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DrugComboRanker: drug combination discovery based on target network analysis.

Bioinformatics (Oxford, England) | 2014

Currently there are no curative anticancer drugs, and drug resistance is often acquired after drug treatment. One of the reasons is that cancers are complex diseases, regulated by multiple signaling pathways and cross talks among the pathways. It is expected that drug combinations can reduce drug resistance and improve patients' outcomes. In clinical practice, the ideal and feasible drug combinations are combinations of existing Food and Drug Administration-approved drugs or bioactive compounds that are already used on patients or have entered clinical trials and passed safety tests. These drug combinations could directly be used on patients with less concern of toxic effects. However, there is so far no effective computational approach to search effective drug combinations from the enormous number of possibilities.

Pubmed ID: 24931988 RIS Download

Research resources used in this publication

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Associated grants

  • Agency: NCI NIH HHS, United States
    Id: U54 CA149196

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This is a list of tools and resources that we have found mentioned in this publication.


Biological General Repository for Interaction Datasets (BioGRID) (tool)

RRID:SCR_007393

Curated protein-protein and genetic interaction repository of raw protein and genetic interactions from major model organism species, with data compiled through comprehensive curation efforts.

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LINCS Connectivity Map (tool)

RRID:SCR_002639

A catalog of gene-expression data collected from human cells treated with chemical compounds and genetic reagents. Computational methods to reduce the number of necessary genomic measurements along with streamlined methodologies enable the current effort to significantly increase the size of the CMap database and along with it, our potential to connect human diseases with the genes that underlie them and the drugs that treat them. The NIH has funded a large expansion of the Connectivity Map dataset through the Library of Integrated Network-based Cellular Signatures (LINCS). The Broad Institute's LINCS center aims to create a first installment of data generation and analysis for the LINCS program. Through these data LINCS intends to accelerate the discovery process by systematically revealing connections between genes/compounds discovered in screens and molecular pathways that underlie disease states.

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MCF-7 (tool)

RRID:CVCL_0031

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HL-60 (tool)

RRID:CVCL_0002

Cell line HL-60 is a Cancer cell line with a species of origin Homo sapiens (Human)

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