AIMC Topic: ErbB Receptors

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Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning.

Cancer medicine May 10, 2019
To develop a deep learning system based on 3D convolutional neural networks (CNNs), and to automatically predict EGFR-mutant pulmonary adenocarcinoma in CT images. A dataset of 579 nodules with EGFR mutation status labels of mutant (Mut) or wild-type...
Algorithms Tomography, X-Ray Computed Female Reproducibility of Results Male Humans Neural Networks, Computer Neoplasm Staging Mutation ErbB Receptors Data Curation Adenocarcinoma of Lung Deep Learning ROC Curve Image Processing, Computer-Assisted Computational Biology
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Automated Stoichiometry Analysis of Single-Molecule Fluorescence Imaging Traces via Deep Learning.

Journal of the American Chemical Society Apr 18, 2019
The stoichiometry of protein complexes is precisely regulated in cells and is fundamental to protein function. Singe-molecule fluorescence imaging based photobleaching event counting is a new approach for protein stoichiometry determination under phy...
Algorithms Protein Structure, Quaternary Fluorescence Photobleaching Deep Learning Humans HeLa Cells Fluorescent Dyes DNA, Single-Stranded Carbocyanines ErbB Receptors Single Molecule Imaging
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Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning.

The European respiratory journal Mar 28, 2019
Epidermal growth factor receptor (EGFR) genotyping is critical for treatment guidelines such as the use of tyrosine kinase inhibitors in lung adenocarcinoma. Conventional identification of EGFR genotype requires biopsy and sequence testing which is i...
Female Reproducibility of Results Aged Male Middle Aged Humans Neural Networks, Computer Retrospective Studies Tomography, X-Ray Computed Neoplasm Staging Deep Learning Mutation ROC Curve ErbB Receptors Image Processing, Computer-Assisted Adenocarcinoma of Lung Computational Biology
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Design and synthesis of new phthalazine-based derivatives as potential EGFR inhibitors for the treatment of hepatocellular carcinoma.

Bioorganic chemistry Dec 31, 2018
Searching for new leads in the battle of cancer will never ends, we herein disclose the design and synthesis of new phthalazine derivatives and their in vitro and in vivo testing for their antiproliferative activity. Phthalazine was selected as a pri...
Cisplatin Carcinoma, Hepatocellular Doxorubicin Protein Kinase Inhibitors Humans ErbB Receptors Cell Proliferation Molecular Docking Simulation Phthalazines Hep G2 Cells Antineoplastic Agents Drug Screening Assays, Antitumor Liver Neoplasms
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RASPELD to Perform High-End Screening in an Academic Environment toward the Development of Cancer Therapeutics.

ChemMedChem Aug 23, 2018
The identification of compounds for dissecting biological functions and the development of novel drug molecules are central tasks that often require screening campaigns. However, the required architecture is cost- and time-intensive. Herein we descri...
Protein Kinase Inhibitors NF-E2-Related Factor 2 Small Molecule Libraries Humans Education, Graduate Antineoplastic Agents Drug Evaluation, Preclinical Kelch-Like ECH-Associated Protein 1 Biological Assay Protein Binding Ligands Dose-Response Relationship, Drug ErbB Receptors Robotics Mutation
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Identifying epidermal growth factor receptor mutation status in patients with lung adenocarcinoma by three-dimensional convolutional neural networks.

The British journal of radiology Aug 13, 2018
OBJECTIVE:: Genetic phenotype plays a central role in making treatment decisions of lung adenocarcinoma, especially the tyrosine-kinase-inhibitors-sensitive mutations of the epidermal growth factor receptor (EGFR) gene. We constructed three-dimension...
Lung Neoplasms Adenocarcinoma Area Under Curve Mutation ErbB Receptors Sensitivity and Specificity Male Imaging, Three-Dimensional Image Processing, Computer-Assisted Humans Neural Networks, Computer Tomography, X-Ray Computed Female
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Development of Ligand-based Big Data Deep Neural Network Models for Virtual Screening of Large Compound Libraries.

Molecular informatics Jun 8, 2018
High-performance ligand-based virtual screening (VS) models have been developed using various computational methods, including the deep neural network (DNN) method. There are high expectations for exploration of the advanced capabilities of DNN to im...
Molecular Docking Simulation Drug Discovery Big Data Ligands Databases, Chemical Humans ErbB Receptors Neural Networks, Computer Small Molecule Libraries
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Machine learning identifies a core gene set predictive of acquired resistance to EGFR tyrosine kinase inhibitor.

Journal of cancer research and clinical oncology May 25, 2018
PURPOSE: Acquired resistance (AR) to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) is a major issue worldwide, for both patients and healthcare providers. However, precise prediction is currently infeasible due to the lack o...
Humans Machine Learning Algorithms Reproducibility of Results Drug Resistance, Neoplasm Neoplasms ErbB Receptors Transcriptome Protein Kinase Inhibitors Cell Line, Tumor Models, Genetic
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Efficacy according to blind independent central review: Post-hoc analyses from the phase III, randomized, multicenter, IPASS study of first-line gefitinib versus carboplatin/paclitaxel in Asian patients with EGFR mutation-positive advanced NSCLC.

Lung cancer (Amsterdam, Netherlands) Nov 30, 2016
OBJECTIVE: The Phase III, randomized, open-label IPASS study (NCT00322452) of first-line epidermal growth factor receptor tyrosine kinase inhibitor (EGFR TKI) gefitinib versus carboplatin/paclitaxel for Asian patients with advanced non-small-cell lun...
Quinazolines Antineoplastic Combined Chemotherapy Protocols Adenocarcinoma Carcinoma, Non-Small-Cell Lung Randomized Controlled Trials as Topic Neoplasm Staging Disease-Free Survival Mutation Male Smoking Asian People Humans Middle Aged ErbB Receptors Carboplatin Antineoplastic Agents Female Protein Kinase Inhibitors Paclitaxel Lung Neoplasms Aged Gefitinib Aged, 80 and over
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Surface Adsorbed Antibody Characterization Using ToF-SIMS with Principal Component Analysis and Artificial Neural Networks.

Langmuir : the ACS journal of surfaces and colloids Aug 19, 2016
Artificial neural networks (ANNs) form a class of powerful multivariate analysis techniques, yet their routine use in the surface analysis community is limited. Principal component analysis (PCA) is more commonly employed to reduce the dimensionality...
Antibodies Multivariate Analysis ErbB Receptors Immunoglobulin Fragments Spectrometry, Mass, Secondary Ion Animals Adsorption Principal Component Analysis Amino Acids Humans Neural Networks, Computer Immunoglobulin G
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