The MST-based hierarchical clustering algorithm: the first step is to determine the sequential representation of a graph through constructing a MST using Prim's algorithm, and the second step is to search for the valleys in the sequential representation

<p><b>Copyright information:</b></p><p>Taken from "Hierarchical classification of functionally equivalent genes in prokaryotes"</p><p></p><p>Nucleic Acids Research 2007;35(7):2125-2140.</p><p>Published online 11 Mar 2007</p><p>PMCID:PMC1874638.</p><p>© 2007 The Author(s)</p

A hierarchical structure formed by HCG-10 and its descendant clusters, where most of the genes belonging to HCG-10 are annotated as

<p><b>Copyright information:</b></p><p>Taken from "Hierarchical classification of functionally equivalent genes in prokaryotes"</p><p></p><p>Nucleic Acids Research 2007;35(7):2125-2140.</p><p>Published online 11 Mar 2007</p><p>PMCID:PMC1874638.</p><p>© 2007 The Author(s)</p> Each rectangular or circular node corresponds to a cluster, whereas a triangular node represents a group of genes that cannot be further clustered. The shape of a node reflects whether the cluster contains multiple genes from the same genome, with the rectangular standing for and the circular standing for . The color of a node reflects the taxonomic lineages of the genomes being covered by the cluster, where a solid color represents that all the genomes being covered belong to the same taxonomic lineage for which the color stands, and a color with white interior represents that most (but not all) of the genomes being covered belong to the taxonomic lineage for which the color stands. The annotations accompanying the clusters are summarized from the NCBI annotations of the genes being included

Linear Regression of NHNOE* Versus Disorder Probability.

<p>Linear Regression of NHNOE* Versus Disorder Probability.</p

Correlation Plots of the Best fitting plots for Human IUPred.

<p>(a), Dog VL-XT (b), Mouse IUPred (c), Cow VL-XT (d), Guinea Pig VSL2b (e), and Rabbit VSL2b (f).</p

A graphical representation of 291 genes and their functional equivalence relationships (as measured by their BLASTP e-values)

<p><b>Copyright information:</b></p><p>Taken from "Hierarchical classification of functionally equivalent genes in prokaryotes"</p><p></p><p>Nucleic Acids Research 2007;35(7):2125-2140.</p><p>Published online 11 Mar 2007</p><p>PMCID:PMC1874638.</p><p>© 2007 The Author(s)</p> Each node represents a gene, and each edge indicates that the reciprocal BLASTP e-values between the two genes ≤1.0. The layout of the nodes and edges is generated by using the Pajek Software (), where the Euclidean distance between two genes and the darkness of their connecting edge are both roughly proportional to their BLASTP e-value. That is, the smaller their BLASTP e-value is, the closer their two nodes are located, and the darker their connecting edge is. Most of these genes encode the two-component system regulatory proteins of either the or the family. See Tables S-1.1–S-1.5 in the Supplementary Data for descriptions of those genes that do not have accompanying IDs. Based on their COG, GO, Pfam and NCBI annotations, these genes fall into five different groups, (), (), 0 () 0 (), and genes without further specifications (▪). Each dotted ellipse contains genes that form a cluster via the rule when a certain percentage of insignificant (bottom) edges are removed, where an edge is less significant if it is associated with a higher BLASTP e-value. See Figure S-1 in the Supplementary Data for additional information of these genes and their functional equivalence relationships

The distribution of (, ) at the root, middle and leaf levels of the HCG, relative to the background distribution of (, ), where SK stands for super-kingdom, and means that two genes do not even belong to the same super-kingdom

<p><b>Copyright information:</b></p><p>Taken from "Hierarchical classification of functionally equivalent genes in prokaryotes"</p><p></p><p>Nucleic Acids Research 2007;35(7):2125-2140.</p><p>Published online 11 Mar 2007</p><p>PMCID:PMC1874638.</p><p>© 2007 The Author(s)</p> Each bin represents the ratio between the percentage of the gene pairs at a particular HCG level and the percentage of the background gene pairs that have the same taxonomic distance level

The distribution of (, ) for all the genes being covered by the HCG prediction, where stands for super-kingdom, and means that two genes do not even belong to the same super-kingdom

<p><b>Copyright information:</b></p><p>Taken from "Hierarchical classification of functionally equivalent genes in prokaryotes"</p><p></p><p>Nucleic Acids Research 2007;35(7):2125-2140.</p><p>Published online 11 Mar 2007</p><p>PMCID:PMC1874638.</p><p>© 2007 The Author(s)</p

Photoinduced Carbonyl Radical Luminescence in Host–Guest Systems

Developing a free radical emission system in different states, especially in water, is highly challenging and desired. Herein, a host–guest coassembly strategy was used to protect the in situ photoactivated radical emission of carbonyl compounds in solid and aqueous solutions by doping them into a series of small molecules with hydroxyl groups. The intermolecular interactions between host and guest and the electron-donating ability of the hydroxyl group can significantly promote the formation and stabilization of luminescence by carbonyl radicals. Accordingly, the stimuli-responsive property of the free radical system was investigated in detail, and the self-assembled aggregates showed photoactive and thermoresponsive behaviors. In addition, an advanced ammonia compound identification system can be built based on a radical emission system. Our design strategy sheds light on developing free radical systems that can emit in various states, which will greatly broaden the application range of free radicals

() Distributions of the confidence scores of the protein–protein interactions predicted by orthology mapping

<p><b>Copyright information:</b></p><p>Taken from "Computational inference and experimental validation of the nitrogen assimilation regulatory network in cyanobacterium sp. WH 8102"</p><p>Nucleic Acids Research 2006;34(3):1050-1065.</p><p>Published online 10 Feb 2006</p><p>PMCID:PMC1363776.</p><p>© The Author 2006. Published by Oxford University Press. All rights reserved</p> () Distributions of the confidence scores of the protein–protein interactions predicted by protein fusion analysis. For both the methods, the distribution of the scores of the non-verified predictions in K12 (black lines) and that of the predictions in WH8102 (green lines) are very similar to that of the verified predictions in K12 (red lines). () Distributions of the confidence scores of the combined protein–protein interactions predicted by the two methods. The distributions of the scores of the predicted protein–protein interactions in K12 and WH8102 are very similar to each other, suggesting that similar prediction accuracy has been achieved for both the species

High-Resolution Mapping of H1 Linker Histone Variants in Embryonic Stem Cells

<div><p>H1 linker histones facilitate higher-order chromatin folding and are essential for mammalian development. To achieve high-resolution mapping of H1 variants H1d and H1c in embryonic stem cells (ESCs), we have established a knock-in system and shown that the N-terminally tagged H1 proteins are functionally interchangeable to their endogenous counterparts <i>in vivo</i>. H1d and H1c are depleted from GC- and gene-rich regions and active promoters, inversely correlated with H3K4me3, but positively correlated with H3K9me3 and associated with characteristic sequence features. Surprisingly, both H1d and H1c are significantly enriched at major satellites, which display increased nucleosome spacing compared with bulk chromatin. While also depleted at active promoters and enriched at major satellites, overexpressed H1⁰ displays differential binding patterns in specific repetitive sequences compared with H1d and H1c. Depletion of H1c, H1d, and H1e causes pericentric chromocenter clustering and de-repression of major satellites. These results integrate the localization of an understudied type of chromatin proteins, namely the H1 variants, into the epigenome map of mouse ESCs, and we identify significant changes at pericentric heterochromatin upon depletion of this epigenetic mark.</p> </div