AIMC Topic: Nuclear Proteins
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Stem loop binding protein promotes SARS-CoV-2 replication via -1 programmed ribosomal frameshifting.
Signal transduction and targeted therapy
Jun 13, 2025
The -1 programmed ribosomal frameshifting (-1 PRF) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial for keeping the balance between pp1a and pp1ab polyproteins. To date, the host factors influencing this process remain poorl...
First-line combination therapy of immunotherapy plus anti-angiogenic drug for thoracic SMARCA4-deficient undifferentiated tumors in AIDS: a case report and review of the literature.
Frontiers in immunology
Jan 9, 2025
BACKGROUND: Thoracic SMARCA4-deficient undifferentiated tumors (SMARCA4-UT) exhibit a notably aggressive phenotype, which is associated with poor patient survival outcomes. These tumors are generally resistant to conventional cytotoxic chemotherapy, ...
Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning.
Molecules (Basel, Switzerland)
Apr 19, 2024
Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calcula...
Oral Cancer Prediction Using a Probability Neural Network (PNN).
Asian Pacific journal of cancer prevention : APJCP
Sep 1, 2023
OBJECTIVE: In India, usually, oral cancer is mostly identified at a progressive stage of malignancy. Hence, we are motivated to identify oral cancer in its early stages, which helps to increase the lifetime of the patient, but this early detection is...
Application of Feature Selection and Deep Learning for Cancer Prediction Using DNA Methylation Markers.
Genes
Aug 29, 2022
DNA methylation is a process that can affect gene accessibility and therefore gene expression. In this study, a machine learning pipeline is proposed for the prediction of breast cancer and the identification of significant genes that contribute to t...
Nested epistasis enhancer networks for robust genome regulation.
Science (New York, N.Y.)
Aug 11, 2022
Mammalian genomes have multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, but it is unclear how these enhancers coordinate to achieve this task. We combine multiplexed CRISPRi screening with machine learning t...
An Integrated Approach Fusing CEEMD Energy Entropy and Sparrow Search Algorithm-Based PNN for Fault Diagnosis of Rolling Bearings.
Computational intelligence and neuroscience
Jul 22, 2022
This paper solves the problem of difficulty in achieving satisfactory results with traditional methods of bearing fault diagnosis, which can effectively extract the fault information and improve the fault diagnosis accuracy. This paper proposes a nov...
MAFF-Net: Multi-Attention Guided Feature Fusion Network for Change Detection in Remote Sensing Images.
Sensors (Basel, Switzerland)
Jan 24, 2022
One of the most important tasks in remote sensing image analysis is remote sensing image Change Detection (CD), and CD is the key to helping people obtain more accurate information about changes on the Earth's surface. A Multi-Attention Guided Featur...
A novel machine-learning-derived genetic score correlates with measurable residual disease and is highly predictive of outcome in acute myeloid leukemia with mutated NPM1.
Blood cancer journal
Oct 1, 2019
Machine learning prediction of cyanobacterial toxin (microcystin) toxicodynamics in humans.
ALTEX
Jul 2, 2019
Microcystins (MC) represent a family of cyclic peptides with approx. 250 congeners presumed harmful to human health due to their ability to inhibit ser/thr-proteinphosphatases (PPP), albeit all hazard and risk assessments (RA) are based on data of on...
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