Cancer bioinformatics: bioinformatic methods, network biomarkers and precision medicine
Edited by:
Xiangdong WANG
Collection published: 1 May 2012
Last updated: 26 November 2012
The "Cancer bioinformatics" thematic series focuses on the latest developments in the emerging field of systems clinical medicine in cancer which integrates systems biology, clinical science, omics-based technology, bioinformatics and computational science to improve diagnosis, therapies and prognosis of cancer.
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Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation
Abel Gonzalez-Perez, Jordi Deu-Pons, Nuria Lopez-Bigas Genome Medicine 2012, 4:89 (26 November 2012)
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| PubMed | Cited on BioMed Central
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Editor’s summary
Cancer genome projects need to identify cancer-causing variants; a new method improves the assessment of the functional impact of SNVs by including the baseline tolerance of genes to mutations.
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Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer
Scott Doyle, Michael D Feldman, Natalie Shih, John Tomaszewski, Anant Madabhushi BMC Bioinformatics 2012, 13:282 (30 October 2012)
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A molecular computational model improves the preoperative diagnosis of thyroid nodules
Sara Tomei, Ivo Marchetti, Katia Zavaglia, Francesca Lessi, Alessandro Apollo, Paolo Aretini, Giancarlo Di Coscio, Generoso Bevilacqua, Chiara Mazzanti BMC Cancer 2012, 12:396 (7 September 2012)
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Editor’s summary
A molecular computational model based on the expression of 8 genes can preoperatively distinguish benign from malignant thyroid lesions and could help identify patients with thyroid nodules who do not require radical surgery.
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A systems biology approach to the global analysis of transcription factors in colorectal cancer
Meeta P Pradhan, Nagendra KA Prasad, Mathew J Palakal BMC Cancer 2012, 12:331 (1 August 2012)
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| PubMed | Cited on BioMed Central
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Cancer bioinformatics: A new approach to systems clinical medicine
Duojiao Wu, Catherine M Rice, Xiangdong Wang BMC Bioinformatics 2012, 13:71 (1 May 2012)
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A unified computational model for revealing and predicting subtle subtypes of cancers
Xianwen Ren, Yong Wang, Jiguang Wang, Xiang-Sun Zhang BMC Bioinformatics 2012, 13:70 (1 May 2012)
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Prognostic gene signatures for patient stratification in breast cancer - accuracy, stability and interpretability of gene selection approaches using prior knowledge on protein-protein interactions
Yupeng Cun, Holger Fröhlich BMC Bioinformatics 2012, 13:69 (1 May 2012)
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A new analysis approach of epidermal growth factor receptor pathway activation patterns provides insights into cetuximab resistance mechanisms in head and neck cancer
Silvia von der Heyde, Tim Beissbarth BMC Medicine 2012, 10:43 (1 May 2012)
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Editor’s summary
A new method published in BMC Genomics identifies gene expression changes downstream of EGFR; von der Heyde and Beissbarth comment on the importance of this method to identify changes associated with cetuximab resistance in head and neck cancer.
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Gene regulatory network inference: evaluation and application to ovarian cancer allows the prioritization of drug targets
Piyush B Madhamshettiwar, Stefan R Maetschke, Melissa J Davis, Antonio Reverter, Mark A Ragan Genome Medicine 2012, 4:41 (1 May 2012)
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Gene expression signatures modulated by epidermal growth factor receptor activation and their relationship to cetuximab resistance in head and neck squamous cell carcinoma
Elana J Fertig, Qing Ren, Haixia Cheng, Hiromitsu Hatakeyama, Adam P Dicker, Ulrich Rodeck, Michael Considine, Michael F Ochs, Christine H Chung BMC Genomics 2012, 13:160 (1 May 2012)
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| PubMed | Cited on BioMed Central
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A dynamic model for tumour growth and metastasis formation
Volker Haustein, Udo Schumacher Journal of Clinical Bioinformatics 2012, 2:11 (1 May 2012)
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Synthetic Lethal Screen Identifies NF-κB as a Target for Combination Therapy with Topotecan for patients with Neuroblastoma
Patricia S Tsang, Adam T Cheuk, Qing-Rong Chen, Young K Song, Thomas C Badgett, Jun S Wei, Javed Khan BMC Cancer 2012, 12:101 (21 March 2012)
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Editor’s summary
A novel combination chemotherapy to improve survival rate in patients with neuroblastoma can be identified using a siRNA library-based synthetic lethal screen, suggesting that this approach may help selecting drugs for use in multimodal treatments.
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