Pregled bibliografske jedinice broj: 909761
Phenotype Inference from Text and Genomic Data
Phenotype Inference from Text and Genomic Data // ECML-PKDD 2017, Lecture Notes in Computer Science / Altun, Yasemin ; Das, Kamalika ; et al. (ur.).
Skopje, Makedonija: Springer International Publishing, 2017. str. 373-377 doi:10.1007/978-3-319-71273-4_34 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 909761 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Phenotype Inference from Text and Genomic Data
Autori
Brbić, Maria ; Piškorec, Matija ; Vidulin, Vedrana ; Kriško, Anita ; Šmuc, Tomislav ; Supek, Fran
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
ECML-PKDD 2017, Lecture Notes in Computer Science
/ Altun, Yasemin ; Das, Kamalika ; et al. - : Springer International Publishing, 2017, 373-377
ISBN
978-3-319-71273-4
Skup
Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD)
Mjesto i datum
Skopje, Makedonija, 18-22.09.2017
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
phenotypic trait ; microbes ; comparative genomics ; late fusion ; text mining ; non-negative matrix factorization
Sažetak
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.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Institut "Ruđer Bošković", Zagreb
Profili:
Fran Supek
(autor)
Maria Brbić
(autor)
Tomislav Šmuc
(autor)
Anita Kriško
(autor)
Matija Piškorec
(autor)