AIMC Topic: Repressor Proteins
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WISP2/CCN5 revealed as a potential diagnostic biomarker for endometriosis based on machine learning and single-cell transcriptomic analysis.
Functional & integrative genomics
Jun 19, 2025
OBJECTIVE: Endometriosis is a prevalent gynecological disease characterized by the ectopic growth of functional endometrial tissue outside the uterine cavity, affecting millions of women worldwide. Currently, the definitive diagnosis relies on invasi...
Conformity of ChatGPT recommendations with the AUA/SUFU guideline on postprostatectomy urinary incontinence.
Neurourology and urodynamics
Mar 7, 2024
INTRODUCTION: Artificial intelligence (AI) shows immense potential in medicine and Chat generative pretrained transformer (ChatGPT) has been used for different purposes in the field. However, it may not match the complexity and nuance of certain medi...
Cell-type-directed design of synthetic enhancers.
Nature
Dec 12, 2023
Transcriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes. It has been a long-standing goal in the field to decode the regulatory logic of an enhan...
Identification of key genes in spontaneous cerebral hemorrhage and prevention of disease damage: LASSO and SVM regression.
Preventive medicine
Jul 18, 2023
Prevention is more important than treatment, and the incidence of intracerebral hemorrhage can be effectively reduced by intervening on the risk factors of intracerebral hemorrhage. By studying the risk factors of spontaneous intracerebral hemorrhage...
Computational analysis of morphological and molecular features in gastric cancer tissues.
Cancer medicine
Feb 3, 2020
Biological morphologies of cells and tissues represent their physiological and pathological conditions. The importance of quantitative assessment of morphological information has been highly recognized in clinical diagnosis and therapeutic strategies...
Targeted bisulfite sequencing identified a panel of DNA methylation-based biomarkers for esophageal squamous cell carcinoma (ESCC).
Clinical epigenetics
Dec 15, 2017
BACKGROUND: DNA methylation has been implicated as a promising biomarker for precise cancer diagnosis. However, limited DNA methylation-based biomarkers have been described in esophageal squamous cell carcinoma (ESCC).
Pseudogenes
Middle Aged
Repressor Proteins
Esophageal Neoplasms
Aged
Early Detection of Cancer
Logistic Models
Sequence Analysis, DNA
CpG Islands
Serine-Threonine Kinase 3
DNA Methylation
Humans
Protein Serine-Threonine Kinases
Promoter Regions, Genetic
DNA-Binding Proteins
Machine Learning
Esophageal Squamous Cell Carcinoma
Female
Carcinoma, Squamous Cell
Epigenesis, Genetic
Databases, Genetic
Sensitivity and Specificity
Biomarkers, Tumor
Male
Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.
Nucleic acids research
Feb 22, 2016
Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the te...
Selection of neuroendocrine markers in diagnostic workup of neuroendocrine neoplasms: The real-world data and machine learning model algorithms.
Cancer cytopathology
May 1, 2025
BACKGROUND: Accurate diagnosis of neuroendocrine neoplasms (NENs) is challenging, especially in poorly differentiated neuroendocrine carcinomas (NECs). This study was aimed to search the best or best combination of neuroendocrine markers in the diagn...
Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer.
Cancer research
Apr 14, 2023
UNLABELLED: Survival rates of patients with metastatic castration-resistant prostate cancer (mCRPC) are low due to lack of response or acquired resistance to available therapies, such as abiraterone (Abi). A better understanding of the underlying mol...
Repressor Proteins
Proto-Oncogene Proteins c-ets
Proto-Oncogene Proteins c-myb
Androstenes
Basic Helix-Loop-Helix Leucine Zipper Transcription Factors
Prostatic Neoplasms
Drug Resistance, Neoplasm
Transcription, Genetic
Male
Gene Expression Profiling
Gene Regulatory Networks
Bayes Theorem
Humans
Machine Learning
Computer Simulation
[Study of FN1 and ZNF438 gene expression negatively regulated by androgen receptor in androgen-independent LNCaP cells].
Zhonghua yi xue za zhi
Dec 19, 2015
OBJECTIVE: To verify whether FN1 and ZNF438 are the androgen receptor(AR) target genes in LNCaP-AI cells and investigate the effects of AR exerts on FN1 and ZNF438 gene expression.
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