Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation

Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measures of their expression dynamics. In this paper we apply a correlation based approach to network reconstruction to three datasets of time series gene expression following system perturbation: 1) Conditional, Tamoxifen dependent, activation of the cMyc proto-oncogene in rat fibroblast; 2) Genomic response to nutrition changes in D. melanogaster; 3) Patterns of gene activity as a consequence of ageing occurring over a life-span time series (25y–90y) sampled from T-cells of human donors

Joint analysis of transcriptional and post- transcriptional brain tumor data: searching for emergent properties of cellular systems

<p>Abstract</p> <p>Background</p> <p>Advances in biotechnology offer a fast growing variety of high-throughput data for screening molecular activities of genomic, transcriptional, post-transcriptional and translational observations. However, to date, most computational and algorithmic efforts have been directed at mining data from each of these molecular <it>levels </it>(genomic, transcriptional, etc.) separately. In view of the rapid advances in technology (new generation sequencing, high-throughput proteomics) it is important to address the problem of analyzing these data as a whole, i.e. preserving the emergent properties that appear in the cellular system when all molecular levels are interacting. We analyzed one of the (currently) few datasets that provide both transcriptional and post-transcriptional data of the same samples to investigate the possibility to extract more information, using a joint analysis approach.</p> <p>Results</p> <p>We use Factor Analysis coupled with pre-established knowledge as a theoretical base to achieve this goal. Our intention is to identify structures that contain information from both mRNAs and miRNAs, and that can explain the complexity of the data. Despite the small sample available, we can show that this approach permits identification of meaningful structures, in particular two polycistronic miRNA genes related to transcriptional activity and likely to be relevant in the discrimination between gliosarcomas and other brain tumors.</p> <p>Conclusions</p> <p>This suggests the need to develop methodologies to simultaneously mine information from different levels of biological organization, rather than linking separate analyses performed in parallel.</p

Exon expression profiling reveals stimulus-mediated exon use in neural cells

Exon centric microarrays were used to resolve the calcium-modulated gene expression response into transcript-level an exon-level regulation

Dynamic and Thermodynamic Models of Adaptation

The concept of biological adaptation was closely connected to some mathematical, engineering and physical ideas from the very beginning. Cannon in his "The wisdom of the body" (1932) used the engineering vision of regulation. In 1938, Selye enriched this approach by the notion of adaptation energy. This term causes much debate when one takes it literally, i.e. as a sort of energy. Selye did not use the language of mathematics, but the formalization of his phenomenological theory in the spirit of thermodynamics was simple and led to verifiable predictions. In 1980s, the dynamics of correlation and variance in systems under adaptation to a load of environmental factors were studied and the universal effect in ensembles of systems under a load of similar factors was discovered: in a crisis, as a rule, even before the onset of obvious symptoms of stress, the correlation increases together with variance (and volatility). During 30 years, this effect has been supported by many observations of groups of humans, mice, trees, grassy plants, and on financial time series. In the last ten years, these results were supplemented by many new experiments, from gene networks in cardiology and oncology to dynamics of depression and clinical psychotherapy. Several systems of models were developed: the thermodynamic-like theory of adaptation of ensembles and several families of models of individual adaptation. Historically, the first group of models was based on Selye's concept of adaptation energy and used fitness estimates. Two other groups of models are based on the idea of hidden attractor bifurcation and on the advection--diffusion model for distribution of population in the space of physiological attributes. We explore this world of models and experiments, starting with classic works, with particular attention to the results of the last ten years and open questions.Comment: Review paper, 48 pages, 29 figures, 183 bibliography, the final version accepted in Phys Life Re

Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation-2

<p><b>Copyright information:</b></p><p>Taken from "Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S16</p><p>BMC Bioinformatics 2007;8(Suppl 1):S16-S16.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885845.</p><p></p>with one-way ANOVA, P value < 0.01. The picture on the right (B) is the histogram of the correlation coefficients for a set of 768 probesets randomly sampled from the whole dataset of 14688 probesets. A single-gene time reshuffling applied onto each dataset produces a Gaussian distribution (data not shown)

Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation-5

<p><b>Copyright information:</b></p><p>Taken from "Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S16</p><p>BMC Bioinformatics 2007;8(Suppl 1):S16-S16.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885845.</p><p></p>sion ratios for the single genes in each pathway are shown in the rightmost panels. The difference in the correlation distributions between c-Myc-ON-treatment (central panel) and c-Myc-OFF-control (left panel) is qualitatively the same as the one observed in the entire pool of genes selected with the ANOVA analysis (Fig. 1)

Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation-3

<p><b>Copyright information:</b></p><p>Taken from "Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S16</p><p>BMC Bioinformatics 2007;8(Suppl 1):S16-S16.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885845.</p><p></p>he probesets in the dataset N (left column) and T (right column) for decreasing cutoff values (). The top row includes all the probesets used in the analysis (> 1); the central row corresponds to an intermediate threshold (= 0.2); the bottom row corresponds to the lowest threshold (= 0.05)

Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation-4

<p><b>Copyright information:</b></p><p>Taken from "Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S16</p><p>BMC Bioinformatics 2007;8(Suppl 1):S16-S16.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885845.</p><p></p>butions between Y-treatment and NY-control is qualitatively the same as the one observed in the entire pool of genes selected with the change point analysis (Figure 2)

A functional genomics study of extracellular protease production by Aspergillus niger

The objective of the project described in this thesis was to study the complex induction of extracellular proteases in the filamentous fungus Aspergillus niger using information gathered with functional genomics technologies. A special emphasis is given to the requirements for performing a successful systems biology study and addressing the challenges met in analyzing the large, information-rich data sets generated with functional genomics technologies. The role that protease activity plays in strain and process development of A. niger and other aspergilli is reviewed. The influence of several environmental factors on the production of extracellular proteases of A. niger in controlled batch cultivations was studied. Samples generated in this study were used for analysis with different functional genomics technologies. With a shotgun proteomics approach the A. niger secretome under different experimental conditions was determined. Furthermore, the effect of different quantitative phenotypes related to protease or glucoamylase activity on the information content of a metabolomics data set was investigated. Finally, the clustering of co-expressed genes is described. First, a set of conserved genes was used to construct gene co-expression networks. Subsequently, all protein-coding A. niger genes, including hypothetical and poorly conserved genes, were integrated into the co-expression analysis.UBL - phd migration 201