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SeesawPred: A Web Application for Predicting Cell-fate Determinants in Cell Differentiation.
Hartmann, András; Okawa, Satoshi; Zaffaroni, Gaia; Del Sol, Antonio.
Afiliação
  • Hartmann A; Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7. avenue des Hauts-Fourneaux, Esch-sur-Alzette, L-4362, Luxembourg City, Luxembourg.
  • Okawa S; Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7. avenue des Hauts-Fourneaux, Esch-sur-Alzette, L-4362, Luxembourg City, Luxembourg.
  • Zaffaroni G; Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7. avenue des Hauts-Fourneaux, Esch-sur-Alzette, L-4362, Luxembourg City, Luxembourg.
  • Del Sol A; Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7. avenue des Hauts-Fourneaux, Esch-sur-Alzette, L-4362, Luxembourg City, Luxembourg. Antonio.delSol@uni.lu.
Sci Rep ; 8(1): 13355, 2018 09 06.
Article em En | MEDLINE | ID: mdl-30190516
Cellular differentiation is a complex process where a less specialized cell evolves into a more specialized cell. Despite the increasing research effort, identification of cell-fate determinants (transcription factors (TFs) determining cell fates during differentiation) still remains a challenge, especially when closely related cell types from a common progenitor are considered. Here, we develop SeesawPred, a web application that, based on a gene regulatory network (GRN) model of cell differentiation, can computationally predict cell-fate determinants from transcriptomics data. Unlike previous approaches, it allows the user to upload gene expression data and does not rely on pre-compiled reference data sets, enabling its application to novel differentiation systems. SeesawPred correctly predicted known cell-fate determinants on various cell differentiation examples in both mouse and human, and also performed better compared to state-of-the-art methods. The application is freely available for academic, non-profit use at http://seesaw.lcsb.uni.lu.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Diferenciação Celular / Internet / Modelos Biológicos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Diferenciação Celular / Internet / Modelos Biológicos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article