Inferring Mechanism of Action of an Unknown Compound from Time Series Omics Data View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-08-24

AUTHORS

Akos Vertes , Albert-Baskar Arul , Peter Avar , Andrew R. Korte , Hang Li , Peter Nemes , Lida Parvin , Sylwia Stopka , Sunil Hwang , Ziad J. Sahab , Linwen Zhang , Deborah I. Bunin , Merrill Knapp , Andrew Poggio , Mark-Oliver Stehr , Carolyn L. Talcott , Brian M. Davis , Sean R. Dinn , Christine A. Morton , Christopher J. Sevinsky , Maria I. Zavodszky

ABSTRACT

Identifying the mechanism of action (MoA) of an unknown, possibly novel, substance (chemical, protein, or pathogen) is a significant challenge. Biologists typically spend years working out the MoA for known compounds. MoA determination is especially challenging if there is no prior knowledge and if there is an urgent need to understand the mechanism for rapid treatment and/or prevention of global health emergencies. In this paper, we describe a data analysis approach using Gaussian processes and machine learning techniques to infer components of the MoA of an unknown agent from time series transcriptomics, proteomics, and metabolomics data. The work was performed as part of the DARPA Rapid Threat Assessment program, where the challenge was to identify the MoA of a potential threat agent in 30 days or less, using only project generated data, with no recourse to pre-existing databases or published literature. More... »

PAGES

238-255

References to SciGraph publications

Book

TITLE

Computational Methods in Systems Biology

ISBN

978-3-319-99428-4
978-3-319-99429-1

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-99429-1_14

DOI

http://dx.doi.org/10.1007/978-3-319-99429-1_14

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106343445


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curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-99429-1_14'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-99429-1_14'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-99429-1_14'


 

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