Neurodegenerative disorders, such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and Amyotrophic lateral sclerosis (ALS), are formidable clinical illnesses whose diagnosis, treatment, and prognosis are complex. As a result, no effective treatment for AD has been found so far. There is plenty of evidence to suggest that computational methods, especially those 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. Accurate prediction and diagnosis is a pivotal goal to prevent the onset of neurodegenerative diseases. With the assistance of biomarkers identified by computational methods, neurologists are able to diagnose the disease at its early stage. Based on next-generation sequencing (NGS) technologies, the risk gene loci and proteins can be detected. Accompanied by Magnetic Resonance Imaging (MRI) technology, clinicians can improve or assure their diagnosis and classification of neurodegenerative disorders. Furthermore, appropriate bioinformatics tools can help biologists to explore the aetiology of neurodegenerative diseases, which may shed light on the underlying mechanisms of brain impairment. In addition, some biomarkers can be utilized to promote drug repurposing as well as de novo drug design. Finally, wet-lab experiments can also be developed that are compatible with computational methods for further validation.

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

Potential topics include but are not limited to the following:

• Algorithms, methods, and tools for diagnosis, treatment, prognosis, and prevention of neurodegenerative disorders
• Machine learning or deep learning methods on dimensional reduction and feature selection for big noisy data in neurodegenerative disorders
• Bioinformatics methods in identifying disease mechanisms of neurodegenerative disorders
• Methods integrating medical images and sequencing data in neurodegenerative disorders
• Drug repositioning and drug target prediction for neurodegenerative disorders
• Validation of results from computational studies by wet-lab experiments
• Clinical applications of computational studies in neurodegenerative disorders