Some Aspects of Analysis of Gene Array Data

2002 ◽  
pp. 71-89 ◽  
Author(s):  
Borko D. Jovanovic ◽  
Raymond C. Bergan ◽  
Warren A. Kibbe
Keyword(s):  
Gene Array ◽  
Array Data

scholarly journals Validation of RNAi Silencing Efficiency Using Gene Array Data shows 18.5% Failure Rate across 429 Independent Experiments

2016 ◽  
Vol 5 ◽  
pp. e366 ◽  
Author(s):  
Gyöngyi Munkácsy ◽  
Zsófia Sztupinszki ◽  
Péter Herman ◽  
Bence Bán ◽  
Zsófia Pénzváltó ◽  
...  
Keyword(s):  
Failure Rate ◽  
Gene Array ◽  
Array Data ◽  
Rnai Silencing

Abstract 1522: Predicting drug sensitivity based on gene array data for cytotoxic chemotherapeutic agents

2016 ◽  
Author(s):  
Joshua Mannheimer ◽  
Jared S. Fowles ◽  
Katherine Shaumberg ◽  
Dawn L. Duval ◽  
Ashok Prasad ◽  
...  
Keyword(s):  
Drug Sensitivity ◽  
Gene Array ◽  
Chemotherapeutic Agents ◽  
Array Data

scholarly journals Array data extractor (ADE): a LabVIEW program to extract and merge gene array data

2013 ◽  
Vol 6 (1) ◽  
Author(s):  
Stefan Kurtenbach ◽  
Sarah Kurtenbach ◽  
Georg Zoidl
Keyword(s):  
Gene Array ◽  
Array Data ◽  
Labview Program

896: Artificial Intelligence Re-Analysis of Gene Array Data Identifies Novel Markers of Urothelial Cancer Progression

2007 ◽  
Vol 177 (4S) ◽  
pp. 297-298
Author(s):  
James W. Catto ◽  
Maysam F. Abbod ◽  
Derek Linkens ◽  
Peter J. Wild ◽  
Alexander Herr ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Cancer Progression ◽  
Urothelial Cancer ◽  
Gene Array ◽  
Array Data

Bioinformatic analysis of primary endothelial cell gene array data illustrated by the analysis of transcriptome changes in endothelial cells exposed to VEGF-A and PlGF

Angiogenesis ◽  
2004 ◽  
Vol 7 (2) ◽  
pp. 143-156 ◽  
Author(s):  
Jonathan Schoenfeld ◽  
Khashayar Lessan ◽  
Nicola Johnson ◽  
D. Charnock-jones ◽  
Amanda Evans ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Endothelial Cell ◽  
Gene Array ◽  
Bioinformatic Analysis ◽  
Array Data ◽  
Cell Gene

2096 ORAL Lapatinib (L) plus Capecitabine (C) in HER2+ advanced breast cancer (ABC): report of updated efficacy and gene-array data

2007 ◽  
Vol 5 (4) ◽  
pp. 212
Author(s):  
J. Crown ◽  
D. Cameron ◽  
A.M. Martin ◽  
B. Newstat ◽  
T. Pienkowski ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Advanced Breast Cancer ◽  
Gene Array ◽  
Advanced Breast ◽  
Array Data

scholarly journals A systematic review of large scale and heterogeneous gene array data in heart failure

2005 ◽  
Vol 38 (3) ◽  
pp. 425-432 ◽  
Author(s):  
Umesh C. Sharma ◽  
Saraswati Pokharel ◽  
Chris T.A. Evelo ◽  
Jos G. Maessen
Keyword(s):  
Heart Failure ◽  
Systematic Review ◽  
Large Scale ◽  
Gene Array ◽  
Array Data

scholarly journals Correlation of Dynamic PET and Gene Array Data in Patients with Gastrointestinal Stromal Tumors

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Ludwig G. Strauss ◽  
Antonia Dimitrakopoulou-Strauss ◽  
Dirk Koczan ◽  
Leyun Pan ◽  
Peter Hohenberger
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Gastrointestinal Stromal Tumors ◽  
Gene Array ◽  
Tracer Uptake ◽  
Cell Cycle Gene ◽  
Dynamic Pet ◽  
Expression Data ◽  
Array Data ◽  
Stromal Tumors

Introduction. The results obtained with dynamic PET (dPET) were compared to gene expression data obtained in patients with gastrointestinal stromal tumors (GIST). The primary aim was to assess the association of the dPET results and gene expression data.Material and Methods. dPET was performed following the injection of F-18-fluorodeoxyglucose (FDG) in 22 patients with GIST. All patients were examined prior to surgery for staging purpose. Compartment and noncompartment models were used for the quantitative evaluation of the dPET examinations. Gene array data were based on tumor specimen obtained by surgery after the PET examinations.Results. The data analysis revealed significant correlations for the dPET parameters and the expression of zinc finger genes (znf43, znf85, znf91, znf189). Furthermore, the transport of FDG (k1) was associated with VEGF-A. The cell cycle gene cyclin-dependent kinase inhibitor 1C was correlated with the maximum tracer uptake (SUVmax) in the tumors.Conclusions. The data demonstrate a dependency of the tracer kinetics on genes associated with prognosis in GIST. Furthermore, angiogenesis and cell proliferation have an impact on the tracer uptake.

Sign in / Sign up

Export Citation Format

Share Document