AIMC Topic: Drug Repositioning
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PISTON: Predicting drug indications and side effects using topic modeling and natural language processing.
Journal of biomedical informatics
Sep 27, 2018
The process of discovering novel drugs to treat diseases requires a long time and high cost. It is important to understand side effects of drugs as well as their therapeutic effects, because these can seriously damage the patients due to unexpected a...
Deep Learning in Drug Discovery and Medicine; Scratching the Surface.
Molecules (Basel, Switzerland)
Sep 18, 2018
The practice of medicine is ever evolving. Diagnosing disease, which is often the first step in a cure, has seen a sea change from the discerning hands of the neighborhood physician to the use of sophisticated machines to use of information gleaned f...
Drug Repurposing Using Deep Embeddings of Gene Expression Profiles.
Molecular pharmaceutics
Aug 7, 2018
Computational drug repositioning requires assessment of the functional similarities among compounds. Here, we report a new method for measuring compound functional similarity based on gene expression data. This approach takes advantage of deep neural...
Drug Repositioning for Schizophrenia and Depression/Anxiety Disorders: A Machine Learning Approach Leveraging Expression Data.
IEEE journal of biomedical and health informatics
Jul 16, 2018
Development of new medications is a lengthy and costly process, and drug repositioning might help to shorten the development cycle. We present a machine learning (ML) workflow to drug discovery or repositioning by predicting indication for a particul...
Cancer Drug Response Profile scan (CDRscan): A Deep Learning Model That Predicts Drug Effectiveness from Cancer Genomic Signature.
Scientific reports
Jun 11, 2018
In the era of precision medicine, cancer therapy can be tailored to an individual patient based on the genomic profile of a tumour. Despite the ever-increasing abundance of cancer genomic data, linking mutation profiles to drug efficacy remains a cha...
Exploiting semantic patterns over biomedical knowledge graphs for predicting treatment and causative relations.
Journal of biomedical informatics
May 12, 2018
BACKGROUND: Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches a...
Drug Repositioning by Integrating Known Disease-Gene and Drug-Target Associations in a Semi-supervised Learning Model.
Acta biotheoretica
Apr 26, 2018
Computational drug repositioning has been proven as a promising and efficient strategy for discovering new uses from existing drugs. To achieve this goal, a number of computational methods have been proposed, which are based on different data sources...
Multi-target drug repositioning by bipartite block-wise sparse multi-task learning.
BMC systems biology
Apr 24, 2018
BACKGROUND: Finding potential drug targets is a crucial step in drug discovery and development. Recently, resources such as the Library of Integrated Network-Based Cellular Signatures (LINCS) L1000 database provide gene expression profiles induced by...
Drug repositioning for prostate cancer: using a data-driven approach to gain new insights.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Apr 16, 2018
UNLABELLED: Prostate cancer (PC) is the most common cancer and the third leading cause of cancer death in men worldwide. Despite its high incidence and mortality, the likelihood of a cure is low for late-stages of PC. There is an unmet need for more ...
A systematic and prospectively validated approach for identifying synergistic drug combinations against malaria.
Malaria journal
Apr 11, 2018
BACKGROUND: Nearly half of the world's population (3.2 billion people) were at risk of malaria in 2015, and resistance to current therapies is a major concern. While the standard of care includes drug combinations, there is a pressing need to identif...
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