Cell lines as biological models: practical steps for more reliable research

Capes-Davis, Amanda; Bairoch, Amos Marc; Barrett, Tanya; Burnett, Edward C; Dirks, Wilhelm G; Hall, Erin M; Healy, Lyn; Kniss, Douglas A; Korch, Christopher; Liu, Yuqin; Neve, Richard M; Nims, Raymond W; Parodi, Barbara; Schweppe, Rebecca E; Storts, Douglas R; Tian, Fang

doi:10.1021/acs.chemrestox.9b00215

Scientific article

English

Cell lines as biological models: practical steps for more reliable research

ContributorsCapes-Davis, Amanda; Bairoch, Amos Marc

; Barrett, Tanya; Burnett, Edward C; Dirks, Wilhelm G; Hall, Erin M; Healy, Lyn; Kniss, Douglas A; Korch, Christopher; Liu, Yuqin; Neve, Richard M; Nims, Raymond W; Parodi, Barbara; Schweppe, Rebecca E; Storts, Douglas R; Tian, Fang

Published inChemical Research in Toxicology, vol. 32, no. 9, p. 1733-1736

Publication date2019

Abstract

Research in toxicology relies on in vitro models such as cell lines. These living models are prone to change and may be described in publications with insufficient information or quality control testing. This article sets out recommendations to improve the reliability of cell-based research.

Affiliation entities

Faculté de médecine / Section de médecine fondamentale / Département de microbiologie et médecine moléculaire

Research groups

Citation (ISO format)

CAPES-DAVIS, Amanda et al. Cell lines as biological models: practical steps for more reliable research. In: Chemical Research in Toxicology, 2019, vol. 32, n° 9, p. 1733–1736. doi: 10.1021/acs.chemrestox.9b00215

Article (Published version)

Identifiers

PID : unige:123849
DOI : 10.1021/acs.chemrestox.9b00215
PMID : 31203605

Journal ISSN0893-228X

363views

1downloads

Creation01/10/2019 16:35:00

First validation01/10/2019 16:35:00

Update30/03/2023 11:01:32

Status update30/03/2023 11:01:32

Last indexation31/10/2024 16:25:03

Archive ouverte UNIGE

Cell lines as biological models: practical steps for more reliable research

Research in toxicology relies on in vitro models such as cell lines. These living models are prone to change and may be described in publications with insufficient information or quality control testing. This article sets out recommendations to improve the reliability of cell-based research.

Technical informations