Dear Colleagues,

Neurodegenerative diseases are increasingly being recognized as an important issue in health care and health outcomes. The incidence of neurodegenerative diseases in older patients is especially high. According to the most recent estimates, neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, multiple sclerosis, stroke, spinal cord injury, and vascular dementia are the leading causes that negatively affect quality of life in the elderly population worldwide. Commensurate with neurodegenerative diseases are systemic changes in neurosecretory signaling, as well as in whole body endocrine signaling. To date, however, no effective treatments for neurosecretory signaling-related neurodegenerative disorders have been found. There is accumulating evidence to suggest that computational methods, especially in bioinformatics and medical informatics, could be critical in solving this issue.

In the post-genome era, numerous computational methods have been developed and applied to the neurological field. Computer-based methods are becoming essential for the accurate prediction and diagnosis of neurodegenerative disorders related to neurosecretory signaling. Changes in neurosecretory signaling reflect, to some extent, changes in the overall condition or function of the organism and provide key clues in the investigation of neurodegenerative disorders. For some specific neurosecretory signaling-related neurodegenerative disorders, the discovery of highly effective biomarkers may partially replace the current gold standard for partially invasive diagnosis and usher in a new era of non-invasive, or less invasive precision and individualized treatments. It will also be interesting to explore the specific mechanisms by which a neurosecretory signaling disorder leads to a neurodegenerative disorder. Our focus will be on studies that have a perspective of computational methods or data mining.

This Special Issue welcomes investigators to contribute original research and review articles related to computational methods and tools for the diagnosis, treatment, prognosis, and prevention of neurosecretory signaling-related biomarkers and neurodegenerative disorders.

Potential topics include but are not limited to the following:

1. Algorithms, methods, and tools for diagnosis, treatment, prognosis, and prevention of neurodegenerative disorders;
2. Machine learning or deep learning methods on dimensional reduction and feature selection for big noisy data in neurodegenerative disorders;
3. Bioinformatics methods for identifying disease mechanisms of neurodegenerative disorders;
4. Methods that integrate medical images and sequencing data in neurodegenerative disorders;
5. Drug repositioning and drug target prediction for neurodegenerative disorders;
6. Validation of results from computational studies of neurodegenerative disorders;
7. Clinical applications of computational studies in neurodegenerative disorders.

Dr. Yuzhen Xu

Guest Editor