iLearnPlus

iLearnPlus provides sequence-based machine-learning analysis and prediction to model relationships between sequence, structure, and function in DNAs, RNAs, and proteins.

Key Features:

• Sequence-based analysis and prediction: Supports analysis and prediction for nucleic acid and protein sequences to interrogate sequence–structure–function relationships in DNAs, RNAs, and proteins.
• Automated workflows: Automates feature extraction, model construction and deployment, predictive performance assessment, statistical analysis, and data visualization.
• Feature sets: Provides a wide range of feature sets that encode information from input sequences.
• Algorithms: Implements over twenty machine-learning techniques, including various deep-learning approaches.
• Predictive model deployment: Facilitates development and deployment of predictive models for sequence-based tasks.

Scientific Applications:

• lncRNA prediction: Predicts long noncoding RNAs (lncRNAs) from RNA transcripts.
• Crotonylation site identification: Identifies crotonylation sites in protein chains.
• Sequence–structure–function modeling: Enables modeling of sequence, structure, and function relationships across DNAs, RNAs, and proteins.

Methodology:

Feature extraction from sequences; machine-learning model construction and deployment using over twenty algorithms including deep-learning; predictive performance assessment; statistical analysis; and data visualization.