AIMC Topic: Necroptosis

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Machine learning with label-free Raman microscopy to investigate ferroptosis in comparison with apoptosis and necroptosis.

Communications biology
Human and animal health rely on balancing cell division and cell death to maintain normal homeostasis. This process is accomplished by regulated cell death (RCD), whose imbalance can lead to disease. Currently, the most frequently used method for ana...

Deep learning-based image classification reveals heterogeneous execution of cell death fates during viral infection.

Molecular biology of the cell
Cell fate decisions, such as proliferation, differentiation, and death, are driven by complex molecular interactions and signaling cascades. While significant progress has been made in understanding the molecular determinants of these processes, hist...

Deciphering Necroptosis-Associated Molecular Subtypes in Acute Ischemic Stroke Through Bioinformatics and Machine Learning Analysis.

Journal of molecular neuroscience : MN
Acute ischemic stroke (AIS) is a severe disorder characterized by complex pathophysiological processes, which can lead to disability and death. This study aimed to determine necroptosis-associated genes in acute ischemic stroke (AIS) and to investiga...

Integrating necroptosis into pan-cancer immunotherapy: a new era of personalized treatment.

Frontiers in immunology
INTRODUCTION: Necroptosis has emerged as a promising biomarker for predicting immunotherapy responses across various cancer types. Its role in modulating immune activation and therapeutic outcomes offers potential for precision oncology.

Machine learning-based analysis of programmed cell death types and key genes in intervertebral disc degeneration.

Apoptosis : an international journal on programmed cell death
Intervertebral disc degeneration (IVDD) is intricately associated with various forms of programmed cell death (PCD). Identifying key PCD types and associated genes is essential for understanding the molecular mechanisms underlying IVDD and discoverin...

Generative deep learning enables the discovery of a potent and selective RIPK1 inhibitor.

Nature communications
The retrieval of hit/lead compounds with novel scaffolds during early drug development is an important but challenging task. Various generative models have been proposed to create drug-like molecules. However, the capacity of these generative models ...

Establishment and Validation of the Novel Necroptosis-related Genes for Predicting Stemness and Immunity of Hepatocellular Carcinoma Machine-learning Algorithm.

Combinatorial chemistry & high throughput screening
BACKGROUND: Necroptosis, a recently identified mechanism of programmed cell death, exerts significant influence on various aspects of cancer biology, including tumor cell proliferation, stemness, metastasis, and immunosuppression. However, the role o...