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Data on metabolomic profiling of ovarian cancer patients' serum for potential diagnostic biomarkers
The data presented here are related to the research paper entitled “Metabolomic profiling suggests long chain ceramides and sphingomyelins as a possible diagnostic biomarker of epithelial ovarian cancer.” (Kozar et al., 2018) [1]. Metabolomic profiling was performed on 15 patients with ovarian cance...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998211/ https://www.ncbi.nlm.nih.gov/pubmed/29904684 http://dx.doi.org/10.1016/j.dib.2018.04.081 |
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author | Kozar, Nejc Kruusmaa, Kristi Bitenc, Marko Argamasilla, Rosa Adsuar, Antonio Goswami, Nandu Arko, Darja Takač, Iztok |
author_facet | Kozar, Nejc Kruusmaa, Kristi Bitenc, Marko Argamasilla, Rosa Adsuar, Antonio Goswami, Nandu Arko, Darja Takač, Iztok |
author_sort | Kozar, Nejc |
collection | PubMed |
description | The data presented here are related to the research paper entitled “Metabolomic profiling suggests long chain ceramides and sphingomyelins as a possible diagnostic biomarker of epithelial ovarian cancer.” (Kozar et al., 2018) [1]. Metabolomic profiling was performed on 15 patients with ovarian cancer, 21 healthy controls and 21 patients with benign gynecological conditions. HPLC-TQ/MS was performed on all samples. PLS-DA was used for the first line classification of epithelial ovarian cancer and healthy control group based on metabolomic profiles. Random forest algorithm was used for building a prediction model based over most significant markers. Univariate analysis was performed on individual markers to determine their distinctive roles. Furthermore, markers were also evaluated for their biological significance in cancer progression. |
format | Online Article Text |
id | pubmed-5998211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-59982112018-06-14 Data on metabolomic profiling of ovarian cancer patients' serum for potential diagnostic biomarkers Kozar, Nejc Kruusmaa, Kristi Bitenc, Marko Argamasilla, Rosa Adsuar, Antonio Goswami, Nandu Arko, Darja Takač, Iztok Data Brief Proteomics and Biochemistry The data presented here are related to the research paper entitled “Metabolomic profiling suggests long chain ceramides and sphingomyelins as a possible diagnostic biomarker of epithelial ovarian cancer.” (Kozar et al., 2018) [1]. Metabolomic profiling was performed on 15 patients with ovarian cancer, 21 healthy controls and 21 patients with benign gynecological conditions. HPLC-TQ/MS was performed on all samples. PLS-DA was used for the first line classification of epithelial ovarian cancer and healthy control group based on metabolomic profiles. Random forest algorithm was used for building a prediction model based over most significant markers. Univariate analysis was performed on individual markers to determine their distinctive roles. Furthermore, markers were also evaluated for their biological significance in cancer progression. Elsevier 2018-04-30 /pmc/articles/PMC5998211/ /pubmed/29904684 http://dx.doi.org/10.1016/j.dib.2018.04.081 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Proteomics and Biochemistry Kozar, Nejc Kruusmaa, Kristi Bitenc, Marko Argamasilla, Rosa Adsuar, Antonio Goswami, Nandu Arko, Darja Takač, Iztok Data on metabolomic profiling of ovarian cancer patients' serum for potential diagnostic biomarkers |
title | Data on metabolomic profiling of ovarian cancer patients' serum for potential diagnostic biomarkers |
title_full | Data on metabolomic profiling of ovarian cancer patients' serum for potential diagnostic biomarkers |
title_fullStr | Data on metabolomic profiling of ovarian cancer patients' serum for potential diagnostic biomarkers |
title_full_unstemmed | Data on metabolomic profiling of ovarian cancer patients' serum for potential diagnostic biomarkers |
title_short | Data on metabolomic profiling of ovarian cancer patients' serum for potential diagnostic biomarkers |
title_sort | data on metabolomic profiling of ovarian cancer patients' serum for potential diagnostic biomarkers |
topic | Proteomics and Biochemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998211/ https://www.ncbi.nlm.nih.gov/pubmed/29904684 http://dx.doi.org/10.1016/j.dib.2018.04.081 |
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