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PTEN Phosphohydrolase

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Large-scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants.

Proteins 29098713
Recent advances in computing power and machine learning empower functional annotation of protein sequences and their transcript variations. Here, we present an automated prediction system UniGOPred, for GO annotations and a database of GO term predic...
Animals Databases, Protein Gene Ontology Humans Machine Learning Models, Biological Proteomics PTEN Phosphohydrolase Sequence Analysis, Protein Transcriptome
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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 32424393
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...
Algorithms Decision Making DNA Damage Genes, p53 Humans Machine Learning Multivariate Analysis Normal Distribution Outcome Assessment, Health Care Probability PTEN Phosphohydrolase Reproducibility of Results ROC Curve Signal Transduction Tumor Suppressor Protein p53
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High throughput assessment of biomarkers in tissue microarrays using artificial intelligence: PTEN loss as a proof-of-principle in multi-center prostate cancer cohorts.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc 32884130
Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and has clinical potential as a prognostic biomarker. The objective of this work was to develop an artificial intelligence (AI) system for automated det...
Algorithms Biomarkers, Tumor Cohort Studies Deep Learning High-Throughput Nucleotide Sequencing Humans Image Processing, Computer-Assisted Male Prostatic Neoplasms PTEN Phosphohydrolase Tissue Array Analysis
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Artificial Intelligence-Based PTEN Loss Assessment as an Early Predictor of Prostate Cancer Metastasis After Surgery: A Multicenter Retrospective Study.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc 37343766
Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and can be measured via immunohistochemistry. The purpose of the study was to establish the clinical application of an in-house developed artificial int...
Aged Artificial Intelligence Biomarkers, Tumor Humans Immunohistochemistry Male Middle Aged Neoplasm Recurrence, Local Predictive Value of Tests Prostatectomy Prostatic Neoplasms PTEN Phosphohydrolase Retrospective Studies
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Predicting Prostate Cancer Molecular Subtype With Deep Learning on Histopathologic Images.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc 37307876
Microscopic examination of prostate cancer has failed to reveal a reproducible association between molecular and morphologic features. However, deep-learning algorithms trained on hematoxylin and eosin (H&E)-stained whole slide images (WSI) may outpe...
Algorithms Biomarkers, Tumor Deep Learning Humans Image Interpretation, Computer-Assisted Male Prostatic Neoplasms PTEN Phosphohydrolase Transcriptional Regulator ERG
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Deep learning prioritizes cancer mutations that alter protein nucleocytoplasmic shuttling to drive tumorigenesis.

Nature communications 40087285
Genetic variants can affect protein function by driving aberrant subcellular localization. However, comprehensive analysis of how mutations promote tumor progression by influencing nuclear localization is currently lacking. Here, we systematically ch...
Active Transport, Cell Nucleus Carcinogenesis Cell Nucleus Cytoplasm Deep Learning Humans Mutation Neoplasms Nuclear Localization Signals PTEN Phosphohydrolase
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Machine Learning and Structural Dynamics-Based Approach to Reveal Molecular Mechanism of PTEN Missense Mutations Shared by Cancer and Autism Spectrum Disorder.

Journal of chemical information and modeling 40228162
Missense mutations in oncogenic proteins that are concurrently associated with neurodevelopmental disorders have garnered significant attention. Phosphatase and tensin homologue (PTEN) serves as a paradigmatic model for mapping its mutational landsca...
Autism Spectrum Disorder Humans Machine Learning Molecular Dynamics Simulation Mutation, Missense Neoplasms Protein Conformation PTEN Phosphohydrolase
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