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Redirected from 유전자 발현
Gene expression (유전자 발현) is the process by which information from a gene is used in the synthesis of a functional gene product. (https://en.wikipedia.org/wiki/Gene_expression)
생물학은 유전자 발현 결과의 양(농도)의 차이로 나타남. 어떻게 양을 결정하는가. 어떻게 조절되는가.
- Genome level
- Epigenome level
- Before transcription
- Before translation
- RNA editing
- Alternative splicing
- mRNA poly-A tail 길이
- microRNA and lncRNA (epigenome)
- After translation
특정 조건에 따라 발현량이 다른 유전자를 Differentially expressed gene (DEG)라고 한다.
관련 논문
- xCell: digitally portraying the tissue cellular heterogeneity landscape Genome Biology : 조직별 발현정보로 조직별 heterogeneity를 확인하는 xCell 방법 개발
Table of Contents
Incoming Links #
[Codes] About (Code 0) #
Related Datasets (Dataset 1) #
Related Software Applications (SoftwareApplication 2) #
Related Books (Book 3) #
Related Products (Product 4) #
Related Articles (Article 5) #
- Biochip
- Biological network
- Chromatin
- Chromosome conformation capture
- Enhancer
- Epigenetics
- FOX
- FOXA1
- Gene set enrichment
- Genome-wide survival analysis
- Genomic imprinting
- Histone modification
- ImmGen
- Machine learning for Genomics
- Q-value
- RNA interference
- Tuxedo protocol
- eQTL
- microRNA
- 암 맞춤의학과 생물정보학
[Datasets] About (Dataset 6) #
Related Medical Conditions (MedicalCondition 7) #
Related Medical Scholarly Articles (MedicalScholarlyArticle 8) #
- Biomarkers in triple negative breast cancer: A review
- Genetic alterations of histone lysine methyltransferases and their significance in breast cancer
- Meta-analysis of the global gene expression profile of triple-negative breast cancer identifies genes for the prognostication and treatment of aggressive breast cancer
- Methods of integrating data to uncover genotype–phenotype interactions
- Prognostic value of PDL1 expression in pancreatic cancer
- The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups
- Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown
- hppRNA-a Snakemake-based handy parameter-free pipeline for RNA-Seq analysis of numerous samples
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