Skip to Main Content (Press Enter)

Logo UNIMI
  • ×
  • Home
  • People
  • Projects
  • Fields
  • Units
  • Outputs
  • Third Mission

Expertise & Skills
Logo UNIMI

|

Expertise & Skills

unimi.it
  • ×
  • Home
  • People
  • Projects
  • Fields
  • Units
  • Outputs
  • Third Mission
  1. Outputs

liputils: a python module to manage individual fatty acid moieties from complex lipids

Academic Article
Publication Date:
2020
Citation:
liputils: a python module to manage individual fatty acid moieties from complex lipids / S. Manzini, M. Busnelli, A. Colombo, M. Kiamehr, G. Chiesa. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 10:1(2020 Aug 07), pp. 13368.1-13368.9.
abstract:
Lipidomic analyses address the problem of characterizing the lipid components of given cells, tissues and organisms by means of chromatographic separations coupled to high-resolution, tandem mass spectrometry analyses. A number of software tools have been developed to help in the daunting task of mass spectrometry signal processing and cleaning, peak analysis and compound identification, and a typical finished lipidomic dataset contains hundreds to thousands of individual molecular
lipid species. To provide researchers without a specific technical expertise in mass spectrometry the possibility of broadening the exploration of lipidomic datasets, we have developed liputils, a Python module that specializes in the extraction of fatty acid moieties from individual molecular lipids. there is no prerequisite data format, as liputils extracts residues from RefMet-compliant textual identifiers and from annotations of other commercially available services. We provide three examples of real- world data processing with liputils, as well as a detailed protocol on how to readily process an existing dataset that can be followed with basic informatics skills.
IRIS type:
01 - Articolo su periodico
Keywords:
Python; Lipidomics; omics, mass spectrometry; bioinformatics
List of contributors:
S. Manzini, M. Busnelli, A. Colombo, M. Kiamehr, G. Chiesa
Authors of the University:
BUSNELLI MARCO ( author )
CHIESA GIULIA MARIA CAROLA ( author )
COLOMBO ALICE ( author )
Link to information sheet:
https://air.unimi.it/handle/2434/782663
Full Text:
https://air.unimi.it/retrieve/handle/2434/782663/1612154/41598_2020_Article_70259.pdf
Project:
Personalized diagnostics and treatment of high risk coronary artery disease patients
  • Research Areas

Research Areas

Concepts (3)


Settore BIO/14 - Farmacologia

Settore BIO/16 - Anatomia Umana

Settore BIO/17 - Istologia
  • Guide
  • Help
  • Accessibility
  • Privacy
  • Use of cookies
  • Legal notices

Powered by VIVO | Designed by Cineca | 26.7.0.0