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@ARTICLE{Jger:167176,
author = {N. Jäger$^*$},
title = {{B}ioinformatics workflows for clinical applications in
precision oncology.},
journal = {Seminars in cancer biology},
volume = {84},
issn = {1044-579X},
address = {London},
publisher = {Academic Press},
reportid = {DKFZ-2021-00167},
pages = {103-112},
year = {2022},
note = {#LA:B062# / 2022 Sep;84:103-112},
abstract = {High-throughput molecular profiling of tumors is a
fundamental aspect of precision oncology, enabling the
identification of genomic alterations that can be targeted
therapeutically. In this context, a patient is matched to a
specific drug or therapy based on the tumor's underlying
genetic driver events rather than the histologic
classification. This approach requires extensive
bioinformatics methodology and workflows, including raw
sequencing data processing and quality control, variant
calling and annotation, integration of different molecular
data types, visualization and finally reporting the data to
physicians, cancer researchers and pharmacologists in a
format that is readily interpretable for clinical decision
making. This review comprises a broad overview of these
bioinformatics aspects and discusses the multiple
analytical, technical and interpretational challenges that
remain to efficiently translate molecular findings into
personalized treatment recommendations.},
subtyp = {Review Article},
keywords = {Bioinformatics (Other) / Genomics (Other) / Precision
Oncology (Other) / clinical decision support (Other) /
somatic variants (Other)},
cin = {B062},
ddc = {610},
cid = {I:(DE-He78)B062-20160331},
pnm = {312 - Funktionelle und strukturelle Genomforschung
(POF4-312)},
pid = {G:(DE-HGF)POF4-312},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:33476720},
doi = {10.1016/j.semcancer.2020.12.020},
url = {https://inrepo02.dkfz.de/record/167176},
}