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Phenotype Inference from Text and Genomic Data

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10536)

Abstract

We describe ProTraits, a machine learning pipeline that systematically annotates microbes with phenotypes using a large amount of textual data from scientific literature and other online resources, as well as genome sequencing data. Moreover, by relying on a multi-view non-negative matrix factorization approach, ProTraits pipeline is also able to discover novel phenotypic concepts from unstructured text. We present the main components of the developed pipeline and outline challenges for the application to other fields.

Keywords

Phenotypic trait Microbes Comparative genomics Late fusion Text mining Non-negative matrix factorization 

Notes

Acknowledgments

This work has been funded by the by the European Union FP7 grants ICT-2013-612944 (MAESTRA) and Croatian Science Foundation grants HRZZ-9623.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Ruđer Bošković InstituteZagrebCroatia
  2. 2.Mediterranean Institute of Life SciencesSplitCroatia
  3. 3.Centre for Genomic RegulationBarcelonaSpain

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