@article {503,
	title = {Defining the genomic signature of totipotency and pluripotency during early human development.},
	journal = {PLoS One},
	volume = {8},
	year = {2013},
	month = {2013},
	pages = {e62135},
	abstract = {<p>The genetic mechanisms governing human pre-implantation embryo development and the in vitro counterparts, human embryonic stem cells (hESCs), still remain incomplete. Previous global genome studies demonstrated that totipotent blastomeres from day-3 human embryos and pluripotent inner cell masses (ICMs) from blastocysts, display unique and differing transcriptomes. Nevertheless, comparative gene expression analysis has revealed that no significant differences exist between hESCs derived from blastomeres versus those obtained from ICMs, suggesting that pluripotent hESCs involve a new developmental progression. To understand early human stages evolution, we developed an undifferentiation network signature (UNS) and applied it to a differential gene expression profile between single blastomeres from day-3 embryos, ICMs and hESCs. This allowed us to establish a unique signature composed of highly interconnected genes characteristic of totipotency (61 genes), in vivo pluripotency (20 genes), and in vitro pluripotency (107 genes), and which are also proprietary according to functional analysis. This systems biology approach has led to an improved understanding of the molecular and signaling processes governing human pre-implantation embryo development, as well as enabling us to comprehend how hESCs might adapt to in vitro culture conditions.</p>},
	keywords = {Blastocyst Inner Cell Mass, Blastomeres, Cell Differentiation, Embryonic Development, Embryonic Stem Cells, Gene Expression Profiling, Gene Regulatory Networks, Genome, Human, Humans, Molecular Sequence Annotation, Pluripotent Stem Cells, Totipotent Stem Cells},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0062135},
	author = {Galan, Amparo and Diaz-Gimeno, Patricia and Poo, Maria Eugenia and Valbuena, Diana and Sanchez, Eva and Ruiz, Veronica and Dopazo, Joaquin and Montaner, David and Conesa, Ana and Simon, Carlos}
}
@article {574,
	title = {Multidimensional gene set analysis of genomic data.},
	journal = {PLoS One},
	volume = {5},
	year = {2010},
	month = {2010 Apr 27},
	pages = {e10348},
	abstract = {<p>Understanding the functional implications of changes in gene expression, mutations, etc., is the aim of most genomic experiments. To achieve this, several functional profiling methods have been proposed. Such methods study the behaviour of different gene modules (e.g. gene ontology terms) in response to one particular variable (e.g. differential gene expression). In spite to the wealth of information provided by functional profiling methods, a common limitation to all of them is their inherent unidimensional nature. In order to overcome this restriction we present a multidimensional logistic model that allows studying the relationship of gene modules with different genome-scale measurements (e.g. differential expression, genotyping association, methylation, copy number alterations, heterozygosity, etc.) simultaneously. Moreover, the relationship of such functional modules with the interactions among the variables can also be studied, which produces novel results impossible to be derived from the conventional unidimensional functional profiling methods. We report sound results of gene sets associations that remained undetected by the conventional one-dimensional gene set analysis in several examples. Our findings demonstrate the potential of the proposed approach for the discovery of new cell functionalities with complex dependences on more than one variable.</p>},
	keywords = {Databases, Genetic, Gene Expression Profiling, Gene Regulatory Networks, Genome, Human, Genomics, Humans, Models, Statistical},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0010348},
	author = {Montaner, David and Dopazo, Joaquin}
}
