14799
2016
eng
8
1
8
article
1
2017-05-05
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Non-Coding RNAs in Lung Cancer: Contribution of Bioinformatics Analysis to the Development of Non-Invasive Diagnostic Tools
Lung cancer is currently the leading cause of cancer related mortality due to late diagnosis and limited treatment intervention. Non-coding RNAs are not translated into proteins and have emerged as fundamental regulators of gene expression. Recent studies reported that microRNAs and long non-coding RNAs are involved in lung cancer development and progression. Moreover, they appear as new promising non-invasive biomarkers for early lung cancer diagnosis. Here, we highlight their potential as biomarker in lung cancer and present how bioinformatics can contribute to the development of non-invasive diagnostic tools. For this, we discuss several bioinformatics algorithms and software tools for a comprehensive understanding and functional characterization of microRNAs and long non-coding RNAs.
Genes
10.3390/genes8010008
urn:nbn:de:bvb:20-opus-147990
Genes 2017, 8(1), 8; doi:10.3390/genes8010008
Fraunhofer Institute Interfacial Engineering and Biotechnology (IGB)
Meik Kunz
Beat Wolf
Harald Schulze
David Atlan
Thorsten Walles
Heike Walles
Thomas Dandekar
eng
uncontrolled
lung cancer
eng
uncontrolled
non-invasive biomarkers
eng
uncontrolled
miRNAs
eng
uncontrolled
lncRNAs
eng
uncontrolled
bioinformatics
eng
uncontrolled
early diagnosis
eng
uncontrolled
algorithm
Biowissenschaften; Biologie
open_access
Theodor-Boveri-Institut für Biowissenschaften
Lehrstuhl für Tissue Engineering und Regenerative Medizin
Institut für Experimentelle Biomedizin
Förderzeitraum 2016
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/14799/Kunz_genes-08-00008.pdf
14736
2016
eng
baw041
2016
article
1
2017-04-20
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The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development
The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure–activity relationships.
Database
10.1093/database/baw041
urn:nbn:de:bvb:20-opus-147369
Database (2016) Vol. 2016: article ID baw041; doi:10.1093/database/baw041
Meik Kunz
Chunguang Liang
Santosh Nilla
Alexander Cecil
Thomas Dandekar
eng
uncontrolled
drug-minded protein
eng
uncontrolled
database
Datenverarbeitung; Informatik
Biowissenschaften; Biologie
open_access
Theodor-Boveri-Institut für Biowissenschaften
Förderzeitraum 2016
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/14736/097_Dandekar_baw041.pdf