Uncover Deeper Biological Insights with Confident Lipid Identification
LipidSearch 5.1.6 represents the latest refinement of the industry-leading software solution for high-throughput lipidomics. Developed by Mitsui Knowledge Industry (MKI) and widely used with Thermo Scientific™ mass spectrometers, this version empowers researchers to accurately identify and quantify hundreds of lipid species from complex biological samples. By streamlining the analysis of liquid chromatography-tandem mass spectrometry (LC-MS/MS) data, LipidSearch 5.1.6 accelerates the discovery of lipid biomarkers and mechanistic insights in fields from disease research to drug development.
Key Features & Enhancements in Version 5.1.6
LipidSearch 5.1.6 builds upon its robust core algorithm with improvements focused on accuracy, throughput, and user confidence.
1. High-Confidence Lipid Identification
The cornerstone of LipidSearch is its powerful and reliable identification engine.
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Comprehensive Database Search: Matches MS/MS spectra against a vast, curated database of over 1.5 million predicted lipid fragments across 46 lipid classes.
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mzLogic™ ID Scorer: This proprietary algorithm automatically re-ranks identifications based on the consistency of fragment ions across product ion scans, significantly reducing false positives and increasing confidence in results.
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Isomer Differentiation: Capable of distinguishing between lipid isomers based on characteristic fragment ions (e.g., sn-positional isomers, double bond locations).
2. Streamlined High-Throughput Workflow
From raw data to statistical results, the process is highly automated and efficient.
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Automated Peak Alignment & Normalization: Corrects for retention time drift and aligns peaks across multiple samples in a batch, ensuring consistent comparison.
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Batch Processing: Seamlessly processes large datasets from dozens or hundreds of samples, saving valuable researcher time.
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One-Cookbook™ Method Files: Pre-configured and customizable analysis methods ensure reproducibility and ease of use, standardizing workflows across a lab.
3. Accurate Relative Quantification
Obtain reliable quantitative data for comparative lipidomics.
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Peak-Based Quantification: Uses the area under the curve (AUC) of the precursor ion for relative quantification across sample groups.
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Stable Isotope Internal Standard (SIS) Support: Allows for normalization using spiked-in standards to correct for technical variation and improve quantitative accuracy.
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Group-Based Analysis: Easily compare lipid abundance between predefined sample groups (e.g., Control vs. Treated, Healthy vs. Disease).
4. Enhanced Data Visualization & Export
Interpret and communicate your findings effectively.
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Interactive Scatter Plots & PCA: Visually explore your data to identify outliers and natural clustering between sample groups.
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Lipid Class Bar Charts & Heat Maps: Quickly visualize changes in lipid class abundance or individual lipid species across conditions.
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Seamless Data Export: Export results, including peak areas and statistical analyses, to standard formats (.csv, .xlsx) for further analysis in other software.
