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Decoding global gene expression programs in liver cancer by noninvasive imaging.

Decoding global gene expression programs in liver cancer by noninvasive imaging.

http://www.wikidata.org/entity/Q34630291

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DART: Denoising Algorithm based on Relevance network Topology improves molecular pathway activity inference Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach Radiomics: extracting more information from medical images using advanced feature analysis Non-small cell lung cancer: identifying prognostic imaging biomarkers by leveraging public gene expression microarray data--methods and preliminary results Identification of noninvasive imaging surrogates for brain tumor gene-expression modules Radiomics: the process and the challenges Molecular imaging of breast cancer: present and future directions Quantitative imaging in cancer evolution and ecology Rapid development of image analysis research tools: Bridging the gap between researcher and clinician with pyOsiriX.Joint analysis of multiple high-dimensional data types using sparse matrix approximations of rank-1 with applications to ovarian and liver cancer Test-retest reproducibility analysis of lung CT image features Medical imaging in personalised medicine: a white paper of the research committee of the European Society of Radiology (ESR)Pushing CT and MR imaging to the molecular level for studying the "omics": current challenges and advancements A combinatorial radiographic phenotype may stratify patient survival and be associated with invasion and proliferation characteristics in glioblastoma Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging.New paradigm for management of hepatocellular carcinoma by imaging.Development of biomarkers for screening hepatocellular carcinoma using global data mining and multiple reaction monitoring.Database integration of 4923 publicly-available samples of breast cancer molecular and clinical data.Glioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features.Characterization of PET/CT images using texture analysis: the past, the present… any future?Associations of Radiomic Data Extracted from Static and Respiratory-Gated CT Scans with Disease Recurrence in Lung Cancer Patients Treated with SBRT Molecular subsets in the gene expression signatures of scleroderma skin.Validation of putative reference genes for gene expression studies in human hepatocellular carcinoma using real-time quantitative RT-PCR.Radiogenomic Analysis of Oncological Data: A Technical Survey.Analysis of heterogeneity in T2-weighted MR images can differentiate pseudoprogression from progression in glioblastoma.The use of molecular imaging combined with genomic techniques to understand the heterogeneity in cancer metastasis.Regenerative medicine: a surgeon's perspective Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer Unsupervised deconvolution of dynamic imaging reveals intratumor vascular heterogeneity and repopulation dynamics.NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics Signatures Radiomic feature clusters and prognostic signatures specific for Lung and Head & Neck cancer.Radiomics: Images Are More than Pictures, They Are Data.Modules, networks and systems medicine for understanding disease and aiding diagnosis.Use of DNA microarray and small animal positron emission tomography in preclinical drug evaluation of RAF265, a novel B-Raf/VEGFR-2 inhibitor.Antiangiogenic therapy for primary liver cancer: correlation of changes in dynamic contrast-enhanced magnetic resonance imaging with tissue hypoxia markers and clinical response Integration of Network Biology and Imaging to Study Cancer Phenotypes and Responses.Quantitative computed tomographic descriptors associate tumor shape complexity and intratumor heterogeneity with prognosis in lung adenocarcinoma.CAM-CM: a signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues.Robust Radiomics feature quantification using semiautomatic volumetric segmentation.Integrative multi-omics module network inference with Lemon-Tree

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P2860

Decoding global gene expression programs in liver cancer by noninvasive imaging.

http://www.wikidata.org/entity/Q34630291

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2007 թվականի մայիսին հրատարակված գիտական հոդված

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Decoding global gene expression programs in liver cancer by noninvasive imaging.

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Decoding global gene expression programs in liver cancer by noninvasive imaging.

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Decoding global gene expression programs in liver cancer by noninvasive imaging.

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Decoding global gene expression programs in liver cancer by noninvasive imaging.

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Decoding global gene expression programs in liver cancer by noninvasive imaging.

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Decoding global gene expression programs in liver cancer by noninvasive imaging.

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Decoding global gene expression programs in liver cancer by noninvasive imaging.

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Decoding global gene expression programs in liver cancer by noninvasive imaging.

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Decoding global gene expression programs in liver cancer by noninvasive imaging.

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Nature Biotechnology

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Decoding global gene expression programs in liver cancer by noninvasive imaging.

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Bryan K Chan

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Christopher T Barry

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Clara Ooi

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Howard Y Chang

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Jeremy Gollub

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Michael D Kuo

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Xin Chen

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The prognostic molecular markers in hepatocellular carcinoma.

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10.1038/NBT1306

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Claude B. Sirlin

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