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

You might also read

Related Articles

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

Sort by
Same author

Spatial multi-omics landscape of colorectal cancer macro- and micrometastases.

Cancer cell·2026
Same author

Reversible and irreversible BTK inhibition promotes stem-like functional multipotency, persistence, and antitumor efficacy of CD19-directed CAR T cells in mantle cell lymphoma.

Leukemia·2026
Same author

A study on the dynamic differences and component correlations of astringency in green tea, black tea and oolong tea based on TI/TDS and LC-MS.

Food chemistry: X·2026
Same author

Pan-cancer spatial atlas of tertiary lymphoid structures.

Science (New York, N.Y.)·2026
Same author

A Spatial Atlas of Muscle-Invasive Bladder Cancer Reveals Lineage-Specific Vulnerabilities and Immune Architecture.

Cancer discovery·2026
Same author

First-in-human use of recombinant IL-7 to potentiate antigen-specific T cell therapy: a single patient case study.

Journal for immunotherapy of cancer·2026

Related Experiment Video

Updated: Jun 25, 2025

Quantification of Orofacial Phenotypes in Xenopus
09:26

Quantification of Orofacial Phenotypes in Xenopus

Published on: November 6, 2014

9.7K

DeepFace: Deep-learning-based framework to contextualize orofacial-cleft-related variants during human embryonic

Yulin Dai1, Toshiyuki Itai1, Guangsheng Pei1

  • 1Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.

HGG Advances
|May 26, 2024
PubMed
Summary

DeepFace, a new AI model, identifies functional variants in orofacial clefts (OFCs) by analyzing epigenomic data. It highlights specific SNPs with temporal roles and implicates trophoblast cells in OFC development.

Keywords:
SNP activity difference predictionconvolutional neural networkepigenomic assaygenome-wide association studieshuman embryonic craniofacial developmentnoncoding variantorofacial cleftsvariant function

More Related Videos

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
10:23

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Published on: September 8, 2023

2.7K
Visualization of Craniofacial Development in the sox10: kaede Transgenic Zebrafish Line Using Time-lapse Confocal Microscopy
06:35

Visualization of Craniofacial Development in the sox10: kaede Transgenic Zebrafish Line Using Time-lapse Confocal Microscopy

Published on: September 30, 2013

12.9K

Related Experiment Videos

Last Updated: Jun 25, 2025

Quantification of Orofacial Phenotypes in Xenopus
09:26

Quantification of Orofacial Phenotypes in Xenopus

Published on: November 6, 2014

9.7K
Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
10:23

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Published on: September 8, 2023

2.7K
Visualization of Craniofacial Development in the sox10: kaede Transgenic Zebrafish Line Using Time-lapse Confocal Microscopy
06:35

Visualization of Craniofacial Development in the sox10: kaede Transgenic Zebrafish Line Using Time-lapse Confocal Microscopy

Published on: September 30, 2013

12.9K

Area of Science:

  • Genomics
  • Developmental Biology
  • Artificial Intelligence

Background:

  • Orofacial clefts (OFCs) are common congenital birth defects with many identified genetic loci, but causal variants remain largely unknown.
  • Previous studies have identified genetic associations for cleft lip with or without cleft palate (CL/P) and cleft palate alone (CP).

Purpose of the Study:

  • To develop a novel computational model, DeepFace, for assessing the functional impact of genetic variants in OFCs.
  • To leverage epigenomic data from critical human embryonic craniofacial development stages to predict variant function.

Main Methods:

  • Developed DeepFace, a convolutional neural network, to predict variant functional impact using SNP Activity Difference (SAD) scores.
  • Trained the model on 204 epigenomic assays from human embryonic development (post-conception week 4-10).
  • Analyzed SAD scores for OFC-associated single nucleotide polymorphisms (SNPs) and assessed cell-type specificity.

Main Results:

  • DeepFace achieved a median Pearson correlation of 0.50-0.83 between predicted and actual epigenetic features.
  • OFC-associated SNPs showed significantly higher SAD scores, indicating context-specific functional impact.
  • Identified six SNPs with linear SAD score relationships across development, suggesting temporal regulatory roles.
  • Trophoblast cells showed the highest enrichment of OFC risk signals.

Conclusions:

  • DeepFace effectively utilizes epigenomic data to prioritize OFC variants by predicting their functional and regulatory roles.
  • The model offers new insights into the temporal and cell-type-specific mechanisms underlying OFC development.
  • DeepFace has the potential to be extended for studying other complex diseases and traits.