There are 316 articles for you to read.

GSVA calculation for RNA-seq data

Author: gene_x

Abstract: #------------------------------ #---- 1. prepare gene sets ---- library(org.Hs.eg.db) library(dplyr) library(AnnotationDbi) #1. Platelets data <- data.frame(

Should the inputs for GSVA be normalized or raw?

Author: gene_x

Abstract: Gene Set Variation Analysis (GSVA) is a non-parametric and unsupervised method used for estimating the variation of gene set enrichment through the samples of a gene expression matrix. Given its natur

Yops (Yersinia outer proteins) analysis 2

Author: gene_x

Abstract: > http://xgenes.com/article/article-content/162/yersinia-outer-proteins-yops-analysis/ 1. extract all plasmids of the 50 isolates with plasmids but no yopK python3 extract_plasmids_from_gff.

细胞分子的降解机制与cDNA的制备及用途

Author: gene_x

Abstract: 1. mRNA、DNA 和蛋白质都是细胞内的重要分子,它们会在一定的时候被降解以维持细胞的稳态。以下是它们在人体中被降解的方式: - mRNA降解: * 5'->3' 衰减:这是在真核生物中最常见的mRNA降解途径。当mRNA分子的5'端被去除帽子结构时,一种称为Xrn1的酶开始从5'端逐渐降解mRNA。 * 3'->5' 衰减:多蛋白复合体,如核糖核酸酶

From epidome to treeHeatmap

Author: gene_x

Abstract: 1. (namely epidome-processing step 2.6) Classification using 98% similarity. #Input Files: yycH_seqtab_nochim.csv and ../epidome/DB/yycH_ref_aln.fasta #Output Files: yycH_seqtab_ASV_s

Merkel细胞多瘤病毒大T抗原(LT)、截短的大T抗原(LTtr; MCC350)和小T抗原(sT)对初级新生儿人类真皮成纤维细胞(nHDFs)中的mRNA水平的影响

Author: gene_x

Abstract: 1: 概要: 此部分讨论研究的优点/缺点、新颖性/意义、总体执行和学术性。 1. 研究了Merkel细胞多瘤病毒大T抗原(LT)、截短的大T抗原(LTtr; MCC350)和小T抗原(sT)对初级新生儿人类真皮成纤维细胞(nHDFs)中的mRNA水平的影响。病毒cDNA通过慢病毒(sT-IRES-mCherry)和LeGO-iG2(LT/LTtr - eGFP)转导,然后在第2天为荧光蛋

Unveiling Difference in Promoter regions of MeDIP data

Author: gene_x

Abstract: 1. Select Genes of Interest: Once Emilia provides the GO term, use a database like Gene Ontology or Bioconductor's "org.Hs.eg.db" package (assuming human genes) to fetch the list of genes asso

Intragenic Methylation Patterns and CpG Island Dynamics: Insights into the Methylome

Author: gene_x

Abstract: MeDIP (Methylated DNA Immunoprecipitation) is a technique used to enrich for methylated DNA sequences. When you obtain a lot of reads mapping to the gene body in your MeDIP data, it may indicate the p

plot treeHeatmap using ggtree

Author: gene_x

Abstract: [![ggtree_and_gheatmap](/static/images/plotTreeHeatmap/ggtree_and_gheatmap.png "ggtree_and_gheatmap")](/static/images/plotTreeHeatmap/ggtree_and_gheatmap.png "ggtree_and_gheatmap") library(ggtr

Unveiling Difference in Promoter regions of MeDIP data 2

Author: gene_x

Abstract: 1. extract all genes by giving GO-terms # # Using Bioconductor in R # library(org.Mm.eg.db) # genes <- select(org.Mm.eg.db, keys="GO:0048813", columns=c("SYMBOL", "ENSEMBL"),


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