AIMC Topic: Neoplasm Proteins

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In vitro study of the nephrotoxicity of total Dahuang (Radix Et Rhizoma Rhei Palmati) anthraquinones and emodin in monolayer human proximal tubular epithelial cells cultured in a transwell chamber.

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan Oct 1, 2019
OBJECTIVE: To examine changes in the morphology and physiological functions of human proximal tubular epithelial cells (HK-2 cells) caused by total Dahuang (Radix Et Rhizoma Rhei Palmati) anthraquinones (TDA) and emodin.
Absorption, Physicochemical Neoplasm Proteins Actins Glucose Emodin Rheum Kidney Tubules, Proximal Anthraquinones Hepatitis A Virus Cellular Receptor 1 gamma-Glutamyltransferase Gene Expression Regulation L-Lactate Dehydrogenase Humans Cell Proliferation Cell Line Epithelial Cells
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Treatment Potential for Macular Cone Vision in Leber Congenital Amaurosis Due to CEP290 or NPHP5 Mutations: Predictions From Artificial Intelligence.

Investigative ophthalmology & visual science Jun 3, 2019
PURPOSE: To use supervised machine learning to predict visual function from retinal structure in retinitis pigmentosa (RP) and apply these estimates to CEP290- and NPHP5-associated Leber congenital amaurosis (LCA) to determine the potential for funct...
Antigens, Neoplasm Neoplasm Proteins Tomography, Optical Coherence Mutation Visual Fields Adult Machine Learning Male Color Vision Defects Female Middle Aged Retinal Cone Photoreceptor Cells Young Adult Adolescent Visual Field Tests Calmodulin-Binding Proteins Humans Cytoskeletal Proteins Leber Congenital Amaurosis Genetic Therapy Retinitis Pigmentosa Cell Cycle Proteins
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DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies.

Nucleic acids research May 7, 2019
Although rapid progress has been made in computational approaches for prioritizing cancer driver genes, research is far from achieving the ultimate goal of discovering a complete catalog of genes truly associated with cancer. Driver gene lists predic...
Humans Machine Learning Software Datasets as Topic Monte Carlo Method Nuclear Proteins Cell Cycle Proteins Cell Movement Oncogenes Atlases as Topic Neoplasm Proteins Mutation Neoplasms Cell Line, Tumor Gene Expression Regulation, Neoplastic Cell Proliferation
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A parsimonious 3-gene signature predicts clinical outcomes in an acute myeloid leukemia multicohort study.

Blood advances Apr 23, 2019
Acute myeloid leukemia (AML) is a genetically heterogeneous hematological malignancy with variable responses to chemotherapy. Although recurring cytogenetic abnormalities and gene mutations are important predictors of outcome, 50% to 70% of AMLs harb...
Infant Adolescent Child, Preschool Child Leukemia, Myeloid, Acute Male Middle Aged Risk Assessment Models, Biological Disease-Free Survival Gene Expression Regulation, Neoplastic Databases, Genetic Neoplasm Proteins Predictive Value of Tests Humans Infant, Newborn Adult Survival Rate Neural Networks, Computer Female
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Deep learning for tumor classification in imaging mass spectrometry.

Bioinformatics (Oxford, England) Apr 1, 2018
MOTIVATION: Tumor classification using imaging mass spectrometry (IMS) data has a high potential for future applications in pathology. Due to the complexity and size of the data, automated feature extraction and classification steps are required to f...
Mass Spectrometry Neoplasm Proteins Supervised Machine Learning Humans Animals Neoplasms Computational Biology
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The co-regulators SRC-1 and SMRT are involved in interleukin-6-induced androgen receptor activation.

European cytokine network Nov 1, 2016
BACKGROUND: The androgen receptor (AR) can be stimulated by interleukin-6 (IL-6) in the absence of androgens to induce prostate cancer progression. The purpose of this study was to investigate whether the co-activator steroid receptor coactivator-1 (...
Prostatic Neoplasms Receptors, Androgen Nuclear Receptor Co-Repressor 2 Nuclear Receptor Coactivator 1 Interleukin-6 Male Humans Cell Line, Tumor Neoplasm Proteins
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Association of ATP-Binding Cassette Transporter (ABC) Gene Polymorphisms with Viral Load in Patients with Genotype 1 Hepatitis C Virus Infection.

Clinical laboratory Sep 1, 2016
BACKGROUND: ATP-binding cassette transporters (ABC) gene polymorphisms are associated with various biological functions, including hepatitis C virus (HCV) infection. This study aims to explore the impact of ABC transporters polymorphisms on HCV viral...
ATP Binding Cassette Transporter, Subfamily B, Member 11 ATP Binding Cassette Transporter, Subfamily G, Member 2 ATP Binding Cassette Transporter, Subfamily G, Member 5 Gene Frequency ATP-Binding Cassette Transporters ATP Binding Cassette Transporter 1 Neoplasm Proteins ATP Binding Cassette Transporter, Subfamily B Viral Load ATP Binding Cassette Transporter, Subfamily B, Member 1 Polymorphism, Single Nucleotide Hepacivirus Humans Genotype Hepatitis C, Chronic Lipoproteins Female Interleukins Male Middle Aged
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Protein interaction network constructing based on text mining and reinforcement learning with application to prostate cancer.

IET systems biology Aug 1, 2015
Constructing interaction network from biomedical texts is a very important and interesting work. The authors take advantage of text mining and reinforcement learning approaches to establish protein interaction network. Considering the high computatio...
Periodicals as Topic PubMed Humans Data Mining Machine Learning Protein Interaction Mapping Neoplasm Proteins Male Natural Language Processing Signal Transduction Prostatic Neoplasms
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Regularised extreme learning machine with misclassification cost and rejection cost for gene expression data classification.

International journal of data mining and bioinformatics Jan 1, 2015
The main purpose of traditional classification algorithms on bioinformatics application is to acquire better classification accuracy. However, these algorithms cannot meet the requirement that minimises the average misclassification cost. In this pap...
Humans Gene Expression Regulation, Neoplastic Databases, Genetic Neoplasm Proteins Artificial Intelligence Algorithms Colonic Neoplasms
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A hybrid ensemble method based on double disturbance for classifying microarray data.

Bio-medical materials and engineering Jan 1, 2015
Microarray data has small samples and high dimension, and it contains a significant amount of irrelevant and redundant genes. This paper proposes a hybrid ensemble method based on double disturbance to improve classification performance. Firstly, ori...
Pattern Recognition, Automated Oligonucleotide Array Sequence Analysis Computer Simulation Neoplasms Humans Gene Expression Profiling Machine Learning Models, Statistical Algorithms Neoplasm Proteins
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