X-rays from the colliding wind binary WR 146

The X-ray emission from the massive binary WR 146R is analysed in the framework of the colliding stellar wind (CSW) picture. The theoretical CSW model spectra match well the shape of the observed X-ray spectrum of WR 146R but they overestimate considerably the observed X-ray flux (emission measure). This is valid both in the case of complete temperature equalization and in the case of partial electron heating at the shock fronts (different electron and ion temperatures), but, there are indications for a better correspondence between model predictions and observations for the latter. To reconcile the model predictions and observations, the mass-loss rate of WR 146 must be reduced by a factor of 8 - 10 compared to the currently accepted value for this object (the latter already takes clumping into account). No excess X-ray absorption is derived from the CSW modelling.Comment: Accepted for publication in MNRAS; 9 pages, 4 figires, 1 tabl

Scheme of the method used for obtaining the Metric Model based on Gene Ontology annotations

(1) Profile vectors are built by retrieving the Molecular Function Gene Ontology annotations (MF-GO terms) of Interpro domains from the file interpro2go. (2) From the profiles, a co-occurrence matrix is calculated by counting how many times two MF-GO terms occur in the same set of Interpro domains. (3) The co-occurrence vectors are feature vectors that describe the functional links of each MF-GO term. The similarity between the MF-GO terms is calculated by the cosine distance between the vectors. (4) The similarity values are arranged in a matrix . The similarity matrix was considered as the Adjacency Matrix of a weighted graph . The terms can be clustered by means of the partition of the graph. To obtain the best partition of , a Spectral Clustering algorithm is applied. The Spectral Clustering algorithm projects the terms in a K dimensional space which can be clustered with standard clustering techniques. (5) The GO terms are grouped in a Hierarchical Tree representing the Functional Distance that satisfy the mathematical properties of a Metric Space.<p><b>Copyright information:</b></p><p>Taken from "Defining functional distances over Gene Ontology"</p><p>http://www.biomedcentral.com/1471-2105/9/50</p><p>BMC Bioinformatics 2008;9():50-50.</p><p>Published online 25 Jan 2008</p><p>PMCID:PMC2375122.</p><p></p

The whole spectra of the P matrix λ()is analyzed selecting the first K eigenvalues and for each selection obtaining a partition of the MF-GO terms

In panel A, the values of the gap measure calculated for are represented and according to the Spectral Clustering theory, the best partition * minimizes the gap value. The red circle encloses the eigenvalues of the spectra that generate 'good' clusterings (interval [4, 93]). Panel B shows the result of applying a second criterion to select the best number of groups from the interval. The correlation coefficient of the ordered similarity matrix with an ideal block diagonal matrix is calculated for each partition. The best clustering is obtained by selecting the first 93 eigenvalues.<p><b>Copyright information:</b></p><p>Taken from "Defining functional distances over Gene Ontology"</p><p>http://www.biomedcentral.com/1471-2105/9/50</p><p>BMC Bioinformatics 2008;9():50-50.</p><p>Published online 25 Jan 2008</p><p>PMCID:PMC2375122.</p><p></p

Representation of the GO “Biological Processes” significantly enriched in disordered proteins in <i>A. thaliana</i>.

<p>Disordered proteins here correspond to those with one or more “long disordered windows” (LDW) based on Disopred predictions. Figure adapted from REVIGO, a system for summarizing and visualizing lists of GO terms. Each rectangle represents a cluster of related terms labeled according to a representative term. Rectangles are grouped in “superclusters” (identified with the same color) based on SimRel semantic similarity measure.</p

Representation of the GO “Biological Processes” comparatively enriched in disordered proteins in <i>A. thaliana</i> respect to <i>H. sapiens.</i>

<p>Disordered proteins here are again those with 1 or more LDWs based on Disopred predictions. Same REVIGO representation adaptation as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055524#pone-0055524-g003" target="_blank">Figure 3</a>.</p

Schematic representation of the methodology used for the comparative study of protein disorder in <i>A. thaliana</i> and <i>H. sapiens</i>.

<p>For each organism (Arabidopsis (green) and human (blue)) protein sequences and their corresponding Gene Ontology annotations are retrieved from Uniprot. For each protein, disordered regions (pink) are calculated using 3 different methods (Iupred, VSL2 and Disopred), and disordered-binding regions (DBRs) are predicted using ANCHOR. Proteins are assigned to GO:BP functional classes. For each GO functional class, a comparative analysis of the disorder levels of the proteins of each organism is performed, using different criteria for quantifying disorder in that given GO class. For those disorder criteria that assign a “yes/no” label to a given protein, contingency tables are constructed with the counts of disordered and not-disordered proteins in both organisms and a Chi-squared test is applied to them. For those criteria that quantify the disorder of a given protein, the tables contain the average values of that figure for both organisms, and a Wilcoxon rank sum test is applied.</p

Genome-Wide Analysis of Protein Disorder in <em>Arabidopsis thaliana</em>: Implications for Plant Environmental Adaptation

<div><p>Intrinsically Disordered Proteins/Regions (IDPs/IDRs) are currently recognized as a widespread phenomenon having key cellular functions. Still, many aspects of the function of these proteins need to be unveiled. IDPs conformational flexibility allows them to recognize and interact with multiple partners, and confers them larger interaction surfaces that may increase interaction speed. For this reason, molecular interactions mediated by IDPs/IDRs are particularly abundant in certain types of protein interactions, such as those of signaling and cell cycle control. We present the first large-scale study of IDPs in <em>Arabidopsis thaliana</em>, the most widely used model organism in plant biology, in order to get insight into the biological roles of these proteins in plants. The work includes a comparative analysis with the human proteome to highlight the differential use of disorder in both species. Results show that while human proteins are in general more disordered, certain functional classes, mainly related to environmental response, are significantly more enriched in disorder in Arabidopsis. We propose that because plants cannot escape from environmental conditions as animals do, they use disorder as a simple and fast mechanism, independent of transcriptional control, for introducing versatility in the interaction networks underlying these biological processes so that they can quickly adapt and respond to challenging environmental conditions.</p> </div

Overall predicted global disorder and disordered binding regions in <i>A. thaliana</i> and <i>H. sapiens</i> proteins.

<p>Left: percentages of disordered proteins (disordered proteins criterion: those proteins containing at least 50% disordered residues based on Disopred predictions). Right: average percentages of disordered residues involved in binding (DBRs), as predicted by ANCHOR. The stars denote significant differences evaluated with the same Chi-square tests described in the Methods section and illustrated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055524#pone-0055524-g001" target="_blank">Figure 1</a> but using all proteins (i.e. not restricted to a particular GO functional class).</p

Summary of intrinsic disorder metrics for <i>A. thaliana and H. sapiens</i>.

<p>Results shown for Disopred (disorder prediction) and ANCHOR (Disorder binding regions, DBRs). For results with other predictors see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055524#pone.0055524.s001" target="_blank">Additional Data File S1</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055524#pone-0055524-t001" target="_blank">Table 1S</a>.</p