A theoretically well-informed and richly circumstantial analysis of the ever-changing and intersecting technologies, careers, institutional and regulatory mechanisms, biological understandings, and clinical exigencies that constitute what we have come to call biomedicine. A powerful and significant contribution to our understanding of the complex and mutually constitutive worlds of biology and pathology, 'science' and 'technology.'

Charles Rosenberg

Ernest Monrad Professor of the Social Sciences, Department of the History of Science, Harvard University

A meticulously documented and theoretically sophisticated work.

Stephen Hilgartner

Cornell University

At the heart of modern biomedicine are the subtly overlapping systems of analysis through which diagnoses are made. Keating and Cambrosio have taken one of them apart, brilliantly revealing the technical, social, commercial, and regulatory aspects of its construction and maintenance. Deeply researched and imaginatively presented, their book links cells, machines, and professionals, in particular hospitals and in global nets. An important, state-of-the-art contribution.

John V. Pickstone

Centre for the History of Science, Technology and Medicine, University of Manchester

Conceptually, the work is highly innovative. It is an original contribution to the longstanding debate about the relation between the laboratory and the clinic, and I predict that it will have a major impact on future studies on the history, epistemology and social studies of biomedicine.

Hans-Jörg Rheinberger

Director, Max Planck Institute for the History of Science, Berlin

The explosive growth of the biomedical literature and the breakdown of disciplinary boundaries in biomedical research make text mining an indispensable part of modern molecular biomedicine. Mining the Biomedical Literature clearly introduces the key ideas and applications to computational biologists looking to get started in this exciting field.

Lawrence Hunter

University of Colorado School of Medicine

This book provides a lucid and accessible exposition of the most important topics in biomedical text mining and related areas of information retrieval, information extraction, and machine learning. Readers will enjoy well-chosen examples of biomedical applications and textual snippets, as well as a balanced treatment of diverse computational techniques used today. The book even provides the most important competition venues for text-mining systems.

Andrey Rzhetsky

Professor of Medicine and Human Genetics, Computation Institute and Institute for Genomics and Systems Biology, University of Chicago