The International Journal of Developmental Biology

Int. J. Dev. Biol. 56: 859 - 866 (2012)

Vol 56, Issue 10-11-12

Special Issue: Female Germ Cells in Development & Tumors

Knowledge-based bioinformatics for the study of mammalian oocytes

Published: 5 February 2013

Francesca Mulas*,1, Lucia Sacchi2, Lan Zagar3, Silvia Garagna1,4, Maurizio Zuccotti5, Blaz Zupan1,3 and Riccardo Bellazzi*,1,2

1Centre for Tissue Engineering, University of Pavia, Pavia, Italy, 2Dipartimento di Ingegneria Industriale e dell’Informazione, Università degli Studi di Pavia, Pavia, Italy, 3Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia, 4Laboratorio di Biologia dello Sviluppo, Dipartimento di Biologia e Biotecnologie 'Lazzaro Spallanzani', Università degli Studi di Pavia, Pavia, Italy and 5Dipartimento di Scienze Biomediche, Biotecnologiche e Traslazionali, Università degli Studi di Parma, Italy


Bioinformatics tools have been recently applied to study the differentiation of the mammalian oocyte during folliculogenesis. In this review, we will summarize our knowledge of 1) the use of biological databases for the extraction of relevant information, 2) bioinformatics methods for knowledge extraction and representation, 3) the application of these methods to the study of mammalian oocyte differentiation and 4) state-of the-art prediction approaches for the assessment and estimation of the cell differentiation status.


knowledge extraction, database, oocyte, stem cell

Full text in web format is not available for this article. Please download the PDF version.