwide; Fodder oats; an overview; Fodder oats in North America; Fodder oats: an overview for South America; Fodder oats in the Maghreb; Fodder oats in Pakistan; Fodder oats in the Himalayas; Fodder oats in China; Fodder oats in New Zealand and Australia- history, production and potential; Fodder oats in Europe; Oat diseases and their control; Perspectives for fodder oats.
Cancer Evolution
Tumor progression is driven by mutations that confer growth advantages to different subpopulations of cancer cells. As a tumor grows, these subpopulations expand, accumulate new mutations, and are subjected to selective pressures from the environment, including anticancer interventions. This process, termed clonal evolution, can lead to the emergence of therapy-resistant tumors and poses a major challenge for cancer eradication efforts. Written and edited by experts in the field, this collection from Cold Spring Harbor Perspectives in Medicine examines cancer progression as an evolutionary process and explores how this way of looking at cancer may lead to more effective strategies for managi...
Guided Inquiry
This dynamic approach to an exciting form of teaching and learning will inspire students to gain insights and complex thinking skills from the school library, their community, and the wider world. Guided inquiry is a way of thinking, learning, and teaching that changes the culture of a school into a collaborative inquiry community. Global interconnectedness calls for new skills, new knowledge, and new ways of learning to prepare students with the abilities and competencies they need to meet the challenges of a changing world. The challenge for the information-age school is to educate students for living and working in this information-rich technological environment. At the core of being educ...
Computational Genomics with R
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrou...
