Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Biostatistics: Overview01:20

Biostatistics: Overview

396
Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
396
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

860
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
860

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Stapokibart reduces blood eosinophil counts in patients with moderate-to-severe atopic dermatitis: a post-hoc analysis from phase II and phase III clinical trials.

The Journal of dermatological treatment·2026
Same author

Circulating metabolites in plasma reveal potential target of lung cancer prevention: insights from fatty acids pathway.

Nutrition journal·2026
Same author

Stapokibart provides significant improvements in signs and symptoms of atopic dermatitis irrespective of prior systemic treatment: a post-hoc analysis of a phase 3 trial.

The Journal of dermatological treatment·2026
Same author

Dermatitis Artefacta: A Multidisciplinary Approach.

The American journal of case reports·2026
Same author

Social isolation, loneliness, genetic susceptibility, and the risk of hypothyroidism.

Social neuroscience·2026
Same author

Advancing synthetic biology with engineered chemically inducible gene regulatory systems.

Biotechnology advances·2026

Related Experiment Video

Updated: Oct 3, 2025

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.4K

A computational system for Bayesian benchmark dose estimation of genomic data in BBMD.

Chao Ji1, Andrew Weissmann2, Kan Shao1

  • 1Department of Environmental and Occupational Health, School of Public Health, Indiana University - Bloomington, Bloomington, IN 47405, USA.

Environment International
|February 12, 2022
PubMed
Summary

Bayesian Benchmark Dose (BMD) modeling using genomic data offers a robust approach to chemical risk assessment. The new Bayesian BMD (BBMD) system quantifies uncertainty, providing more reliable dose-response estimates than traditional methods.

Keywords:
BBMDBayesianBenchmark doseGenomic data

More Related Videos

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation
10:33

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Published on: September 4, 2017

15.9K
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

9.1K

Related Experiment Videos

Last Updated: Oct 3, 2025

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.4K
Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation
10:33

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Published on: September 4, 2017

15.9K
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

9.1K

Area of Science:

  • Toxicology
  • Genomics
  • Computational Biology

Background:

  • Existing methods for benchmark dose (BMD) estimation from transcriptomics data often ignore model uncertainty, leading to overconfident inferences.
  • Current software typically uses maximum likelihood estimation, potentially resulting in inadequate decisions for chemical risk assessment.
  • Short-term in vivo transcriptomics studies can provide BMD estimates comparable to long-term toxicity assessments.

Purpose of the Study:

  • To develop a web-based system, Bayesian BMD (BBMD), for genomic dose-response modeling and BMD estimation.
  • To quantitatively address uncertainty from various sources in BMD estimation using genomic data.
  • To compare the performance of BBMD with existing tools like BMDExpress.

Main Methods:

  • The Bayesian BMD (BBMD) system was developed based on the National Toxicology Program Approach to Genomic Dose-Response Modeling.
  • Bayesian model averaging was applied for BMD estimation and pathway analyses.
  • The system offers flexibility in data preparation and uncertainty characterization.

Main Results:

  • BBMD was validated using microarray datasets and the Open TG-Gates database.
  • Short-term transcriptional BMD values from BBMD showed high correlation with long-term apical BMD values (R = 0.78-0.91).
  • BBMD provided more adequate BMD estimates compared to BMDExpress, with fewer extreme values and no calculation failures. Pathway analysis in BBMD yields conservative estimates.

Conclusions:

  • Genomic dose-response modeling is crucial for chemical risk assessment.
  • BBMD is a robust, user-friendly tool for analyzing genomic dose-response data.
  • BBMD effectively quantifies uncertainty, improving the reliability of risk assessment decisions.