Ergänzungen zur iberischen Pseudoscorpioniden-Fauna

Die systematischen Aufsammlungen, die Prof. Dr. H. Franz in den letzten Jahren in weiten Teilen der iberischen Halbinsel durchführte, schliessen weitgehend die Lücken, die bisher noch zwischen den explorierten Gebieten klafften. Sie ergänzen und berichtigen daher unsere bisherigen, von mir letztmals 1955 (Eos, XXXI, pp. 87-122) zusammengefassten Kenntnisse in taxonomischer und faunistischer Hinsicht und runden das Faunenbild auch tiergeographisch zu erfreulicher Vollständigkeit ab. Die Ausbeuten enthielten wiederum 8 neue Arten beziehungsweise Unterarten. Drei weitere Arten waren für Spanien neu. In den cantabrischen Gebirgen tritt nunmehr die Gattung Microcreagris als charakteristisches Faunenelement noch stärker hervor.— Im folgenden werden die seither gemachten Funde angeführt.Peer reviewe

Functional Enrichment Analysis in Branches and Communities.

<p>(A) A plot of the percentage of branches and percent of communities found to be enriched at <i>p</i> < 0.01 in each gene signature. Although both communities and GO-branches have enrichment in these signatures, many signatures are only enriched in communities and not branches at the <i>p</i> < 0.01 significance. We chose a subset of signatures to investigate further, and note those with a blue dot. (b) A heat map showing the statistical enrichment of selected cancer signatures (noted in (a) with a blue dot), as measured by AEA, in both GO branches and term communities.</p

Visual Representation of Our Approach.

<p>First, we summarize gene annotations made to functional terms in the Gene Ontology hierarchy as a gene-term bipartite graph. From these gene-term relationships, we project a term-term network. We partition this network into communities and compare those term communities to branches of terms in the DAG. Finally, we perform functional enrichment analysis on experimentally-defined gene sets using both the term communities and GO branches.</p

A Comparison of Branches in the GO DAG and Term Communities Found by Partitioning the Term Network.

<p>(a) Distribution of <i>J</i>_<i>m</i>, the maximum similarity a community or branch with ten or more members has compared to all other branches or communities with ten or more members, respectively. Although a small number of communities and branches have similar memberships, most are highly dissimilar. (b)-(c) Two example comparisons between communities and branches: (b) TC:0003876 compared to GO:0015298, and (c) TC:0011556 compared to GO:0090559. In each panel on the left hand side a community and its inter-community connections in the annotation-driven term network is shown and on the right hand side the branch with which that community has the the highest Jaccard similarity is illustrated. In the right panel edges represent the ontological associations defined by the Gene Ontology term hierarchy. Each term member of the community or branch is colored both by its associated primary domain (inner color—BP:yellow, MF:cyan, CC:magenta) and its community membership (outer color), determined at the same resolution value as the illustrated community. Terms common between each community and branch pair are circled. To read term-labels, please zoom in.</p

Biological Information in Term Communities.

<p>(a-d) Term Communities (TC:0000228, TC:0000227) and branches (GO:0050896, GO:0002376) summarized as word clouds. In each case the color of a word represents how often the term description containing that word belongs to each of the primary domains (BP:yellow, MF:cyan, CC:magenta, also see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004565#pcbi.1004565.g002" target="_blank">Fig 2</a> for mixed-domain coloration) and size represents that word’s statistical enrichment in that community/branch.</p

Visualization of Communities (Circles) of GO Terms Found at the Six Lowest Levels of Resolution (Rows), in Increasing Order (Top to Bottom).

<p>The width of the line connecting two communities is proportional to the percentage of terms in the child community that are also in the parent community. The size of communities is proportional to the log of the number of terms in the community. Color represents the normalized percentage of terms in the community which belong to the BP (yellow), MF (cyan) and CC (magenta) primary domains.</p

Data used to construct both the initial and gold-standard networks used in the evaluation of PANDA and the other network reconstruction algorithms.

<p>Data used to construct both the initial and gold-standard networks used in the evaluation of PANDA and the other network reconstruction algorithms.</p

Specific examples of condition-specific genes and edges highlighted by PANDA.

<p>(<b>A</b>) A table of genes (transcription factors bolded) with an enrichment of edges in a particular condition-specific network compared the union of all the networks and an example of their functional role in the cell. Also, the expression levels of these genes across the conditions in the cell-cycle and stress-response datasets. For visualization purposes, each row in each dataset was normalized to a Z-score. The co-expression of the genes in these regulatory “modules” is easily discernible. As co-expression between genes and transcription factors is not used by PANDA when building the networks it is not surprising that some of the TFs are not as highly co-expressed with the other identified genes. (<b>B–C</b>) Visualization of the edges surrounding these enriched genes in the (<b>B</b>) cell cycle and (<b>C</b>) stress response condition-specific networks. Co-regulatory (<i>C</i>) and protein-cooperativity (<i>P</i>) network edges are shown if they are in the top 10% of edges identified by PANDA in the final condition-specific co-regulatory and protein-cooperativity networks (for more information see Methods S1).</p

An evaluation of PANDA’s performance.

<p>(<b>A</b>) The significance of the area under the ROC curve (AUC) for the regulatory network predicted by PANDA at each step during convergence using all experimental data types. Red dotted and dashed lines indicate the AUC values for either random (0.5) or the motif prior (0.687), respectively. Edges included in the motif prior as well as those that are not included in the motif prior are evaluated separately. As messages are passed, the quality of the regulatory network increases. A large portion of this improvement is attributable to a removal of false positives from motif-edges. (<b>B</b>) PANDA’s performance as noise is added to the motif prior. Even upon “full” randomization of the initial motif network, PANDA is able to improve the network prediction, indicating that it can still find biological signal in the absence of an accurate prior. (<b>C</b>) Evaluation of the accuracy of transformation for each data type specific network by PANDA. The initial AUC of each input network is shown as well as the AUC of the edges predicted by PANDA. The significance was determined by jackknifing the input data.</p

CREB binding is relatively low in the group of promoters bound by CREB, C/EBPβ and cJun and induced by differentiation.

<p><b>A.</b> Transcription factor binding distributions in all promoters, promoters bound by CREB, C/EBPβ and c-Jun, and promoters bound by all three of these proteins that are also either induced or repressed upon differentiation. Columns show the mean value of the binding affinity for each of the three transcription factors in these four groups of promoters, while error bars show the 15% and 85% percentiles. The binding affinity of CREB is significantly lower in promoters bound by all three transcription factors and induced by differentiation. Number on top represents the p-value from an unpaired t-test. <b>B.</b> Chip-PCR for promoter regions of SPRP1A and DNAse1L3 induced by differentiation. CREB binding is low in comparison with C/EBPβ and c-Jun. 3′ GAPDH region was not enriched in these samples.</p