التفاصيل البيبلوغرافية
| العنوان: |
A computational method for drug repositioning using publicly available gene expression data |
| المؤلفون: |
Shabana, KM, Abdul Nazeer, KA, Pradhan, Meeta, Palakal, Mathew |
| بيانات النشر: |
BioMed Central Ltd. |
| سنة النشر: |
2015 |
| المجموعة: |
BioMed Central |
| مصطلحات موضوعية: |
drug repositioning, computational drug discovery, gene expression data |
| الوصف: |
Motivation The identification of new therapeutic uses of existing drugs, or drug repositioning, offers the possibility of faster drug development, reduced risk, lesser cost and shorter paths to approval. The advent of high throughput microarray technology has enabled comprehensive monitoring of transcriptional response associated with various disease states and drug treatments. This data can be used to characterize disease and drug effects and thereby give a measure of the association between a given drug and a disease. Several computational methods have been proposed in the literature that make use of publicly available transcriptional data to reposition drugs against diseases. Method In this work, we carry out a data mining process using publicly available gene expression data sets associated with a few diseases and drugs, to identify the existing drugs that can be used to treat genes causing lung cancer and breast cancer. Results Three strong candidates for repurposing have been identified- Letrozole and GDC-0941 against lung cancer, and Ribavirin against breast cancer. Letrozole and GDC-0941 are drugs currently used in breast cancer treatment and Ribavirin is used in the treatment of Hepatitis C. |
| نوع الوثيقة: |
report |
| اللغة: |
English |
| العلاقة: |
http://www.biomedcentral.com/1471-21-5/16/S17/S5Test |
| الإتاحة: |
http://www.biomedcentral.com/1471-21-5/16/S17/S5Test |
| حقوق: |
Copyright 2015 Shabana et al. |
| رقم الانضمام: |
edsbas.88E89E6B |
| قاعدة البيانات: |
BASE |
