AIMC Topic: ErbB Receptors

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[Prediction of gene mutation in lung cancer based on deep learning and histomorphology analysis].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Feb 25, 2020
Lung cancer is a most common malignant tumor of the lung and is the cancer with the highest morbidity and mortality worldwide. For patients with advanced non-small cell lung cancer who have undergone epidermal growth factor receptor (EGFR) gene mutat...
Humans Deep Learning Mutation ErbB Receptors Carcinoma, Non-Small-Cell Lung Lung Neoplasms
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Validity of Natural Language Processing for Ascertainment of and Test Results in SEER Cases of Stage IV Non-Small-Cell Lung Cancer.

JCO clinical cancer informatics May 1, 2019
PURPOSE: SEER registries do not report results of epidermal growth factor receptor () and anaplastic lymphoma kinase () mutation tests. To facilitate population-based research in molecularly defined subgroups of non-small-cell lung cancer (NSCLC), we...
Male Middle Aged Adult Population Surveillance Natural Language Processing Carcinoma, Non-Small-Cell Lung Lung Neoplasms Female Algorithms Aged Reproducibility of Results Humans Machine Learning Anaplastic Lymphoma Kinase DNA Mutational Analysis SEER Program ErbB Receptors Registries Kentucky Mutation Genetic Testing
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KAI1/CD82, Metastasis Suppressor Gene as a Therapeutic Target for Non-Small-Cell Lung Carcinoma.

Journal of environmental pathology, toxicology and oncology : official organ of the International Society for Environmental Toxicology and Cancer Jan 1, 2017
Lung cancer is the most frequent malignancy and the leading cause of cancer-related death worldwide; it is the second most common cancer, comprising 1.69 million deaths worldwide per year. Among these, 85% of lung cancers are non-small-cell lung carc...
Kangai-1 Protein ErbB Receptors Genes, p53 Genes, Tumor Suppressor Humans Wnt Signaling Pathway Carcinoma, Non-Small-Cell Lung Lung Neoplasms
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Structural Comparison of Gene Relevance Networks for Breast Cancer Tissues in Different Grades.

Combinatorial chemistry & high throughput screening Jan 1, 2016
BACKGROUND: The breast is an important biological system of human with two distinct states, i.e. normal and tumoral. Research on breast cancer could be based on systematic modeling to contrast the system structures of these two states.
Proto-Oncogene Proteins c-fos Genes, Neoplasm bcl-2 Homologous Antagonist-Killer Protein ZAP-70 Protein-Tyrosine Kinase ErbB Receptors Humans ras Proteins Lipocalin-2 Gene Regulatory Networks Support Vector Machine Breast Neoplasms Female
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Self-Organizing Map (SOM) and Support Vector Machine (SVM) Models for the Prediction of Human Epidermal Growth Factor Receptor (EGFR/ ErbB-1) Inhibitors.

Combinatorial chemistry & high throughput screening Jan 1, 2016
EGFR (ErbB-1/HER1) kinase plays an important role in cancer therapy. Two classification models were established to predict whether a compound is an inhibitor or a decoy of human EGFR (ErbR-1) by using Kohonen's self-organizing map (SOM) and support v...
Computing Methodologies ErbB Receptors Molecular Structure Substrate Specificity Software Humans Support Vector Machine Binding Sites
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