NucPred

NucPred predicts the probability of nuclear localization for eukaryotic protein sequences by identifying nuclear localization signals and assigning per-sequence and per-residue likelihood scores.

Key Features:

• Prediction Methodology: Applies regular expression matching and multiple program classifiers induced by genetic programming to analyze eukaryotic protein sequences and produce likelihood scores for nuclear localization at the sequence and residue levels.
• Visualization Tools: Provides visualization options to highlight predicted nuclear localization signals (NLSs) and display per-residue probability profiles.
• Integration with Biological Databases: Links predictions to supplementary biological information by integrating real and predicted data sources for validation and interpretation.

Scientific Applications:

• Protein Function Analysis: Infers protein functional roles from predicted nuclear localization and subcellular distribution.
• Disease Diagnosis: Aids identification of localization-based biomarkers by revealing aberrant nuclear localization patterns.
• Drug Discovery: Supports development of targeted therapies by providing insights into protein localization within cellular compartments.

Methodology:

Regular expression matching and genetic programming-induced multiple classifiers are applied to eukaryotic protein sequences to generate per-sequence and per-residue likelihood scores for nuclear localization.