title: Lipid-Pro: a computational lipid identification solution for untargeted lipidomics on data-independent acquisition tandem mass spectrometry platforms.
abstract: A major challenge for mass spectrometric-based lipidomics, aiming at describing all lipid species in a biological sample, lies in the computational and bioinformatic processing of the large amount of data that arises after data acquisition. Lipid-Pro is a software tool that supports the identification of lipids by interpreting large datasets generated by liquid chromatography--tandem mass spectrometry (LC-MS/MS) using the advanced data-independent acquisition mode MS(E). In the MS(E) mode, the instrument fragments all molecular ions generated from a sample and records time-resolved molecular ion data as well as fragment ion data for every detectable molecular ion. Lipid-Pro matches the retention time-aligned mass-to-charge ratio data of molecular- and fragment ions with a lipid database and generates a report on all identified lipid species. For generation of the lipid database, Lipid-Pro provides a module for construction of lipid species and their fragments using a flexible building block approach. Hence, Lipid-Pro is an easy to use analysis tool to interpret complex MS(E) lipidomics data and also offers a module to generate a user-specific lipid database.
  
  
  METHODS
  Lipid-Pro is freely available at: http://www.neurogenetics.biozentrum.uni-wuerzburg.de/en/project/services/lipidpro/.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Neurobiology and Genetics, Biocenter, Department of Bioinformatics, Biocenter and Department of Pharmaceutical Biology, Biocenter, University of Wuerzburg, Wuerzburg, Germany Department of Neurobiology and Genetics, Biocenter, Department of Bioinformatics, Biocenter and Department of Pharmaceutical Biology, Biocenter, University of Wuerzburg, Wuerzburg, Germany.
authors.forename: Zeeshan
authors.initials: Z
authors.lastname: Ahmed
authors.affiliation: Department of Neurobiology and Genetics, Biocenter, Department of Bioinformatics, Biocenter and Department of Pharmaceutical Biology, Biocenter, University of Wuerzburg, Wuerzburg, Germany.
authors.forename: Michel
authors.initials: M
authors.lastname: Mayr
authors.affiliation: Department of Neurobiology and Genetics, Biocenter, Department of Bioinformatics, Biocenter and Department of Pharmaceutical Biology, Biocenter, University of Wuerzburg, Wuerzburg, Germany.
authors.forename: Saman
authors.initials: S
authors.lastname: Zeeshan
authors.affiliation: Department of Neurobiology and Genetics, Biocenter, Department of Bioinformatics, Biocenter and Department of Pharmaceutical Biology, Biocenter, University of Wuerzburg, Wuerzburg, Germany.
authors.forename: Thomas
authors.initials: T
authors.lastname: Dandekar
authors.affiliation: Department of Neurobiology and Genetics, Biocenter, Department of Bioinformatics, Biocenter and Department of Pharmaceutical Biology, Biocenter, University of Wuerzburg, Wuerzburg, Germany.
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Mueller
authors.affiliation: Department of Neurobiology and Genetics, Biocenter, Department of Bioinformatics, Biocenter and Department of Pharmaceutical Biology, Biocenter, University of Wuerzburg, Wuerzburg, Germany.
authors.forename: Agnes
authors.initials: A
authors.lastname: Fekete
mesh_terms: D000465:Algorithms; D002853:Chromatography, Liquid / Q000379:methods*; D016208:Databases, Factual; D006801:Humans; D008055:Lipids / Q000032:analysis*; D055432:Metabolomics / Q000379:methods*; D012984:Software; D053719:Tandem Mass Spectrometry / Q000379:methods*
chemical_list: D008055:Lipids