Since the decoding of the Human Genome in 2003, bioinformatics, data mining, and machine learning techniques have been involved in uncovering patterns and increasing amounts and types of different data produced by profiling technologies applied to clinical samples, animal models, and cellular systems. Yet, progress on unravelling biological mechanisms, that have been implicated in the pathogenesis of many diseases, has been restricted, in part due to the characteristic complexity of biological systems. Although scientific community has achieved notable progress in deciphering the areas of cancer, cardiovascular and metabolic diseases, neurodegenerative diseases have proved to be more perplexed and very challenging. 

Afflicted neurons in most neurodegenerative diseases display in general complicated and dissimilar pathological features before the catastrophic incidence of vast neuronal loss at the late stages of the diseases. The complex nature of neuronal pathophysiology inevitably implicates system wide alterations in fundamental cellular mechanisms such as transcriptional regulators and signal cascades as a cause. Moreover, most clinical trials into treatments for neurodegenerative diseases and especially for Alzheimer’s disease have failed. A probable reason for the high failure rate is that treatments are being tested on those who already have irreversible impairment to the brain.  So, treatments that slow or stop further neuron deterioration will be more effective if they are applied at earlier stages of the disease. Nowadays there is a clear need for a widely available, inexpensive and reliable method to early screen for these diseases. Also, by detecting dementia at earlier stages, it should be possible to design better clinical trials for treatments that make a real difference and improve people’s lives.

Neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease are a global health, economic and social emergency.  More than 40 million people worldwide are estimated to suffer from Alzheimer’s disease and related disorders and predictions suggest this number may double by 2050.

Modeling and simulating the molecular processes of biological cells and tissues is a craft and an art. In “Computational Models for Neurodegeneration” workshop a panel of bioinformatics and modeling approaches that have recently been developed to identify candidate mechanisms of neurodegenerative diseases based on publicly available data and knowledge will be described by prominent scientists. In the Computational Models for Neurodegeneration workshop, participants will be enlightened in specific topics that include: Applied Mathematics, Data Mining, Modeling, Biophysics, Biochemistry, Bioinformatics, Neuroinformatics and Computational Mathematics in Biology. The purpose of this workshop is to bring together experts from the mathematical, computational, and medical scientist’s communities and provide a platform for the exchange of ideas. The workshop is envisioned to survey the state-of-the-art in modeling, mathematical analysis, and computational practice mostly on the field of neurodegenerative diseases, while exploring new application domains and promoting new collaborations.