PATO

PATO predicts genome-wide long non-coding RNA (lncRNA)-DNA triple helices to identify potential lncRNA–DNA triplex interactions from next-generation sequencing (NGS) datasets.

Key Features:

• Efficiency and Speed: Processes over 60 GB of sequence data in approximately one hour on a two-socket server, enabling genome-scale analysis of NGS datasets.
• Modern Architecture: Implements computational strategies tailored for contemporary NGS data and large-scale sequence processing.
• High Prediction Accuracy: Enables exhaustive exploration of potential triplex-forming solutions to improve prediction precision of lncRNA-DNA triple helices.

Scientific Applications:

• lncRNA regulatory roles: Predicts RNA-DNA triplexes to support studies of long non-coding RNA involvement in chromatin dynamics.
• Mechanisms of direct hybridization: Aids elucidation of direct RNA–DNA hybridization mechanisms underlying triplex formation.
• Gene regulation and epigenetics: Supports investigation of gene regulation and epigenetic modifications mediated by lncRNA-DNA interactions.

Methodology:

Uses a computational algorithm that integrates modern techniques to efficiently scan genomic sequences, identify potential lncRNA-DNA triplex formations, and explore a large solution space of possible RNA-DNA interactions.