AIMC Topic: Tumor Suppressor Protein p53

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A novel algorithm to improve specificity in ovarian cancer detection.

Cancer treatment and research communications Nov 10, 2017
BACKGROUND: Measurement of autoantibodies (AAbs) to tumor associated antigens has been proposed to aid in the early detection of ovarian cancer with high specificity. Here we describe a multiplex approach to evaluate selected peptide epitopes of p53 ...
Neoplasm Staging Immunoassay Epitopes Tumor Suppressor Protein p53 CA-125 Antigen Biomarkers, Tumor Middle Aged Early Detection of Cancer Humans Ovarian Neoplasms Female Autoantibodies Aged Sensitivity and Specificity
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MRI features predict p53 status in lower-grade gliomas via a machine-learning approach.

NeuroImage. Clinical Oct 29, 2017
BACKGROUND: P53 mutation status is a pivotal biomarker for gliomas. Here, we developed a machine-learning model to predict p53 status in lower-grade gliomas based on radiomic features extracted from conventional magnetic resonance (MR) images.
Middle Aged Adolescent Child, Preschool Child Humans ROC Curve Image Processing, Computer-Assisted Machine Learning Young Adult Glioma Retrospective Studies Adult Magnetic Resonance Imaging Female Brain Neoplasms Mutation Aged Male Tumor Suppressor Protein p53
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Achyranthes bidentate saponins protect rat articular chondrocytes against interleukin-1β-induced inflammation and apoptosis in vitro.

The Kaohsiung journal of medical sciences Dec 30, 2016
Achyranthes bidentate Blume (Niuxi) is often employed for treatment of arthritis in Traditional Chinese Medicine and possesses anti-inflammatory properties. Phytochemical and pharmacological studies proved the oleanane-type saponins to be the main bi...
Animals bcl-2-Associated X Protein Male Chondrocytes Anti-Inflammatory Agents, Non-Steroidal Plant Extracts Saponins Proliferating Cell Nuclear Antigen Signal Transduction Plant Roots Rats Tumor Suppressor Protein p53 Cyclooxygenase 2 Rats, Sprague-Dawley Achyranthes Interleukin-1beta Inflammation Gene Expression Regulation Cartilage, Articular Apoptosis NF-kappa B bcl-Associated Death Protein Caspase 3 bcl-X Protein Matrix Metalloproteinase 9 Matrix Metalloproteinase 3 Primary Cell Culture
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Genotoxic mode of action predictions from a multiplexed flow cytometric assay and a machine learning approach.

Environmental and molecular mutagenesis Jan 13, 2016
Several endpoints associated with cellular responses to DNA damage as well as overt cytotoxicity were multiplexed into a miniaturized, "add and read" type flow cytometric assay. Reagents included a detergent to liberate nuclei, RNase and propidium io...
Humans Mutagens Cell Line Machine Learning Mutagenicity Tests DNA Damage Algorithms Histones Flow Cytometry Automation, Laboratory Aneugens Tumor Suppressor Protein p53 Biomarkers Reproducibility of Results
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Lung cancer prediction using neural network ensemble with histogram of oriented gradient genomic features.

TheScientificWorldJournal Feb 23, 2015
This paper reports an experimental comparison of artificial neural network (ANN) and support vector machine (SVM) ensembles and their "nonensemble" variants for lung cancer prediction. These machine learning classifiers were trained to predict lung c...
Mutation Tumor Suppressor Protein p53 ErbB Receptors Proto-Oncogene Proteins p21(ras) Neural Networks, Computer Humans Biomarkers, Tumor Lung Neoplasms Support Vector Machine Carcinoma, Non-Small-Cell Lung
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AI-HOPE: an AI-driven conversational agent for enhanced clinical and genomic data integration in precision medicine research.

Bioinformatics (Oxford, England) Jul 1, 2025
MOTIVATION: The growing complexity of clinical cancer research has fueled a surge in demand for automated bioinformatics tools capable of integrating clinical and genomic data to accelerate discovery efforts.
Neoplasms Genomics Computational Biology Humans Mutation Tumor Suppressor Protein p53 Artificial Intelligence Precision Medicine Colorectal Neoplasms
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Development and validation of a machine learning prognostic model based on an epigenomic signature in patients with pancreatic ductal adenocarcinoma.

International journal of medical informatics Jul 1, 2025
BACKGROUND: In Pancreatic Ductal Adenocarcinoma (PDAC), current prognostic scores are unable to fully capture the biological heterogeneity of the disease. While some approaches investigating the role of multi-omics in PDAC are emerging, the analysis ...
Middle Aged Epigenomics DNA Methylation Pancreatic Neoplasms Mutation Carcinoma, Pancreatic Ductal Tumor Suppressor Protein p53 CpG Islands Proto-Oncogene Proteins p21(ras) Humans Machine Learning Prognosis Female Male
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Bioconjugates of photon-upconversion nanoparticles with antibodies for the detection of prostate-specific antigen and p53 in heterogeneous and homogeneous immunoassays.

Nanoscale May 9, 2025
Sensitive immunoassays for the detection of tumor biomarkers play an important role in the early diagnosis and therapy of cancer. Using luminescent nanomaterials as labels can significantly improve immunoassay performance, especially in terms of sens...
Prostatic Neoplasms Prostate-Specific Antigen Immunoassay Tumor Suppressor Protein p53 Photons Biomarkers, Tumor Male Nanoparticles Antibodies, Monoclonal Limit of Detection Erbium Humans
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CODEX, a neural network approach to explore signaling dynamics landscapes.

Molecular systems biology Apr 1, 2021
Current studies of cell signaling dynamics that use live cell fluorescent biosensors routinely yield thousands of single-cell, heterogeneous, multi-dimensional trajectories. Typically, the extraction of relevant information from time series data reli...
Humans Neural Networks, Computer Machine Learning Algorithms Animals Light Intercellular Signaling Peptides and Proteins Tumor Suppressor Protein p53 Databases as Topic Movement Signal Transduction Cell Line Fluorescent Dyes Proto-Oncogene Proteins c-akt Transforming Growth Factor beta Dose-Response Relationship, Radiation Drosophila Radiation, Ionizing Extracellular Signal-Regulated MAP Kinases
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Modeling and measurement of signaling outcomes affecting decision making in noisy intracellular networks using machine learning methods.

Integrative biology : quantitative biosciences from nano to macro May 21, 2020
Characterization of decision-making in cells in response to received signals is of importance for understanding how cell fate is determined. The problem becomes multi-faceted and complex when we consider cellular heterogeneity and dynamics of biochem...
Multivariate Analysis Genes, p53 Normal Distribution PTEN Phosphohydrolase Machine Learning Algorithms Reproducibility of Results ROC Curve Signal Transduction Decision Making DNA Damage Outcome Assessment, Health Care Probability Tumor Suppressor Protein p53 Humans
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