Skip to Main Content (Press Enter)

Logo UNIMI
  • ×
  • Home
  • Persone
  • Attività
  • Ambiti
  • Strutture
  • Pubblicazioni
  • Terza Missione

Expertise & Skills
Logo UNIMI

|

Expertise & Skills

unimi.it
  • ×
  • Home
  • Persone
  • Attività
  • Ambiti
  • Strutture
  • Pubblicazioni
  • Terza Missione
  1. Pubblicazioni

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

Articolo
Data di Pubblicazione:
2020
Citazione:
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.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Python; Lipidomics; omics, mass spectrometry; bioinformatics
Elenco autori:
S. Manzini, M. Busnelli, A. Colombo, M. Kiamehr, G. Chiesa
Autori di Ateneo:
BUSNELLI MARCO ( autore )
CHIESA GIULIA MARIA CAROLA ( autore )
COLOMBO ALICE ( autore )
Link alla scheda completa:
https://air.unimi.it/handle/2434/782663
Link al Full Text:
https://air.unimi.it/retrieve/handle/2434/782663/1612154/41598_2020_Article_70259.pdf
Progetto:
Personalized diagnostics and treatment of high risk coronary artery disease patients
  • Aree Di Ricerca

Aree Di Ricerca

Settori (3)


Settore BIO/14 - Farmacologia

Settore BIO/16 - Anatomia Umana

Settore BIO/17 - Istologia
  • Informazioni
  • Assistenza
  • Accessibilità
  • Privacy
  • Utilizzo dei cookie
  • Note legali

Realizzato con VIVO | Progettato da Cineca | 25.11.5.0