Abstract: Markers are provided for detecting coronary artery disease. Levels of these markers are indicative of a patient being at risk of having or developing coronary artery disease.

Abstract: Markers are provided that are predictive of Alzheimer's disease. Levels of these markers, when different from a standard, are indicative of a patient being at risk of having or developing Alzheimer's disease.

Abstract: A method for predicting treatment response of a type II diabetes patient to rosiglitazone is provided. The method involves at least one sample from a patient having type II diabetes and analyzing biomarkers predictive of a patient who will respond to treatment with rosiglitazone. The biomarkers include, at least, interleukin-8, histidine, citrate. These biomarkers are identified in at least one classification analyses selected from the group consisting of a majority-vote based classifier and support-vector machine (SVM) classifier. Also provided is a method for predicting treatment response of a type II diabetes patient to glyburide at 8 weeks post-initiation of therapy. The method involves obtaining a sample from a type II diabetes patient who has been treated with glyburide for about 4 weeks and analyzing biomarkers predictive of a patient who will respond to treatment with glyburide at 8 weeks. The biomarkers useful in this method include, at least, sphingomyelin 23:1 and L-phenylalanine.

Abstract: Markers are provided for detecting coronary artery disease. Levels of these markers are indicative of a patient being at risk of having or developing coronary artery disease.

Abstract: Markers are provided that are predictive of Alzheimer's disease. Levels of these markers, when different from a standard, are indicative of a patient being at risk of having or developing Alzheimer's disease.

Abstract: Disclosed are methods for the practice of systems pharmacology, systems toxicology, and systems pathology using patterns, such as images, reflective of the biological state of subjects such as humans or experimental mammals. The patterns are generated from data obtained from one or more samples from one or more subjects by applying certain data treatment techniques, and are reflective of the biochemistry of the subjects. The patterns are used in drug selection and discovery, assessment of toxicity and drug efficacy, segmentation of populations, discovery of disease subtypes, as surrogate end points, in the assessment of therapeutic options, and for diagnosis and prognosis of disease.