Genetics From Genes to Genomes – 6th Edition

About the Author

Dr. Leland Hartwell is President and Director of Seattle’s Fred Hutchinson Cancer Research Center and Professor of Genome Sciences at the University of Washington. Dr. Hartwell’s primary research contributions were in identifying genes that control cell division in yeast, including those necessary for the division process as well as those necessary for the fidelity of genome reproduction. Subsequently, many of these same genes have been found to control cell division in humans and often to be the site of alteration in cancer cells. Dr. Hartwell is a member of the National Academy of Sciences and has received the Albert Lasker Basic Medical Research Award, the Gairdner Foundation International Award, the Genetics Society Medal, and the 2001 Nobel Prize in Physiology or Medicine.

Dr. Michael Goldberg
is a Professor at Cornell University, where he teaches introductory genetics and human genetics. He was an undergraduate at Yale University and received his Ph.D. in biochemistry from Stanford University. Dr. Goldberg performed postdoctoral research at the Biozentrum of the University of Basel (Switzerland) and at Harvard University, and he received an NIH Fogarty Senior International Fellowship for study at Imperial College (England) and fellowships from the Fondazione Cenci Bolognetti for sabbatical work at the University of Rome (Italy). His current research uses the tools of Drosophila genetics and the biochemical analysis of frog egg cell extracts to investigate the mechanisms that ensure proper cell cycle progression and
chromosome segregation during mitosis and meiosis.

Dr. Janice Fischer is a Professor at The University of Texas at Austin, where she is an awardwinning teacher of genetics and Director of the Biology Instructional Office. She received her Ph.D. in biochemistry and molecular biology from Harvard University, and did postdoctoral research at The University of California at Berkeley and The Whitehead Institute at MIT. In her research, Dr. Fischer used Drosophila first to determine how tissue-specific transcription works, and then to examine the roles of ubiquitin and endocytosis in cell signaling during development.

Dr. Lee Hood received an M.D. from the Johns Hopkins Medical School and a Ph.D. in biochemistry from the California Institute of Technology. His research interests include immunology, cancer biology, development, and the development of biological instrumentation (for example, the protein sequencer and the automated fluorescent DNA sequencer). His early research played a key role in unraveling the mysteries of antibody diversity. More recently he has pioneered systems approaches to biology and medicine. Dr. Hood has taught molecular evolution, immunology, molecular biology, genomics and biochemistry and has co-authored textbooks in biochemistry, molecular biology, and immunology, as well as The Code of Codes—a monograph about the Human Genome Project. He was one of the first advocates for the Human Genome Project and directed one of the federal genome centers that sequenced the human genome. Dr. Hood is currently the president (and co-founder) of the crossdisciplinary Institute for Systems Biology in Seattle, Washington. Dr. Hood has received a variety of awards, including the Albert Lasker Award for Medical Research (1987), the Distinguished Service Award from the National Association of Teachers (1998) and the Lemelson/MIT Award for Invention (2003). He is the 2002 recipient of the Kyoto
Prize in Advanced Biotechnology—an award recognizing his pioneering work in developing the protein and DNA synthesizers and sequencers that provide the technical foundation of modern biology. He is deeply involved in K–12 science education. His hobbies include running, mountain climbing, and reading.

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Product details


McGraw-Hill Education






6 edition
September 20, 2017

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About the Author

Dr. Janice Fischer

Dr. Lee Hood

Dr. Leland Hartwell

Dr. Michael Goldberg


This book was written to solve a problem. The people who I interview for data science jobs have sterling mathematical pedigrees, but most of them are unable to write a simple script that computes Fibonacci numbers (in case you aren’t familiar with Fibonacci numbers, this takes about five lines of code). On the other side, employers tend to view data scientists as either mysterious wizards or used‐car salesmen (and when data scientists can’t be trusted to write a basic script, the latter impression has some merit!). These problems reflect a fundamental misunderstanding, by all parties, of what data science is (and isn’t) and what skills its practitioners need. When I first got into data science, I was part of that problem. Years of doing academic physics had trained me to solve problems in a way that was long on abstract theory but short on common sense or flexibility. Mercifully, I also knew how to code (thanks, Googleinternships!), and this let me limp along while I picked up the skills and mindsets that actually mattered.
Since leaving academia, I have done data science consulting for companies of every stripe. This includes web traffic analysis for tiny start‐ups, manufacturing optimizations for Fortune 100 giants, and everything in between. The problems to solve are always unique, but the skills required to solve them are strikingly universal. They are an eclectic mix of computer programming, mathematics, and business savvy. They are rarely found together in one person, but in truth they can be learned by anybody. A few interviews I have given stand out in my mind. The candidate was smart and knowledgeable, but the interview made it painfully clear that they were unprepared for the daily work of a data scientist. What do you do as an interviewer when the candidate starts apologizing for wasting your time? We ended up filling the hour with a crash course on what they were missing and how they could go out and fill the gaps in their knowledge. They went out, learned what they needed to, and are now successful data scientists. I wrote this book in an attempt to help people like that out, by condensing data science’s various skill sets into a single, coherent volume. It is hands‐on