There are 219 articles for you to read.

Small RNA sequencing processing in the example of smallRNA_7

Author: gene_x

Abstract: 1. adapter sequence Lexogen small RNA-Seq kit some common adapter sequences from different kits for reference: - TruSeq Small RNA (Illumina): TGGAATTCTCGGGTGCCAAGG - Small RNA Kits V1 (Il

Regulating Gene Expression in Diploid Organisms with Different Haplotypes

Author: gene_x

Abstract: If two haplotypes in a diploid organism are different, then the genome sequences for those haplotypes are also different. These genetic differences can indeed impact gene expression, and there are var

Peak and Motif analyses in Promoters

Author: gene_x

Abstract: * ./1_generate_promoter_sequences.py gencode.v43.annotation.gtf.db [1_generate_promoter_sequences.py](/static/peaks_and_motifs_in_promoters/1_generate_promoter_sequences.py "1_generate_promoter_sequ

Density of motif plots and its statistical tests

Author: gene_x

Abstract: [![Density_of_GRGGC_Motifs](/static/peaks_and_motifs_in_promoters/Density_of_GRGGC_Motifs.png "Density_of_GRGGC_Motifs")](/static/peaks_and_motifs_in_promoters/Density_of_GRGGC_Motifs.png "Density_of_

Small RNA processing

Author: gene_x

Abstract: Small RNA sequencing is a type of RNA-sequencing (RNA-seq) that specifically targets and sequences small RNA molecules in a sample. RNA-seq is a technique that uses next-generation sequencing (NGS) t

洛那法尼(lonafarnib):从抗癌症到抗病毒的多功能药物

Author: huang

Abstract: > Drug repurposing screen identifies lonafarnib as respiratory syncytial virus fusion protein inhibitor 0. A Promising Farnesyltransferase Inhibitor for Cancer and Progeria Treatment Lonafarnib

Setup conda environments

Author: gene_x

Abstract: 1. install rnaseq on sage #-- version 2 -- conda install -c conda-forge mamba mamba create -n rnaseq -c conda-forge -c bioconda -c defaults python fastqc trim-galore star hisa

ChIP-seq using HOMER (-style factor, findPeaks + default getDifferentialPeaksReplicates.pl)

Author: gene_x

Abstract: 1. nextflow ChIP-seq run for NHDF_p783 #under Raw_Data for ChIP-seq ln -s ./230306_NB501882_0417_AHMVHHBGXN/2023_022_nf_denise/nf859/3_NHDF_Donor_1_p783_input_S5_R1_001.fastq.gz p783

RNA-seq data analysis on bacterial genome

Author: gene_x

Abstract: 1. prepare input reads and samplesheet ln -s ./F23A430001245_SEPiovzP/soapnuke/clean/EX_15_min_A/EX_15_min_A_1.fq.gz . ln -s ./F23A430001245_SEPiovzP/soapnuke/clean/EX_15_min_A/EX_15_

Prepare the databases for vrap

Author: gene_x

Abstract: 1. I used an strategy, at first annotate the contigs using the virus-speicific data and bacteria-speicific data, then using more general databases nt and nr. The results are as attached. For some samp


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