ConnecTF

ConnecTF constructs and refines gene regulatory networks (GRNs) by integrating TF-centric high-throughput sequencing and TF-target binding and regulation datasets to identify transcription factor (TF) targets and network pathways.

Key Features:

• Species-Independent Analysis: Applicable across different species for comparative and systems biology studies.
• Integration of Omic Data: Combines TF-centric omic datasets, including genome-wide TF-target gene binding and regulation data.
• Validation and Refinement: Enables construction of validated GRNs using precision/recall assessments and pruning to improve network accuracy.
• Network Walking: Maps pathways from master TFs to their direct and indirect targets to trace regulatory cascades.
• Public TF-target Interaction Database: Provides interaction datasets via https://ConnecTF.org, including Arabidopsis with 3,738,278 interactions for 423 TFs and Maize with 839,210 interactions for 139 TFs.

Scientific Applications:

• Abscisic Acid Signaling: Integrates TF-target regulation and binding datasets to identify key TFs and potential partners involved in abscisic acid signaling.
• Nitrogen Signaling: Applies precision/recall analysis to refine inferred GRNs related to nitrogen signaling.
• Network Path Charting: Uses Network Walking to trace pathways from master TFs such as NLP7 to secondary and indirect targets within nitrogen signaling networks.

Methodology:

Integration of TF-centric high-throughput sequencing datasets and genome-wide TF-target binding and regulation data across studies, automated construction and refinement of inferred GRNs using precision/recall assessments and pruning, and application of Network Walking to map direct and indirect TF-target pathways.