Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions

Author:

Vatansever Sezen123ORCID,Schlessinger Avner45,Wacker Daniel456,Kaniskan H. Ümit457,Jin Jian457,Zhou Ming‐Ming47,Zhang Bin1234

Affiliation:

1. Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York New York USA

2. Mount Sinai Center for Transformative Disease Modeling Icahn School of Medicine at Mount Sinai New York New York USA

3. Icahn Institute for Data Science and Genomic Technology Icahn School of Medicine at Mount Sinai New York New York USA

4. Department of Pharmacological Sciences Icahn School of Medicine at Mount Sinai New York New York USA

5. Mount Sinai Center for Therapeutics Discovery Icahn School of Medicine at Mount Sinai New York New York USA

6. Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York USA

7. Department of Oncological Sciences, Tisch Cancer Institute Icahn School of Medicine at Mount Sinai New York New York USA

Publisher

Wiley

Subject

Drug Discovery,Pharmacology,Molecular Medicine

Reference468 articles.

1. Drug discovery and development: Role of basic biological research

2. Activity, assay and target data curation and quality in the ChEMBL database

3. The Human Genome Project, and recent advances in personalized genomics

4. Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research

5. Administration USFD. Artificial Intelligence and Machine Learning in Software as a Medical Device.https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-software-medical-device. Accessed October 26 2020.

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