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izvor podataka: crosbi

Phenotype Inference from Text and Genomic Data (CROSBI ID 655790)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Brbić, Maria ; Piškorec, Matija ; Vidulin, Vedrana ; Kriško, Anita ; Šmuc, Tomislav ; Supek, Fran Phenotype Inference from Text and Genomic Data // ECML-PKDD 2017, Lecture Notes in Computer Science / Altun, Yasemin ; Das, Kamalika ; et al. (ur.). Springer, 2017. str. 373-377 doi: 10.1007/978-3-319-71273-4_34

Podaci o odgovornosti

Brbić, Maria ; Piškorec, Matija ; Vidulin, Vedrana ; Kriško, Anita ; Šmuc, Tomislav ; Supek, Fran

engleski

Phenotype Inference from Text and Genomic Data

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 nonnegative 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.

phenotypic trait ; microbes ; comparative genomics ; late fusion ; text mining ; non-negative matrix factorization

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Podaci o prilogu

373-377.

2017.

objavljeno

10.1007/978-3-319-71273-4_34

Podaci o matičnoj publikaciji

ECML-PKDD 2017, Lecture Notes in Computer Science

Altun, Yasemin ; Das, Kamalika ; et al.

Springer

978-3-319-71273-4

Podaci o skupu

Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD)

predavanje

18.09.2017-22.09.2017

Skopje, Sjeverna Makedonija

Povezanost rada

Računarstvo

Poveznice