Novel therapeutics for complex diseases from genome-wide association data
Contribuinte(s) |
Wouters, Merridee Crowley Tamsyn Sherman, Craig |
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Data(s) |
01/10/2016
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Resumo |
The development of novel therapies is essential to lower the burden of complex diseases. The purpose of this study is to identify novel therapeutics for complex diseases using bioinformatic methods. Bioinformatic tools such as candidate gene prediction tools allow identification of disease genes by identifying the potential candidate genes linked to genetic markers of the disease. Candidate gene prediction tools can only identify candidates for further research, and do not identify disease genes directly. Integration of drug-target datasets with candidate gene data-sets can identify novel potential therapeutics suitable for repositioning in clinical trials. Drug repositioning can save valuable time and money spent in therapeutic development of complex diseases. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Deakin University, Faculty of Health, School of Medicine |
Relação |
http://dro.deakin.edu.au/eserv/DU:30089382/grover-agreement-2016.pdf http://dro.deakin.edu.au/eserv/DU:30089382/grover-noveltherapeutics-2016A.pdf |
Direitos |
The Author. All Rights Reserved |
Palavras-Chave | #Genetics #pharmacology #Therapeutic drugs #Diseases #Gene therapy #Databases |
Tipo |
Thesis |