CritiCal-C is a cutting-edge web-based platform designed to identify and analyze critical cytosines in gene promoter sequences that play pivotal roles in gene regulation across species. Our innovative approach combines statistical methods with explainable AI to provide researchers with powerful insights into epigenetic regulation mechanisms.
Our integrated computational pipeline processes user-uploaded promoter sequences data to identify critical cytosines and assess their impact on transcriptional regulation. The platform employs sophisticated deep learning models, including ResNet9 and Grad-CAM, to assign criticality scores based on predicted influence on gene regulation.
As a cornerstone for elucidating fundamental epigenetic mechanisms in plants, our Arabidopsis species specific database integrates bisulfite sequencing (BS-Seq) and RNA-Seq data. This resource enables researchers to investigate how cytosine in promoter regions modulates gene transcription, influencing key biological processes such as growth, development, and stress responses.
Our rice database serves as a dedicated platform for investigating critical cytosine gene regulation in one of the world's most essential crops. It allows researchers to examine critical cytosine patterns under diverse environmental, developmental, and stress conditions, supporting research aimed at enhancing stress resilience, improving yield stability, and optimizing agricultural productivity.
CritiCal-C visualizes critical cytosine through powerful visualization graphs including:
These tools provide a comprehensive and user-friendly analysis environment for exploring methylation patterns and their functional implications.
By elucidating condition-specific critical cytosine patterns, CritiCal-C advances our understanding of:
This platform constitutes an essential resource for advancing plant epigenetics and functional genomics, thereby contributing to crop improvement strategies, sustainable agriculture, and global food security.