title: Random Forests Are Able to Identify Differences in Clotting Dynamics from Kinetic Models of Thrombin Generation.
abstract: Current methods for distinguishing acute coronary syndromes such as heart attack from stable coronary artery disease, based on the kinetics of thrombin formation, have been limited to evaluating sensitivity of well-established chemical species (e.g., thrombin) using simple quantifiers of their concentration profiles (e.g., maximum level of thrombin concentration, area under the thrombin concentration versus time curve). In order to get an improved classifier, we use a 34-protein factor clotting cascade model and convert the simulation data into a high-dimensional representation (about 19000 features) using a piecewise cubic polynomial fit. Then, we systematically find plausible assays to effectively gauge changes in acute coronary syndrome/coronary artery disease populations by introducing a statistical learning technique called Random Forests. We find that differences associated with acute coronary syndromes emerge in combinations of a handful of features. For instance, concentrations of 3 chemical species, namely, active alpha-thrombin, tissue factor-factor VIIa-factor Xa ternary complex, and intrinsic tenase complex with factor X, at specific time windows, could be used to classify acute coronary syndromes to an accuracy of about 87.2%. Such a combination could be used to efficiently assay the coagulation system.
authors.affiliation: Department of Mechanical Engineering, Texas A&M University, College Station, Texas, United States of America.
authors.forename: Jayavel
authors.initials: J
authors.lastname: Arumugam
authors.affiliation: Department of Industrial and Systems Engineering, Texas A&M University, College Station, Texas, United States of America.
authors.forename: Satish T S
authors.initials: ST
authors.lastname: Bukkapatnam
authors.affiliation: Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, United States of America.
authors.forename: Krishna R
authors.initials: KR
authors.lastname: Narayanan
authors.affiliation: Department of Mechanical Engineering, Texas A&M University, College Station, Texas, United States of America.
authors.forename: Arun R
authors.initials: AR
authors.lastname: Srinivasa
mesh_terms: D054058:Acute Coronary Syndrome / Q000097:blood; D000465:Algorithms; D001777:Blood Coagulation / Q000502:physiology*; D001779:Blood Coagulation Factors / Q000378:metabolism; D003324:Coronary Artery Disease / Q000097:blood; D003663:Decision Trees; D006801:Humans; D007700:Kinetics; D008954:Models, Biological; D056004:Molecular Dynamics Simulation; D013917:Thrombin / Q000378:metabolism*; D013925:Thromboplastin / Q000378:metabolism; D013997:Time Factors
chemical_list: D001779:Blood Coagulation Factors; D013925:Thromboplastin; D013917:Thrombin