Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Predicting the Epigenome from DNA Sequence - Are We There Yet?

Computational Genomics Summer Institute CGSI via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a comprehensive lecture on predicting the epigenome from DNA sequences presented by Hae Kyung Haky Im at the Computational Genomics Summer Institute (CGSI) 2023. Delve into the background of epigenome prediction, its importance in genomics, and the components of genome-wide association studies (GWAS). Examine gene-level association techniques and methods for predicting expression levels, while acknowledging the limitations of current approaches. Investigate deep learning methods applied to epigenome prediction, including data analysis, prediction models, and correlation studies. Learn about the Gene Pack 6 team's innovative ideas, such as TFprint and logistic regression for predicting epigenome features. Discover insights into transcription factor binding prediction and t-test results for identifying the best binding sites. Gain a thorough understanding of transcription factor scanning techniques and their applications in epigenome research.

Syllabus

Introduction
Background
Why Predict the Epigenome
Components of GWAS
Gene level association
Predicting expression levels
Limitations
Deep Learning Methods
Data
Prediction
Correlation
Gene Pack 6
Team
Idea
TFprint
Logistic Regression
Predicting Epigenome
Transcription Vector Binding
Ttest Results
Best site
Transcription Factor Scan
Summary

Taught by

Computational Genomics Summer Institute CGSI

Reviews

Start your review of Predicting the Epigenome from DNA Sequence - Are We There Yet?

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.