Some studies have shown that efficacious drug combination can increase the therapeutic effect, and decrease drug toxicity and side-effects. Thus, drug combinations have been widely used in the treatment of complex diseases, especially cancer. However, experiment-based methods are extremely costly in time and money. Computational models can greatly reduce the cost, but most of the models do not use the data of more than two drugs and lose a lot of useful information. Here, we used high-order drug combination information and developed a hypergraph random walk with restart model (HRWR) for efficacious drug combination prediction. As a result, compared with the other methods by leave-one-out cross-validation (LOOCV), the Area Under Receiver Operating Characteristic Curve (AUROC) of the HRWR algorithm were higher than others. Moreover, the case studies of lung cancer, breast cancer, and colorectal cancer showed that HRWR had a powerful ability to predict potential efficacious combinations, which provides new prospects for cancer treatment. The code and dataset of HRWR are freely available at https://github.com/wangqi27/HRWR.
- Downloaded 93 times
- Download rankings, all-time:
- Site-wide: 138,103
- In bioinformatics: 10,690
- Year to date:
- Site-wide: 92,762
- Since beginning of last month:
- Site-wide: 72,763
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!