№ files_lp_4_process_2_87164
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Supplementary tables provide primer sequences and TP53 mutations observed in patient samples, while figures show methylation distributions and associations with survival outcomes in gastric cancer.
Year:
2026
Region / City:
Not specified
Subject:
TP53 mutations, DNA methylation, GC patients
Document Type:
Supplementary material
Institution:
Not specified
Author:
Not specified
Target Audience:
Researchers and clinicians in molecular genetics and oncology
Methods:
Sanger sequencing, pyrosequencing, primer design
Data Source:
Patient tumor samples
Genomic Reference:
GRCh37: Genome Reference Consortium human build 37
Figures Included:
Methylation distribution and survival analysis
Tables Included:
Primer sequences, TP53 mutations
Clinical Context:
Neoadjuvant and adjuvant chemotherapy subgroups
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The product description is provided for reference. Actual content and formatting may differ slightly.
Year:
2023
Region / City:
N/A
Subject:
Genomic analysis, liver organoids
Document Type:
Research Methodology
Organization / Institution:
N/A
Author:
N/A
Target Audience:
Researchers, genomic scientists
Period of Validity:
N/A
Approval Date:
N/A
Date of Changes:
N/A
Year:
2021
Region / City:
International
Topic:
Cancer Research
Document Type:
Supplementary Data
Institution:
Not specified
Author:
Not specified
Target Audience:
Researchers in cancer immunotherapy
Period of Validity:
Not specified
Approval Date:
Not specified
Date of Changes:
Not specified
Year:
2026
Region / City:
N/A
Topic:
Immune cell score analysis, TP53 mutation, HRD status, estrogen receptor status
Document type:
Figure
Organization / Institution:
N/A
Author:
N/A
Target audience:
Researchers, medical professionals
Period of validity:
N/A
Approval date:
N/A
Date of modifications:
N/A
Year:
2025
Note:
Region / city
Topic:
Central nervous system tumor diagnostics
Document type:
Scientific article
Author:
Aldape K, Capper D, von Deimling A, Giannini C, Gilbert MR, Hawkins C, Hench J, Jacques TS, Jones D, Louis DN, Mueller S, Orr BA, Nasrallah M, Pfister SM, Sahm F, Snuderl M, Solomon D, Varlet P, Wesseling P
DOI:
10.1093/noajnl/vdae228
PMID:
39902391
PMCID:
PMC11788596
Context:
A scientific article offering guidelines on the use of DNA methylation profiling for diagnosing tumors in the central nervous system.
Year:
2017
Region / City:
Netherlands, Canada
Topic:
DNA Methylation Analysis
Document Type:
Research Supplementary Materials
Institution:
Not specified
Author:
Forest et al.
Target Audience:
Researchers in genomics and molecular biology
Period of validity:
Not specified
Date of approval:
Not specified
Date of changes:
Not specified
Document type:
Supplementary material
Subject:
Differential DNA methylation analysis
Keywords:
DNA methylation, DMPs, DMRs, CpG island, GO enrichment, KEGG pathway, polyps, normal tissue
Biological context:
Comparison between polyp and control tissue samples
Analytical methods:
Correlation heatmap, box plot normalization, differential methylation analysis, GO and KEGG enrichment analysis
Genes mentioned:
LPA, SVIL, KRT18, MYH13 and others listed in enrichment tables
Statistical measures:
Pearson’s correlation coefficient, T value, pvalue, adjusted pvalue, qvalue
Biological processes highlighted:
Regulation of membrane potential, axon guidance, extracellular matrix organization, ion transmembrane transport
Abbreviations:
TSS (transcription start site), P (polyp), C (control), FEM (Functional epigenetic modules), DMP (differentially methylated position), DMR (differentially methylated region)
Year:
2022
Region / city:
Global
Theme:
DNA methylation analysis
Document type:
Product datasheet
Organization / institution:
Abcam
Author:
Abcam
Target audience:
Researchers in molecular biology, genetics, and biochemistry
Validity period:
Not specified
Approval date:
21 June 2022
Modification date:
Not specified
Year:
2026
Institution:
Johns Hopkins Hospital, Asan Medical Center
Study Type:
Molecular biology study
Methods:
Droplet digital PCR, MSP, bisulfite sequencing, ddQMSP, mRNA expression analysis
Biomarkers:
SOX17, ACTB, KRAS, GNAS, seven marker genes
Sample Type:
Surgically aspirated pancreatic cyst fluid, pancreatic cell lines, normal pancreatic tissue
Sample Size:
183 patients (discovery and validation sets)
Pathology:
IPMN, MCN, SCN, HGD, INV, IGD, LGD
Data Presentation:
1-D ddPCR plots, heat maps, AUC values, box plots, correlation plots
Statistical Measures:
Mean ± standard deviation, coefficient of determination (R²), coefficient of variation (% CV), 95% confidence interval
Experimental Conditions:
5-Aza-2′-deoxycytidine, trichostatin A treatment
Comparisons:
Between hospitals (JHH vs AMC), among cyst types, stratified by mutation status and histologic grade
Year:
2025
Region / city:
China
Subject:
Nasopharyngeal carcinoma, RNA modification
Document type:
Original research article
Institution:
University hospital, Otolaryngology department
Author:
Not specified
Target audience:
Researchers, clinicians
Period of validity:
Not specified
Approval date:
Not specified
Date of revisions:
Not specified
Year:
Not specified
Region / City:
Not specified
Subject:
DNA methylation, LRP11, HCC
Document Type:
Supplementary figure
Organization / Institution:
SMART database
Author:
Not specified
Target Audience:
Researchers in genomics
Effective Period:
Not specified
Approval Date:
Not specified
Date of Changes:
Not specified
Year:
2026
Study Population:
Whites
Sample Type:
Plasma, Urine
Disease Focus:
Cancer
Number of Cancer Cases:
41
Number of Control Cases:
11
Genes Analyzed:
CDO1, TAC1, HOXA7, HOXA9, SOX17, ZFP42
Parameters Measured:
Sensitivity, Specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), Area Under the Curve (AUC), 95% Confidence Interval
Data Presentation:
Tabular
Cutoff Criteria:
Detectable vs. Non-detectable
Combined Analysis:
At least 3 positive genes
Year:
2023
Region / City:
Denmark
Theme:
Cervical Cancer Screening, HPV Testing, DNA Methylation
Document Type:
Research Article
Organization / Institution:
University Research Clinic for Cancer Screening, Aarhus University
Authors:
Mette Tranberg, Severien Van Keer, Albertus T Hesselink, Pia Nørgaard, Rikke Brøndum, Chunsen WU, Line Winther Gustafson, Anne Hammer, Pinar Bor, Karen Omann Binderup, Christina Blach, Alex Vorsters, Renske Steenbergen
Target Audience:
Researchers, Healthcare Professionals, Medical Community
Period of Application:
Not specified
Approval Date:
Not specified
Date of Changes:
Not specified
Study Registration:
Clinicaltrials.gov: NCT05065853
Keywords:
DNA methylation, cervical cancer screening, HPV DNA testing, urinary HPV testing, early detection of cancer/methods
Abstract:
The study evaluates the performance of ASCL1/LHX8 DNA methylation markers and HPV genotyping in first-void urine samples for detecting high-grade cervical intraepithelial neoplasia (CIN2+) and cervical cancer in HPV-positive women, comparing it with clinician-collected cervical samples.
Document Type:
Supplementary data description
Content Type:
Data file index and variable definitions
Research Field:
Epigenetics; Neurodegenerative disease research
Disease Focus:
Parkinson’s disease
Biological Material:
Human prefrontal cortex nuclei samples
Cell Types:
NeuN+ neuronal nuclei; SOX10+ oligodendrocyte nuclei; double negative glial nuclei
Genetic Factor:
GBA1 variant status
Data Types:
Sample metadata; quality control metrics; cell composition estimates; differential DNA methylation results; gene ontology analysis
Analytical Methods:
EWAS (epigenome-wide association study); linear regression analysis; interaction models; Tukey HSD test; ANOVA; χ² test
Laboratory Methods:
EPIC DNA methylation array; bisulfite conversion; fluorescence-activated nuclei sorting (FANS)
Variables Included:
PD status; GBA1 status; sex; dementia status; Braak Lewy body stage; Braak neurofibrillary tangle stage; methylation signal intensity; principal components; genomic site coordinates
Sample Groups:
PD-GBA1; PD-non-GBA1; Control-GBA1; Control-non-GBA1
Brain Region:
Prefrontal cortex
Number of Supplementary Files:
14
File Formats:
XLS spreadsheets
Key Measurements:
DNA methylation beta values; cell composition fractions; quality control metrics; differential methylation statistics
Year:
2021
Region / City:
Princeton
Theme:
Biology, Protein Synthesis, Genetics
Document Type:
Lesson Plan
Institution:
Princeton High School
Authors:
Emily Leitnick & Arionne Smith
Target Audience:
High School Students (Biology Class)
Duration:
10 days
Date of Approval:
8/9/21
Date of Revisions:
Not specified
Period of Validity:
Second Six Weeks Period
Year:
2023
Region / city:
Not specified
Topic:
Cancer research, EGFR mutations
Document type:
Research figure
Organization / institution:
Not specified
Author:
Not specified
Target audience:
Researchers, oncologists
Effective period:
Not specified
Approval date:
Not specified
Modification date:
Not specified
Year:
N/A
Region / City:
N/A
Theme:
Mutation Frequency, Bacterial Genetics
Document Type:
Research Data
Author:
N/A
Target Audience:
Researchers in Genetics, Microbiology
Period of Action:
N/A
Date of Approval:
N/A
Date of Modifications:
N/A
Year:
2007
Region / city:
Not specified
Topic:
Mutagenesis, Genetics, Crop Improvement
Document type:
Educational Module
Organization / Institution:
Not specified
Author:
Not specified
Target audience:
Researchers, students in the field of genetics and plant breeding
Period of validity:
Not specified
Approval date:
Not specified
Modification date:
Not specified
Year:
2015
Region / City:
Nice, France
Field:
Hepatology, Virology, Infectious Diseases
Document Type:
Original Article, Observational Study
Institution:
Archet Hospital, Centre Hospitalier Universitaire
Author(s):
Alissa Naqvi, Valérie Giordanengo, Brigitte Dunais, Francine de Salvador-Guillouet, Isabelle Perbost, Jacques Durant, Pascal Pugliese, Aline Joulié, Pierre Marie Roger, Eric Rosenthal
Target Audience:
Medical Researchers, Healthcare Professionals, Clinicians
Period of Study:
August 2011 - October 2013
Approval Date:
2015
Date of Last Revision:
March 17, 2015
Date Published:
July 21, 2015
Year:
2023
Region / city:
Not specified
Topic:
Radiomics, Machine learning, EGFR mutation detection
Document type:
Supplementary material
Author:
Not specified
Target audience:
Researchers, Medical professionals
Period of validity:
Not specified
Approval date:
Not specified
Date of changes:
Not specified
Contextual description:
Supplementary material for a scientific manuscript discussing the radiomic detection of EGFR mutations in non-small cell lung cancer (NSCLC) using machine learning techniques.
Year:
2026
Region / City:
Not specified
Subject:
Genetics and Mutations
Document Type:
Educational Worksheet
Author:
Not specified
Target Audience:
Students
Topics Covered:
DNA sequence changes, types of mutations, gene therapy, effects of mutations, genetic diseases, safety precautions