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Parenclitic networks for predicting ovarian cancer
Harry J Whitwell
, Oleg Blyuss
, Usha Menon
, John F Timms
, Alexey Zaikin
School of Physics, Engineering & Computer Science
Research output
:
Contribution to journal
›
Article
›
peer-review
27
Citations (Scopus)
Overview
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Keyphrases
Ovarian Cancer
100%
Disease Classification
100%
Network Approach
100%
Parenclitic Network
100%
Ovarian Cancer Screening
50%
Personalized Medicine
50%
System Level
50%
Nested Sets
50%
Quantitative Proteomics
50%
Complex Disease Classification
50%
Assay Data
50%
Cancer Biology
50%
Network Topology
50%
United Kingdom
50%
Screening Assays
50%
Serological Assay
50%
Omics Technologies
50%
FGFBP1
50%
Single Network
50%
Logistic Regression Model
50%
Large Amount of Data
50%
Complex Disease
50%
Cancer Progression
50%
Synthetic Data
50%
Collaborative Trial
50%
Medicine and Dentistry
Nosology
100%
Ovarian Cancer
100%
Cancer Growth
33%
Disease
33%
Personalized Medicine
33%
Logistic Regression Analysis
33%
Biological Marker
33%
Ovarian Cancer Screening
33%
Tamsulosin
33%
Quantitative Proteomics
33%
Biochemistry, Genetics and Molecular Biology
Disease Classification
100%
Quantitative Proteomics
33%
Tamsulosin
33%
Solution and Solubility
33%
Cancer Screening
33%