AIMC Topic: Tumor Suppressor Protein p53

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Interpretable multi-stage attention network to predict cancer subtype, microsatellite instability, TP53 mutation and TMB of endometrial and colorectal cancer.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mismatch repair deficiency (dMMR), also known as high-grade microsatellite instability (MSI-H), is a well-established biomarker for predicting the immunotherapy response in endometrial cancer (EC) and colorectal cancer (CRC). Tumor mutational burden ...

Estimation of TP53 mutations for endometrial cancer based on diffusion-weighted imaging deep learning and radiomics features.

BMC cancer
OBJECTIVES: To construct a prediction model based on deep learning (DL) and radiomics features of diffusion weighted imaging (DWI), and clinical variables for evaluating TP53 mutations in endometrial cancer (EC).

Novel anoikis-related diagnostic biomarkers for aortic dissection based on machine learning.

Scientific reports
Aortic dissection (AD) is one of the most dangerous diseases of the cardiovascular system, which is characterized by acute onset and poor prognosis, while the pathogenesis of AD is still unclear and may affect or even delay the diagnosis of AD. Ancho...

Role of artificial intelligence in cancer detection using protein p53: A Review.

Molecular biology reports
Normal cell development and prevention of tumor formation rely on the tumor-suppressor protein p53. This crucial protein is produced from the Tp53 gene, which encodes the p53 protein. The p53 protein plays a vital role in regulating cell growth, DNA ...

Screening core genes for minimal change disease based on bioinformatics and machine learning approaches.

International urology and nephrology
Based on bioinformatics and machine learning methods, we conducted a study to screen the core genes of minimal change disease (MCD) and further explore its pathogenesis. First, we obtained the chip data sets GSE108113 and GSE200828 from the Gene Expr...

Combining network pharmacology, machine learning, molecular docking and molecular dynamic to explore the mechanism of Chufeng Qingpi decoction in treating schistosomiasis.

Frontiers in cellular and infection microbiology
BACKGROUND: Although the Chufeng Qingpi Decoction (CQD) has demonstrated clinical effectiveness in the treatment of schistosomiasis, the precise active components and the underlying mechanisms of its therapeutic action remain elusive. To achieve a pr...

AI-based histopathology image analysis reveals a distinct subset of endometrial cancers.

Nature communications
Endometrial cancer (EC) has four molecular subtypes with strong prognostic value and therapeutic implications. The most common subtype (NSMP; No Specific Molecular Profile) is assigned after exclusion of the defining features of the other three molec...

Exploring the NRF2-TP53 Signaling Network Through Machine Learning and Pan-Cancer Analysis: Identifying Potential targets for Cancer Prognosis Related to Oxidative Stress.

Advanced biology
Oxidative stress (OXS) is closely related to tumor prognosis and immune response, while TP53 integrated with NRF2 is closely associated with the regulation of cancer-related OXS. Hence, constructing a TP53-NRF2 integrated OXS signature of pan-cancer ...

PMSPcnn: Predicting protein stability changes upon single point mutations with convolutional neural network.

Structure (London, England : 1993)
Protein missense mutations and resulting protein stability changes are important causes for many human genetic diseases. However, the accurate prediction of stability changes due to mutations remains a challenging problem. To address this problem, we...