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Practical aspects of NGS-based pathways analysis for personalized cancer science and medicineIntegrating next-generation sequencing into clinical oncology: strategies, promises and pitfallsData Sharing, Clinical Trials, and Biomarkers in Precision Oncology: Challenges, Opportunities, and Programs at the Department of Veterans AffairsNovel targeted therapies in chordoma: an update.Bioinformatic approaches to augment study of epithelial-to-mesenchymal transition in lung cancerVariant interpretation through Bayesian fusion of frequency and genomic knowledgeHow Will Big Data Improve Clinical and Basic Research in Radiation Therapy?Toward rapid learning in cancer treatment selection: An analytical engine for practice-based clinical dataLnc-CC3 increases metastasis in cervical cancer by increasing Slug expressionImproving Cancer Treatment via Mathematical Modeling: Surmounting the Challenges Is Worth the EffortOpportunities for translational epidemiology: the important role of observational studies to advance precision oncology.The VA Point-of-Care Precision Oncology Program: Balancing Access with Rapid Learning in Molecular Cancer Medicine.Public Health Platforms: An Emerging Informatics Approach to Health Professional Learning and Development.Jumonji domain-containing protein 1A promotes cell growth and progression via transactivation of c-Myc expression and predicts a poor prognosis in cervical cancer.TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.Reinforcement learning improves behaviour from evaluative feedback.Methods: for studying pharmacogenetic profiles of combination chemotherapeutic drugs.Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer.Long and short noncoding RNAs in lung cancer precision medicine: Opportunities and challenges.AACR Project GENIE: Powering Precision Medicine through an International Consortium.Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives.In silico polypharmacology of natural products.High performance of targeted next generation sequencing on variance detection in clinical tumor specimens in comparison with current conventional methods.Global connectivity of hub residues in Oncoprotein structures encodes genetic factors dictating personalized drug response to targeted Cancer therapy.Nonlinear mixed effects dose response modeling in high throughput drug screens: application to melanoma cell line analysis.Radiogenomics: Identification of Genomic Predictors for Radiation Toxicity.[Toward dynamic informed consent].Tissue-Specific Signaling Networks Rewired by Major Somatic Mutations in Human Cancer Revealed by Proteome-Wide Discovery.Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes.Analytical Validation and Capabilities of the Epic CTC Platform: Enrichment-Free Circulating Tumour Cell Detection and Characterization.Prototyping a precision oncology 3.0 rapid learning platform
P2860
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P2860
description
article científic
@ca
article scientifique
@fr
articol științific
@ro
articolo scientifico
@it
artigo científico
@gl
artigo científico
@pt
artigo científico
@pt-br
artikel ilmiah
@id
artikull shkencor
@sq
artículo científico
@es
name
Rapid learning for precision oncology.
@en
type
label
Rapid learning for precision oncology.
@en
prefLabel
Rapid learning for precision oncology.
@en
P2860
P1476
Rapid learning for precision oncology.
@en
P2093
Jay M Tenenbaum
Jeff Shrager
P2860
P304
P356
10.1038/NRCLINONC.2013.244
P407
P577
2014-01-21T00:00:00Z