Machine learning analysis of 10 hub genes related to SCI was performed using eight algorithms applied to the dataset.

Machine learning analysis of 10 hub genes related to SCI was performed using eight algorithms applied to the dataset.

<p>The results from different machine learning methods include: Lasso-Logistic regression <b>(A)</b>, LQV algorithm <b>(B)</b>, Boruta <b>(C)</b>, Bagged Tree <b>(D)</b>, Random Forest <b>(E)</b>, Bayesian <b>(F)</b>, SVM...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Tianbao Feng (21722233) (author)
مؤلفون آخرون: Jiating Hu (10502876) (author), Mi Xie (2065444) (author), Guodong Shi (314927) (author), Qi Wang (22418) (author), Jingyuan Yao (15188771) (author), Xiaoqin Liu (296429) (author)
منشور في: 2025
الموضوعات:
Biochemistry
Cell Biology
Genetics
Molecular Biology
Immunology
Biological Sciences not elsewhere classified
spinal cord injury
severely impacts motor
programmed cell death
div >< p
debilitating neurological condition
promising diagnostic potential
potential therapeutic target
707 upregulated genes
functional enrichment analysis
gene expression omnibus
panoptosis scores calculation
identify hub genes
consistently identified across
panoptosis gene sets
gene gsea analysis
hub genes
related gene
potential drugs
related genes
elevated expression
targeting panoptosis
panoptosis score
23 panoptosis
time pcr
study seeks
significantly higher
significant roles
significant challenges
results underscore
rat model
quantitative real
performed single
patient quality
pathways associated
intersected degs
inflammatory response
immune response
ihc ).
healthy controls
hc samples
future studies
experimentally confirm
experimental validation
emerging concept
datasets gse151371
casp5 </
biological functions
autonomic functions
auc value
الوسوم: إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

مواد مشابهة