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Title:A simple in silico approach to generate gene-expression profiles from subsets of cancer genomics data
Authors:ID Khurshed, Mohammed (Author)
ID Molenaar, Remco J. (Author)
ID Noorden, Cornelis J. F. van (Author)
Files:.pdf PDF - Presentation file, download (2,04 MB)
MD5: 269A8E27D0E5EF5B7D033CFA1F7B7D63
 
URL URL - Source URL, visit https://doi.org/10.2144/btn-2018-0179
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo NIB - National Institute of Biology
Abstract:In biomedical research, large-scale profiling of gene expression has become routine and offers a valuable means to evaluate changes in onset and progression of diseases, in particular cancer. An overwhelming amount of cancer genomics data has become publicly available, and the complexity of these data makes it a challenge to perform in silico data exploration, integration and analysis, in particular for scientists lacking a background in computational programming or informatics. Many web interface tools make these large datasets accessible but are limited to process large datasets. To accelerate the translation of genomic data into new insights, we provide a simple method to explore and select data from cancer genomic datasets to generate gene-expression profiles of subsets that are of specific genetic, biological or clinical interest.
Keywords:cancer genomics, cBioPortal, data mining, epigenetics, gene expression, in silico
Publication status:Published
Publication version:Version of Record
Publication date:23.11.2019
Year of publishing:2019
Number of pages:str. 172-176
Numbering:Vol. 67, no. 4
PID:20.500.12556/DiRROS-19596 New window
UDC:577.2
ISSN on article:0736-6205
DOI:10.2144/btn-2018-0179 New window
COBISS.SI-ID:5289039 New window
Publication date in DiRROS:24.07.2024
Views:386
Downloads:558
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Record is a part of a journal

Title:Biotechniques
Shortened title:BioTechniques
Publisher:Eaton Pub. Co.
ISSN:0736-6205
COBISS.SI-ID:27332096 New window

Document is financed by a project

Funder:Other - Other funder or multiple funders
Funding programme:Dutch Cancer Society
Project number:UVA 2014-6839 and AMC 2016.1-10460

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.

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