TargetSearch

TargetSearch pre-processes GC-MS data to enable accurate metabolite profiling through iterative retention time correction and automated quantification workflows.

Key Features:

• High Throughput Capability: Handles very large GC-MS datasets to support high-throughput metabolite quantification.
• Iterative Retention Time Correction: Iteratively corrects and updates retention time indices to improve metabolite identification accuracy.
• Comprehensive Validation: Validated using known chemical standard mixtures and biological experiments.
• Performance Optimization: Implemented primarily in R with computationally intensive functions in C to optimize speed and performance.
• Reduction of Manual Curation: Automates preprocessing steps to reduce manual curation and associated subjectivity.

Scientific Applications:

• Systems-level metabolite profiling: Supports metabolite profiling in systems-level biology by pre-processing GC-MS datasets.
• High-throughput experiments: Enables large-scale experimental designs that require processing of extensive GC-MS data.
• Pharmacology: Applicable to metabolomics studies in pharmacology for metabolite quantification and comparison.
• Toxicology: Applicable to metabolomics investigations in toxicology for detecting metabolic perturbations.
• Plant biology: Supports metabolite profiling applications in plant biology using GC-MS data.

Methodology:

Pre-processes GC-MS data with iterative retention time index correction and automated preprocessing; implemented primarily in R with computationally intensive routines in C.