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Biology and General Science

Biology and General Science

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The goal of structured prediction is to build machine learning models that predict relational information that itself has structure, such as being composed of multiple interrelated parts. These models, which reflect prior knowledge, task-specific relations, and constraints, are used in fields including computer vision, speech recognition, natural language processing, and computational biology. They can carry out such tasks as predicting a natural language sentence, or segmenting an image into meaningful components.

Mastering Complexity

In this book, Sanjoy Mahajan shows us that the way to master complexity is through insight rather than precision. Precision can overwhelm us with information, whereas insight connects seemingly disparate pieces of information into a simple picture. Unlike computers, humans depend on insight. Based on the author’s fifteen years of teaching at MIT, Cambridge University, and Olin College, The Art of Insight in Science and Engineering shows us how to build insight and find understanding, giving readers tools to help them solve any problem in science and engineering.

Category theory was invented in the 1940s to unify and synthesize different areas in mathematics, and it has proven remarkably successful in enabling powerful communication between disparate fields and subfields within mathematics. This book shows that category theory can be useful outside of mathematics as a rigorous, flexible, and coherent modeling language throughout the sciences.

Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional datasets. This collection describes key approaches in sparse modeling, focusing on its applications in fields including neuroscience, computational biology, and computer vision.

Reinventing the Human in the Molecular Age

The molecular life sciences are making visible what was once invisible. Yet the more we learn about our own biology, the less we are able to fit this knowledge into an integrated whole. Life is divided into new sub-units and reassembled into new forms: from genes to clones, from embryonic stages to the building-blocks of synthetic biology.

Voyages of Scientific Discovery with the Mars Exploration Rovers

Geologists in the field climb hills and hang onto craggy outcrops; they put their fingers in sand and scratch, smell, and even taste rocks. Beginning in 2004, however, a team of geologists and other planetary scientists did field science in a dark room in Pasadena, exploring Mars from NASA’s Jet Propulsion Laboratory (JPL) by means of the remotely operated Mars Exploration Rovers (MER).

How Evolution Made Humans Unique

Over the last three million years or so, our lineage has diverged sharply from those of our great ape relatives. Change has been rapid (in evolutionary terms) and pervasive. Morphology, life history, social life, sexual behavior, and foraging patterns have all shifted sharply away from those of the other great apes. In The Evolved Apprentice, Kim Sterelny argues that the divergence stems from the fact that humans gradually came to enrich the learning environment of the next generation.

Our beliefs constitute a large part of our knowledge of the world. We have beliefs about objects, about culture, about the past, and about the future. We have beliefs about other people, and we believe that they have beliefs as well. We use beliefs to predict, to explain, to create, to console, to entertain. Some of our beliefs we call theories, and we are extraordinarily creative at constructing them. Theories of quantum mechanics, evolution, and relativity are examples. But so are theories about astrology, alien abduction, guardian angels, and reincarnation.

Setting Limits on Healthcare

Most people would agree that the healthcare system in the United States is a mess. Healthcare accounts for a larger percentage of gross domestic product in the United States than in any other industrialized nation, but health outcomes do not reflect this enormous investment. In this book, Philip Rosoff offers a provocative proposal for providing quality healthcare to all Americans and controlling the out-of-control costs that threaten the economy.

The Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks

In this book, Dan Gusfield examines combinatorial algorithms to construct genealogical and exact phylogenetic networks, particularly ancestral recombination graphs (ARGs). The algorithms produce networks (or information about networks) that serve as hypotheses about the true genealogical history of observed biological sequences and can be applied to practical biological problems.

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