# Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/google-goes-cancer-improving-outcome-prediction-for-cancer-patients-by-network/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Christof Winter,Glen Kristiansen,Stephan Kersting,Janine Roy,Daniela E. Aust,Thomas Knösel,Petra Rümmele,Beatrix Jahnke,Vera Hentrich,Felix Rückert,Marco Niedergethmann,Wilko Weichert,Marcus Bahra,Hans J. Schlitt,Utz Settmacher,Helmut Frieß,Markus W. Büchler,Hans‐Detlev Saeger,Michael Schroeder,Christian Pilarsky,Robert Grützmann |
| Citations | 218 |
| DOI | 10.1371/journal.pcbi.1002511 |
| Fields | Biochemistry, Genetics and Molecular Biology,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1002511&type=printable |
| OpenAlex ID | https://openalex.org/W1965302838 |
| PMID | 22615549 |
| Type | article |
| Year | 2012 |

## Paper authors

- [Daniela E. Aust](https://scholariq.org/researchers/daniela-e-aust/)

## Paper primary topic

- [Pancreatic and Hepatic Oncology Research](https://scholariq.org/topics/pancreatic-and-hepatic-oncology-research/)

## Paper topics

- [Pancreatic and Hepatic Oncology Research](https://scholariq.org/topics/pancreatic-and-hepatic-oncology-research/)
- [Bioinformatics and Genomic Networks](https://scholariq.org/topics/bioinformatics-and-genomic-networks/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.