@article {491, title = {Pathway network inference from gene expression data.}, journal = {BMC Syst Biol}, volume = {8 Suppl 2}, year = {2014}, month = {2014}, pages = {S7}, abstract = {

BACKGROUND: The development of high-throughput omics technologies enabled genome-wide measurements of the activity of cellular elements and provides the analytical resources for the progress of the Systems Biology discipline. Analysis and interpretation of gene expression data has evolved from the gene to the pathway and interaction level, i.e. from the detection of differentially expressed genes, to the establishment of gene interaction networks and the identification of enriched functional categories. Still, the understanding of biological systems requires a further level of analysis that addresses the characterization of the interaction between functional modules.

RESULTS: We present a novel computational methodology to study the functional interconnections among the molecular elements of a biological system. The PANA approach uses high-throughput genomics measurements and a functional annotation scheme to extract an activity profile from each functional block -or pathway- followed by machine-learning methods to infer the relationships between these functional profiles. The result is a global, interconnected network of pathways that represents the functional cross-talk within the molecular system. We have applied this approach to describe the functional transcriptional connections during the yeast cell cycle and to identify pathways that change their connectivity in a disease condition using an Alzheimer example.

CONCLUSIONS: PANA is a useful tool to deepen in our understanding of the functional interdependences that operate within complex biological systems. We show the approach is algorithmically consistent and the inferred network is well supported by the available functional data. The method allows the dissection of the molecular basis of the functional connections and we describe the different regulatory mechanisms that explain the network{\textquoteright}s topology obtained for the yeast cell cycle data.

}, keywords = {Alzheimer Disease, Cell Cycle, DNA Replication, Gene Expression Profiling, Gene Regulatory Networks, Gluconeogenesis, Glycolysis, Oxidative Phosphorylation, Proteolysis, Purines, Saccharomyces cerevisiae, Systems biology, Ubiquitin}, issn = {1752-0509}, doi = {10.1186/1752-0509-8-S2-S7}, author = {Ponzoni, Ignacio and Nueda, Mar{\'\i}a and Tarazona, Sonia and G{\"o}tz, Stefan and Montaner, David and Dussaut, Julieta and Dopazo, Joaquin and Conesa, Ana} } @article {496, title = {Intrauterine growth restriction is associated with cardiac ultrastructural and gene expression changes related to the energetic metabolism in a rabbit model.}, journal = {Am J Physiol Heart Circ Physiol}, volume = {305}, year = {2013}, month = {2013 Dec}, pages = {H1752-60}, abstract = {

Intrauterine growth restriction (IUGR) affects 7-10\% of pregnancies and is associated with cardiovascular remodeling and dysfunction, which persists into adulthood. The underlying subcellular remodeling and cardiovascular programming events are still poorly documented. Cardiac muscle is central in the fetal adaptive mechanism to IUGR given its high energetic demands. The energetic homeostasis depends on the correct interaction of several molecular pathways and the adequate arrangement of intracellular energetic units (ICEUs), where mitochondria interact with the contractile machinery and the main cardiac ATPases to enable a quick and efficient energy transfer. We studied subcellular cardiac adaptations to IUGR in an experimental rabbit model. We evaluated the ultrastructure of ICEUs with transmission electron microscopy and observed an altered spatial arrangement in IUGR, with significant increases in cytosolic space between mitochondria and myofilaments. A global decrease of mitochondrial density was also observed. In addition, we conducted a global gene expression profile by advanced bioinformatics tools to assess the expression of genes involved in the cardiomyocyte energetic metabolism and identified four gene modules with a coordinated over-representation in IUGR: oxygen homeostasis (GO: 0032364), mitochondrial respiratory chain complex I (GO:0005747), oxidative phosphorylation (GO: 0006119), and NADH dehydrogenase activity (GO:0003954). These findings might contribute to changes in energetic homeostasis in IUGR. The potential persistence and role of these changes in long-term cardiovascular programming deserves further investigation.

}, keywords = {Animals, Disease Models, Animal, Energy Metabolism, Female, Fetal Growth Retardation, gene expression, Mitochondria, Myocardium, Oxidative Phosphorylation, Placenta, Pregnancy, Rabbits}, issn = {1522-1539}, doi = {10.1152/ajpheart.00514.2013}, author = {Gonz{\'a}lez-Tendero, Anna and Torre, Iratxe and Garc{\'\i}a-Ca{\~n}adilla, Patricia and Crispi, F{\'a}tima and Garcia-Garcia, Francisco and Dopazo, Joaquin and Bijnens, Bart and Gratac{\'o}s, Eduard} }