Cancer Bioinformatics: Bioinformatic Methods, Network Biomarkers and Precision Medicine

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. Topics include: Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation; Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer; A molecular computational model improves the preoperative diagnosis of thyroid nodules; A systems biology approach to the global analysis of transcription factors in colorectal cancer; Cancer bioinformatics: A new approach to systems clinical medicine; A unified computational model for revealing and predicting subtle subtypes of cancers; Prognostic gene signatures for patient stratification in breast cancer - accuracy, stability and interpretability of gene selection approaches using prior knowledge on protein-protein interactions; A new analysis approach of epidermal growth factor receptor pathway activation patterns provides insights into cetuximab resistance mechanisms in head and neck cancer; Gene regulatory network inference: evaluation and application to ovarian cancer allows the prioritization of drug targets; Gene expression signatures modulated by epidermal growth factor receptor activation and their relationship to cetuximab resistance in head and neck squamous cell carcinoma; A dynamic model for tumour growth and metastasis formation; Synthetic Lethal Screen Identifies NF-kappaB as a Target for Combination Therapy with Topotecan for patients with Neuroblastoma. Proceeds from the sale of this book go to the support of an elderly disabled person.