相关实验视频

Updated: Jul 5, 2025

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Published on: November 19, 2018

12.5K

机器学习和单细胞分析识别IPF相关纤维细胞亚型的分子特征及其对IPF预后的影响

Jiwei Hou1, Yanru Yang1, Xin Han1

  • 1Department of Biochemistry and Molecular Biology, School of Medicine & Holistic Integrative Medicine, Jiangsu Collaborative Innovation Canter of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing 210023, China.

International journal of molecular sciences
|January 11, 2024
PubMed
概括

研究人员在异常性肺纤维化 (IPF) 肺部中确定了两个主要的纤维细胞亚型. 这些与IPF相关的纤维细胞及其基因特征可以预测疾病预后,并指导IPF患者的向治疗.

关键词:
生物信息学是一种生物信息学.纤维细胞细胞是什么?异质性的异质性异形性肺纤维化 异形性肺纤维化预测模型是一个预测模型.

更多相关视频

Predictive Immune Modeling of Solid Tumors08:50

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

7.0K
Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations10:23

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

Published on: January 19, 2017

11.0K

相关概念视频

EPS and iPS Cells in Disease Research01:21

EPS and iPS Cells in Disease Research

Embryonic and induced pluripotent stem cells are excellent models for disease research because of their ability to self-renew and differentiate into most cell types. Somatic cells from a patient are isolated and reprogrammed into induced pluripotent stem cells or iPSCs. These iPSCs are later differentiated into the desired cell type, which mirrors the diseased cell of the patient. In this way, disease models have been created for investigating diseases such as Down syndrome, type I diabetes,...
2.8K