Beginning with a survey of fundamental concepts associated with data integration‎,‎ knowledge representation‎,‎ and hypothesis generation from heterogeneous data sets‎,‎ Methods in Biomedical Informatics provides a practical survey of methodologies used in biological‎,‎ clinical‎,‎ and public health contexts‎.‎ These concepts provide the foundation for more advanced topics like information retrieval‎,‎ natural language processing‎,‎ Bayesian modeling‎,‎ and learning classifier systems‎.‎ The survey of topics then concludes with an exposition of essential methods associated with engineering‎,‎ personalized medicine‎,‎ and linking of genomic and clinical data‎.‎ Within an overall context of the scientific method‎,‎ Methods in Biomedical Informatics provides a practical coverage of topics that is specifically designed for‎:‎ domain experts seeking an understanding of biomedical informatics approaches for addressing specific methodological needs‎;‎ or biomedical informaticians seeking an approachable overview of methodologies that can be used in scenarios germane to biomedical research‎.‎ Contributors represent leading biomedical informatics experts‎:‎ individuals who have demonstrated effective use of biomedical informatics methodologies in the real‎-world‎,‎ high‎-quality biomedical applications‎;‎ and Material is presented as a balance between foundational coverage of core topics in biomedical informatics with practical ‎"‎in‎-the‎-trenches‎"‎ scenarios‎.‎ It contains appendices that function as primers on‎:‎ Unix‎;‎ Ruby‎;‎ Databases‎;‎ and Web Services‎.‎