Semantic analysis is one of the most important areas in the field of natural language processing. Semantic analysis is devoted to the study of the meaning of linguistic utterances. This book describes algorithms that extract semantics from bioscience text using statistical machine learning techniques. In particular this book is concerned with the identification of concepts of interest ("entities") and the identification of the relationships that hold between them. Novel machine learning algorithms are proposed for the problems of classifying the semantic relations between nouns in noun compounds, of distinguishing among several relation types that can occur between the entities "treatment" and "disease" and the problem of identifying the interactions between proteins. The results described in this book represent first steps on the way to a comprehensive strategy of exploiting machine learning algorithms for the analysis of bioscience text.