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  2. School of Engineering
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  4. Publikationen School of Engineering
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dc.contributor.authorSmith, Ellery-
dc.contributor.authorPaloots, Rahel-
dc.contributor.authorGiagkos, Dimitris-
dc.contributor.authorBaudis, Michael-
dc.contributor.authorStockinger, Kurt-
dc.date.accessioned2024-03-22T10:48:57Z-
dc.date.available2024-03-22T10:48:57Z-
dc.date.issued2024-03-
dc.identifier.issn2635-0041de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/30347-
dc.description.abstractWith the proliferation of research means and computational methodologies, published biomedical literature is growing exponentially in numbers and volume. Cancer cell lines are frequently-used models in biological and medical research that are currently applied for a wide range of purposes, from studies of cellular mechanisms to drug development, which has led to a wealth of related data and publications. Sifting through large quantities of text to gather relevant information on cell lines of interest is tedious and extremely slow when performed by humans. Hence, novel computational information extraction and correlation mechanisms are required to boost meaningful knowledge extraction. In this work, we present the design, implementation and application of a novel data extraction and exploration system. This system extracts deep semantic relations between textual entities from scientific literature to enrich existing structured clinical data concerning cancer cell lines. We introduce a new public data exploration portal, which enables automatic linking of genomic copy number variants plots with ranked, related entities such as affected genes. Each relation is accompanied by literature-derived evidences, allowing for deep, yet rapid, literature search, using existing structured data as a springboard.de_CH
dc.language.isoende_CH
dc.publisherOxford University Pressde_CH
dc.relation.ispartofBioinformatics Advancesde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectCancer cell linede_CH
dc.subjectCopy number variantde_CH
dc.subjectInformation extractionde_CH
dc.subjectNatural language processingde_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleData-driven information extraction and enrichment of molecular profiling data for cancer cell linesde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.1093/bioadv/vbae045de_CH
zhaw.funding.euinfo:eu-repo/grantAgreement/EC/H2020/863410//INODE - Intelligent Open Data Exploration/INODEde_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statusacceptedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedIntelligent Information Systemsde_CH
zhaw.funding.zhawINODE – Intelligent Open Data Exploration (EU Horizon 2020)de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
zhaw.relation.referenceshttps://github.com/progenetix/cancercelllines-webde_CH
Appears in collections:Publikationen School of Engineering

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Smith, E., Paloots, R., Giagkos, D., Baudis, M., & Stockinger, K. (2024). Data-driven information extraction and enrichment of molecular profiling data for cancer cell lines. Bioinformatics Advances. https://doi.org/10.1093/bioadv/vbae045
Smith, E. et al. (2024) ‘Data-driven information extraction and enrichment of molecular profiling data for cancer cell lines’, Bioinformatics Advances [Preprint]. Available at: https://doi.org/10.1093/bioadv/vbae045.
E. Smith, R. Paloots, D. Giagkos, M. Baudis, and K. Stockinger, “Data-driven information extraction and enrichment of molecular profiling data for cancer cell lines,” Bioinformatics Advances, Mar. 2024, doi: 10.1093/bioadv/vbae045.
SMITH, Ellery, Rahel PALOOTS, Dimitris GIAGKOS, Michael BAUDIS und Kurt STOCKINGER, 2024. Data-driven information extraction and enrichment of molecular profiling data for cancer cell lines. Bioinformatics Advances. März 2024. DOI 10.1093/bioadv/vbae045
Smith, Ellery, Rahel Paloots, Dimitris Giagkos, Michael Baudis, and Kurt Stockinger. 2024. “Data-Driven Information Extraction and Enrichment of Molecular Profiling Data for Cancer Cell Lines.” Bioinformatics Advances, March. https://doi.org/10.1093/bioadv/vbae045.
Smith, Ellery, et al. “Data-Driven Information Extraction and Enrichment of Molecular Profiling Data for Cancer Cell Lines.” Bioinformatics Advances, Mar. 2024, https://doi.org/10.1093/bioadv/vbae045.


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