AIMC Topic: Gene Expression Profiling
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Single-cell and whole-transcriptome sequencing of lymph node metastasis-related gene signature: a large-scale pan-cancer cohort, machine learning and experimental study: Retraction.
International journal of surgery (London, England)
Sep 1, 2024
Machine learning approach to predict blood-secretory proteins and potential biomarkers for liver cancer using omics data.
Journal of proteomics
Aug 30, 2024
Identifying non-invasive blood-based biomarkers is crucial for early detection and monitoring of liver cancer (LC), thereby improving patient outcomes. This study leveraged computational approaches to predict potential blood-based biomarkers for LC. ...
Identification of immune-related biomarkers for intracerebral hemorrhage diagnosis based on RNA sequencing and machine learning.
Frontiers in immunology
Aug 30, 2024
BACKGROUND: Intracerebral hemorrhage (ICH) is a severe stroke subtype with high morbidity, disability, and mortality rates. Currently, no biomarkers for ICH are available for use in clinical practice. We aimed to explore the roles of RNAs in ICH path...
Artificial neural network inference analysis identified novel genes and gene interactions associated with skeletal muscle aging.
Journal of cachexia, sarcopenia and muscle
Aug 29, 2024
BACKGROUND: Sarcopenia is an age-related muscle disease that increases the risk of falls, disabilities, and death. It is associated with increased muscle protein degradation driven by molecular signalling pathways including Akt and FOXO1. This study ...
Identification of key immune-related genes and potential therapeutic drugs in diabetic nephropathy based on machine learning algorithms.
BMC medical genomics
Aug 26, 2024
BACKGROUND: Diabetic nephropathy (DN) is a major contributor to chronic kidney disease. This study aims to identify immune biomarkers and potential therapeutic drugs in DN.
Deep learning-based multimodal spatial transcriptomics analysis for cancer.
Advances in cancer research
Aug 22, 2024
The advent of deep learning (DL) and multimodal spatial transcriptomics (ST) has revolutionized cancer research, offering unprecedented insights into tumor biology. This book chapter explores the integration of DL with ST to advance cancer diagnostic...
is a novel marker for bladder cancer prognosis: evidence based on experimental studies, machine learning and single-cell sequencing.
Frontiers in immunology
Aug 21, 2024
BACKGROUND: Bladder cancer, a highly fatal disease, poses a significant threat to patients. Positioned at 19q13.2-13.3, LIG1, one of the four DNA ligases in mammalian cells, is frequently deleted in tumour cells of diverse origins. Despite this, the ...
Identification of copper death-associated molecular clusters and immunological profiles for lumbar disc herniation based on the machine learning.
Scientific reports
Aug 20, 2024
Lumbar disc herniation (LDH) is a common clinical spinal disorder, yet its etiology remains unclear. We aimed to explore the role of cuproptosis-related genes (CRGs) and identify potential diagnostic biomarkers. Our analysis involved interrogating th...
Deciphering the role of HLF in idiopathic orbital inflammation: integrative analysis via bioinformatics and machine learning techniques.
Scientific reports
Aug 20, 2024
Idiopathic orbital inflammation, formerly known as NSOI (nonspecific orbital inflammation), is characterized as a spectrum disorder distinguished by the polymorphic infiltration of lymphoid tissue, presenting a complex and poorly understood etiology....
Identification of key metabolism-related genes and pathways in spontaneous preterm birth: combining bioinformatic analysis and machine learning.
Frontiers in endocrinology
Aug 20, 2024
BACKGROUND: Spontaneous preterm birth (sPTB) is a global disease that is a leading cause of death in neonates and children younger than 5 years of age. However, the etiology of sPTB remains poorly understood. Recent evidence has shown a strong associ...
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