Construction and Analysis of lncRNA-Mediated ceRNA Network in Nasopharyngeal Carcinoma Based on Weighted Correlation

Zhenning Zou1, Shuguang Liu2, Yanping Ha1

  • 1Department of Pathology, Guangdong Medical University, Zhanjiang, China.

Related Concept Videos

lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
9.5K
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

3.2K
The Nucleolus02:55

The Nucleolus

The nucleolus is the most prominent substructure of the nucleus. When it was first discovered, it was considered to be an isolated organelle that forms fibrils and granules. In 1931, the relationship between the nucleolus and chromosomes was first described by Heitz. He observed that the appearance and size of nucleolus varies depending on the stage of the cell cycle. He also noticed constricted regions on different chromosomes clustered together at definite cell cycle stages. These regions,...
9.9K
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.4K
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
555