title: Knowledge-based bioinformatics for the study of mammalian oocytes.
abstract: 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.
authors: Centre for Tissue Engineering, University of Pavia, Via Ferrata 1, Pavia, Italy. francesca.mulas@unipv.it
authors: Francesca
authors: F
authors: Mulas
authors: Lucia
authors: L
authors: Sacchi
authors: Lan
authors: L
authors: Zagar
authors: Silvia
authors: S
authors: Garagna
authors: Maurizio
authors: M
authors: Zuccotti
authors: Blaz
authors: B
authors: Zupan
authors: Riccardo
authors: R
authors: Bellazzi
mesh_terms: D000818:Animals; D002454:Cell Differentiation / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D005260:Female; D020869:Gene Expression Profiling; D018507:Gene Expression Regulation, Developmental; D053263:Gene Regulatory Networks; D006801:Humans; D009865:Oocytes / Q000166:cytology / Q000378:metabolism*; D009866:Oogenesis / Q000235:genetics*