DESSO-DB

DESSO-DB provides motif prediction and analysis to identify cis-regulatory motifs and transcription factor binding signals from ChIP-seq, ATAC-seq, and CLIP-seq datasets.

Key Features:

• Motif prediction and visualization: Provides motif predictions and visual representations derived from 690 ENCODE human ChIP-seq datasets (161 transcription factors across 91 cell lines) and 1,677 additional ChIP-seq datasets (547 transcription factors in 359 cell lines).
• Deep learning-based prediction (DESSO): Employs the in-house DESSO deep learning (DL) models for motif prediction.
• Dataset coverage: Aggregates motif analysis results from 126 cancer ChIP-seq datasets and 55 RNA CLIP-seq datasets.
• Motif finding and scanning: Performs motif finding and motif scanning on ChIP-seq and ATAC-seq datasets.

Scientific Applications:

• Transcription factor binding site identification: Enables detection and characterization of transcription factor binding signals from ChIP-seq and CLIP-seq data.
• Regulatory element identification: Supports identification of cis-regulatory motifs and candidate regulatory elements across cell types.
• Gene regulatory network analysis: Facilitates studies aimed at elucidating gene regulatory interactions and networks.

Methodology:

Applies the DESSO deep learning models to predict motifs and performs motif finding and scanning on ChIP-seq, ATAC-seq, and CLIP-seq datasets.