AIMC Topic: Membrane Proteins
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Development of a prognostic model for osteosarcoma based on macrophage polarization-related genes using machine learning: implications for personalized therapy.
Clinical and experimental medicine
May 9, 2025
While neoadjuvant chemotherapy combined with surgical resection has improved the prognosis for patients with osteosarcoma, its impact on metastatic and recurrent cases remains limited. Immunotherapy is emerging as a promising alternative. However, th...
Exploring genetic and immune cell dynamics in systemic lupus erythematosus patients with Epstein-Barr virus infection via machine learning.
Rheumatology (Oxford, England)
May 1, 2025
OBJECTIVES: EBV is a widespread virus implicated in various diseases, including SLE. However, the specific genes and pathways altered in SLE patients with EBV infection remain unclear. We aimed to identify key genes and immune cells in SLE patients w...
Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD).
Frontiers in immunology
Jan 1, 2025
BACKGROUND: Acute intestinal graft-versus-host disease (AIGVHD) is a common complication of allogeneic hematopoietic stem cell transplantation (allo HSCT) with a high mortality rate. The primary aim of the present study is to identify tissue-based ge...
Machine Learning Reveals Aneuploidy Characteristics in Cancers: The Impact of BEX4.
Frontiers in bioscience (Landmark edition)
Nov 29, 2024
BACKGROUND: Aneuploidy is crucial yet under-explored in cancer pathogenesis. Specifically, the involvement of brain expressed X-linked gene 4 () in microtubule formation has been identified as a potential aneuploidy mechanism. Nevertheless, 's compre...
A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma.
Briefings in bioinformatics
Nov 22, 2024
Recent studies suggest cGAS-STING pathway may play a crucial role in the genesis and development of hepatocellular carcinoma (HCC), closely associated with classical pathways and tumor immunity. We aimed to develop models predicting survival and anti...
Machine Learning Diagnostic Model for Hepatocellular Carcinoma Based on Liquid-Liquid Phase Separation and Ferroptosis-Related Genes.
The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
Oct 7, 2024
BACKGROUND/AIMS: Hepatocellular carcinoma (HCC) represents a primary liver malignancy with a multifaceted molecular landscape. The interplay between liquid-liquid phase separation (LLPS) and ferroptosis-a regulated form of cell death-has garnered int...
ProteinMAE: masked autoencoder for protein surface self-supervised learning.
Bioinformatics (Oxford, England)
Dec 1, 2023
SUMMARY: The biological functions of proteins are determined by the chemical and geometric properties of their surfaces. Recently, with the booming progress of deep learning, a series of learning-based surface descriptors have been proposed and achie...
Identification of membrane protein types via deep residual hypergraph neural network.
Mathematical biosciences and engineering : MBE
Nov 6, 2023
A membrane protein's functions are significantly associated with its type, so it is crucial to identify the types of membrane proteins. Conventional computational methods for identifying the species of membrane proteins tend to ignore two issues: Hig...
Neural potentials of proteins extrapolate beyond training data.
The Journal of chemical physics
Aug 28, 2023
We evaluate neural network (NN) coarse-grained (CG) force fields compared to traditional CG molecular mechanics force fields. We conclude that NN force fields are able to extrapolate and sample from unseen regions of the free energy surface when trai...
GeoBind: segmentation of nucleic acid binding interface on protein surface with geometric deep learning.
Nucleic acids research
Jun 9, 2023
Unveiling the nucleic acid binding sites of a protein helps reveal its regulatory functions in vivo. Current methods encode protein sites from the handcrafted features of their local neighbors and recognize them via a classification, which are limite...
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