Constructing differential co‑expression network to predict key pathways for myocardial infarction

Network to Identify Myocardial Infarction

Using patient-reportable clinical history factors to predict myocardial infarction

Using a derivation data set of 1253 patients, we built several logistic regression and neural network models to estimate the likelihood of myocardial infarction based upon patient-reportable clinical history factors only. The best performing logistic regression model and neural network model had C-indices of 0.8444 and 0.8503, respectively, when validated on an independent data set of 500 patie...

Measuring plasma fibrinogen to predict stroke and myocardial infarction.

Epidemiological observations indicate that high plasma fibrinogen levels are strongly correlated with the frequency of two major thrombotic complications of atherosclerosis, stroke and myocardial infarction. Thrombosis is increasingly recognized as a central mechanism in stroke and myocardial infarction, and fibrinogen is involved in events thought to play a major role in thrombosis. Therefore,...

A Global Coexpression Network Approach for Connecting Genes to Specialized Metabolic Pathways in Plants.

Plants produce diverse specialized metabolites (SMs), but the genes responsible for their production and regulation remain largely unknown, hindering efforts to tap plant pharmacopeia. Given that genes comprising SM pathways exhibit environmentally dependent coregulation, we hypothesized that genes within a SM pathway would form tight associations (modules) with each other in coexpression netwo...

Testosterone levels: key to survival after myocardial infarction?

Existence of relationship between the level of sex-steroids and the risk of cardio-vascular events has been suspected for years. Men experience a gradual decrease in testosterone levels from the age of 30 and onward. Age and male gender are the strongest independent risk factors for coronary artery disease (CAD). Whilst a wide variation in CAD mortality exists between countries, a male to femal...