Computational Cardiology Models and Methods

Dear Colleagues,

In cardiology practice, new imaging, genetic screening, and gadgets are becoming more and more important for treating individual patients. The difficulty of using a patient's whole range of measures to decide the best course of therapy appears to be paradoxically growing as the amount of imaging and other diagnostic data rises, accompanied by the increased ability to customize treatment.

Computational models, which provide a common framework for merging diverse patient data sets, are progressively addressing this issue. These models, which are based on physiology and physics rather than population statistics, enable computational simulations to predict treatment outcomes for specific patients and reveal diagnostic data that would have been concealed otherwise.

The "Basic and Translational Cardiovascular Research" section of JCDD includes research on the pathophysiology of cardiovascular diseases and the basic scientific principles of cardiovascular medicine. Transforming the latest findings from the bench to the clinic, the investigations in this part generally examine the cardiovascular system from the molecular, protein, cellular, tissue-engineering, organ, and/or animal model levels.

We welcome submissions of manuscripts that cover relevant topics, including but not limited to the following: Congenital heart disease, heart failure, regeneration, biomarkers, cardiac fibrosis, transcriptional regulation, hypertension, cardiomyopathy, gene regulation, transcription factors, epigenetics, heart failure with preserved ejection fraction, epigenetic regulation, arrhythmia, myocardial infarction, coronary artery disease, zebrafish, cardiac biology, stem cells, conduction system, bioprostheses, cardiac regeneration, tissue engineering, and disease modeling.

Prof. Dr. Nicholas G Kounis
Prof. Dr. Cesare De Gregorio
Guest Editors

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