№ files_lp_4_process_3_076382
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Analysis of RNA-seq data from wheat and identification of genotypic and phenotypic associations relevant to plant breeding and genetics.
Year:
2023
Region / City:
Yangling
Subject:
Genomics, Plant Biology, Wheat Breeding
Document Type:
Research Article
Institution:
Not specified
Author:
Not specified
Target Audience:
Researchers in Plant Genomics and Breeding
Period of Validity:
Not applicable
Date of Approval:
Not applicable
Date of Changes:
Not applicable
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Year:
Not specified
Region / City:
Not specified
Topic:
Statistical evaluation, genetic interaction networks
Document Type:
Research Article
Organization / Institution:
Not specified
Author:
Not specified
Target Audience:
Researchers in genetic and statistical fields
Period of validity:
Not specified
Approval Date:
Not specified
Date of changes:
Not specified
Context:
The document presents a statistical evaluation of pleiotropic-epistatic network reconstruction in genetics using simulation scenarios to assess the accuracy of time-varying genotypic effect estimates.
Subject:
Biology
Topic:
Genetic variants and phenotypes
Key concepts:
Mutation, gene transcription, translation, protein synthesis, RNA polymerase binding, amino acid sequence
Curriculum references:
SB3.9B; SB3.10B
Document type:
Lesson plan
Educational level:
Secondary education
Components:
Objectives; Learning outcomes; Quick Quiz; Starters; Exploring activities; Worksheets; Safety guidance; Equipment list
Resources referenced:
ALDS presentation SB3e Genetic variants and phenotypes objectives; ALDS presentation SB3e Quick Quiz; Worksheet SB3e.1; Worksheet SB3e.2; Student Book SB3d Protein synthesis
Assessment methods:
Quick Quiz; Progression questions; Confidence level scoring; Peer checking activity
Practical activities:
Protein modelling with beads; Genetic code transcription and translation exercise
Safety considerations:
Eye protection required; Slip hazard from dropped beads
Year:
2023
Region / City:
Not specified
Topic:
Dendritic phenotyping, RNAi stocks
Document type:
Research data
Organization / Institution:
Not specified
Author:
Not specified
Target audience:
Researchers in neuroscience, specifically in the field of neuronal phenotyping
Validity period:
Not specified
Approval date:
Not specified
Date of changes:
Not specified
Document type:
Supplementary tables
Study population:
HIV-positive (n=142) and HIV-negative (n=73) participants
Subgroup analysis:
HIV-negative participants (n=71 with pre-; n=73 with post- measurements)
Measured variables:
CD4 T cell phenotypes, CD8 T cell phenotypes, monocyte phenotypes
Phenotype categories:
Differentiation, Activation Profiles, Inflammation/Exhaustion Profiles, Senescence Profiles
Monocyte subsets:
Classical, Intermediate, Non-Classical
Pulmonary function measures:
FEV1, FVC, FEV1/FVC, DLCO
Statistical methods:
Two-sample t-test; linear regression models with adjustment for HBV infection, HCV infection, smoking pack-years, body-mass index, marijuana use, crack cocaine use, injection drug use, tuberculosis, pneumonia
Data presentation:
Median (IQR); standardized beta coefficients
Reference standards:
NHANES III predicted lung function values
Significance thresholds:
P < 0.05 with Bonferroni correction (P=0.05/112)
Year:
2026
Region / City:
Honolulu, HI, USA; Ann Arbor, MI, USA
Topic:
Hepatocellular carcinoma genetics
Document type:
Research article
Institution:
University of Hawaii Cancer Center; University of Michigan
Authors:
Kumardeep Chaudhary, Olivier B Poirion, Liangqun Lu, Sijia Huang, Travers Ching, Lana X Garmire
Funding:
NIEHS K01ES025434, P20 COBRE GM103457, NICHD R01 HD084633, NLM R01LM012373, Hawaii Community Foundation 14ADVC-64566
Target audience:
Biomedical researchers, oncologists, bioinformaticians
Methods:
Multi-modal meta-analysis, mutation profiling, Kaplan-Meier survival analysis, bipartite graph analysis
Sample size:
1494 HCC samples across 6 cohorts
Key findings:
Associations of consensus driver genes with phenotypes, miR expression, CNV, and overall survival
Supplementary materials:
Figures S1–S8, Table S1, File S1
Document type of source:
Peer-reviewed scientific publication
Year:
2016–2021
Field:
Cancer Genomics
Research Topic:
Lung Adenocarcinoma (LUAD) Molecular Subtypes
Document Type:
Supplementary Scientific Notes and Figures
Study Context:
Comparative analysis with Chen et al. 2016 study and related genomic datasets
Data Sources:
TCGA LUAD cohort; CCLE LUAD cell lines; CPTAC LUAD cohort
Analytical Methods:
mRNA expression clustering; GSVA pathway analysis; MutSig2CV mutation analysis; GISTIC2.0 copy number analysis; Cox proportional hazards modeling
Key Molecular Features:
STK11/KRAS co-mutation; MET activation; stem cell gene signature
Subtype Classification:
Five LUAD mRNA expression subtypes (S1–S5)
Comparative Subtypes Referenced:
PP, PI, TRU expression-based subtypes
Genomic Data Types:
DNA copy number; DNA methylation; mRNA expression; miRNA expression; protein expression
Immune Phenotyping Source:
TCGA H&E image–based immune scores
Gene Signature Components:
C6orf62; DNER; NELL2; LATS2; LGR5; PTPRO; LRIG1; PABPC1; NT5E; SET
Referenced Studies:
Chen et al., 2016; Huang et al., 2021; Thorsson et al., 2018
Organism:
Drosophila melanogaster
Data types:
ChIP-seq and RNA-seq
Experimental conditions:
wt and cuff homozygous mutant ovaries
Replicates:
Three replicates per condition for RNA-seq and Pol2 ChIP-seq; two replicates for Cuff ChIP-seq
Reference genome version:
FlyBase v5.41
Transposon dataset versions:
FlyBase v9.41 and D_mel_transposon_sequence_set.fasta
Software and tools:
cutadapt v1.2.1; bowtie2 v2.0.0-beta7; samtools v0.0.19; MACS2 v2.0.10.20130501; tophat2 v2.0.8; bedtools v2.17.0; DESeq v1.16.0
Statistical methods:
IDR protocol with threshold 0.05; Benjamini-Hochberg multiple testing correction
Genomic features analyzed:
protein-coding genes; rRNA; snRNA; snoRNA; piRNA clusters; canonical transposons
Number of Cuff peaks (genome-wide):
937 at IDR 0.05
Number of Cuff peaks (transposons):
149 at q-value < 0.05
Visualization platform:
UCSC Genome Browser
Scope:
Genome-wide alignment, peak detection, and differential expression analysis
Year:
2026
Source repository:
European Nucleotide Archive (ENA)
Project ID:
PRJEB14210
Data type:
RNA sequencing
Processing steps:
Filtering, de novo assembly, read mapping
Software tools:
SortMeRNA, cutadapt, PRINSEQ, IDBA-UD, IDBA-tran, Bowtie2, samtools
Organism/environment:
Aerobic and anaerobic microbial samples
Output formats:
FASTQ, SAM, BAM, contigs
Read statistics:
Number of reads, base counts, alignment rates
Processing date:
2026
Year:
2026
Organism:
Oithona similis
Type of document:
Supplementary material
Methods:
PCR, qRT-PCR, RNA-seq
Content:
Primer sequences for dsRNA synthesis, qRT-PCR assays, and DEG validation
Genes analyzed:
Multiple O. similis gene clusters
Target molecules:
dsAllim, dsOslim, dsGFP
Purpose:
Gene expression analysis and validation
Laboratory techniques:
Molecular biology, genetic analysis