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Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities.

Publication ,  Journal Article
Dhami, DS; Kunapuli, G; Das, M; Page, D; Natarajan, S
Published in: Smart Health (Amst)
December 2018

We develop a pipeline to mine complex drug interactions by combining different similarities and interaction types (molecular, structural, phenotypic, genomic etc). Our goal is to learn an optimal kernel from these heterogeneous similarities in a supervised manner. We formulate an extensible framework that can easily integrate new interaction types into a rich model. The core of our pipeline features a novel kernel-learning approach that tunes the weights of the heterogeneous similarities, and fuses them into a Similarity-based Kernel for Identifying Drug-Drug interactions and Discovery, or SKID3. Experimental evaluation on the DrugBank database shows that SKID3 effectively combines similarities generated from chemical reaction pathways (which generally improve precision) and molecular and structural fingerprints (which generally improve recall) into a single kernel that gets the best of both worlds, and consequently demonstrates the best performance.

Duke Scholars

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Published In

Smart Health (Amst)

DOI

ISSN

2352-6483

Publication Date

December 2018

Volume

9-10

Start / End Page

88 / 100

Location

Netherlands

Related Subject Headings

  • 46 Information and computing sciences
  • 42 Health sciences
  • 40 Engineering
 

Citation

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Dhami, D. S., Kunapuli, G., Das, M., Page, D., & Natarajan, S. (2018). Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities. Smart Health (Amst), 910, 88–100. https://doi.org/10.1016/j.smhl.2018.07.007
Dhami, Devendra Singh, Gautam Kunapuli, Mayukh Das, David Page, and Sriraam Natarajan. “Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities.Smart Health (Amst) 9–10 (December 2018): 88–100. https://doi.org/10.1016/j.smhl.2018.07.007.
Dhami DS, Kunapuli G, Das M, Page D, Natarajan S. Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities. Smart Health (Amst). 2018 Dec;9–10:88–100.
Dhami, Devendra Singh, et al. “Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities.Smart Health (Amst), vol. 9–10, Dec. 2018, pp. 88–100. Pubmed, doi:10.1016/j.smhl.2018.07.007.
Dhami DS, Kunapuli G, Das M, Page D, Natarajan S. Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities. Smart Health (Amst). 2018 Dec;9–10:88–100.
Journal cover image

Published In

Smart Health (Amst)

DOI

ISSN

2352-6483

Publication Date

December 2018

Volume

9-10

Start / End Page

88 / 100

Location

Netherlands

Related Subject Headings

  • 46 Information and computing sciences
  • 42 Health sciences
  • 40 Engineering