Factors Affecting Vibration Induced Settlement

In urbanized areas, vibration induced settlement on granular soils depends on vibration characteristics including vibration path and source, in-situ stress conditions, and soil properties. Quantitative laboratory assessment of settlement was extrapolated using parametric study of in-situ settlement of sands. It is shown that vibration amplitude should be monitored within the vulnerable soil layers or evaluated considering attenuation characteristics of soil. Combining the effects of influencing factors, the discussed model can be utilized to predict vibration induced settlement of structures on sand

Protein Ontology: A controlled structured network of protein entities

The Protein Ontology (PRO; http://proconsortium.org) formally defines protein entities and explicitly represents their major forms and interrelations. Protein entities represented in PRO corresponding to single amino acid chains are categorized by level of specificity into family, gene, sequence and modification metaclasses, and there is a separate metaclass for protein complexes. All metaclasses also have organism-specific derivatives. PRO complements established sequence databases such as UniProtKB, and interoperates with other biomedical and biological ontologies such as the Gene Ontology (GO). PRO relates to UniProtKB in that PRO’s organism-specific classes of proteins encoded by a specific gene correspond to entities documented in UniProtKB entries. PRO relates to the GO in that PRO’s representations of organism-specific protein complexes are subclasses of the organism-agnostic protein complex terms in the GO Cellular Component Ontology. The past few years have seen growth and changes to the PRO, as well as new points of access to the data and new applications of PRO in immunology and proteomics. Here we describe some of these developments

Symmetry-induced interference effects in metalloporphyrin wires

Organo-metallic molecular structures where a single metallic atom is embedded in the organic backbone are ideal systems to study the effect of strong correlations on their electronic structure. In this work we calculate the electronic and transport properties of a series of metalloporphyrin molecules sandwiched by gold electrodes using a combination of density functional theory and scattering theory. The impact of strong correlations at the central metallic atom is gauged by comparing our results obtained using conventional DFT and DFT+U approaches. The zero bias transport properties may or may not show spin-filtering behavior, depending on the nature of the d state closest to the Fermi energy. The type of d state depends on the metallic atom and gives rise to interference effects that produce different Fano features. The inclusion of the U term opens a gap between the d states and changes qualitatively the conductance and spin-filtering behavior in some of the molecules. We explain the origin of the quantum interference effects found as due to the symmetry-dependent coupling between the d states and other molecular orbitals and propose the use of these systems as nanoscale chemical sensors. We also demonstrate that an adequate treatment of strong correlations is really necessary to correctly describe the transport properties of metalloporphyrins and similar molecular magnets

Biochemical pathways represented by Gene Ontology-Causal Activity Models identify distinct phenotypes resulting from mutations in pathways.

Gene inactivation can affect the process(es) in which that gene acts and causally downstream ones, yielding diverse mutant phenotypes. Identifying the genetic pathways resulting in a given phenotype helps us understand how individual genes interact in a functional network. Computable representations of biological pathways include detailed process descriptions in the Reactome Knowledgebase and causal activity flows between molecular functions in Gene Ontology-Causal Activity Models (GO-CAMs). A computational process has been developed to convert Reactome pathways to GO-CAMs. Laboratory mice are widely used models of normal and pathological human processes. We have converted human Reactome GO-CAMs to orthologous mouse GO-CAMs, as a resource to transfer pathway knowledge between humans and model organisms. These mouse GO-CAMs allowed us to define sets of genes that function in a causally connected way. To demonstrate that individual variant genes from connected pathways result in similar but distinguishable phenotypes, we used the genes in our pathway models to cross-query mouse phenotype annotations in the Mouse Genome Database (MGD). Using GO-CAM representations of 2 related but distinct pathways, gluconeogenesis and glycolysis, we show that individual causal paths in gene networks give rise to discrete phenotypic outcomes resulting from perturbations of glycolytic and gluconeogenic genes. The accurate and detailed descriptions of gene interactions recovered in this analysis of well-studied processes suggest that this strategy can be applied to less well-understood processes in less well-studied model systems to predict phenotypic outcomes of novel gene variants and to identify potential gene targets in altered processes

Protein Ontology: Enhancing and scaling up the representation of protein entities

The Protein Ontology (PRO; http://purl.obolibrary.org/obo/pr) formally defines and describes taxon-specific and taxon-neutral protein-related entities in three major areas: proteins related by evolution; proteins produced from a given gene; and protein-containing complexes. PRO thus serves as a tool for referencing protein entities at any level of specificity. To enhance this ability, and to facilitate the comparison of such entities described in different resources, we developed a standardized representation of proteoforms using UniProtKB as a sequence reference and PSI-MOD as a post-translational modification reference. We illustrate its use in facilitating an alignment between PRO and Reactome protein entities. We also address issues of scalability, describing our first steps into the use of text mining to identify protein-related entities, the large-scale import of proteoform information from expert curated resources, and our ability to dynamically generate PRO terms. Web views for individual terms are now more informative about closely-related terms, including for example an interactive multiple sequence alignment. Finally, we describe recent improvement in semantic utility, with PRO now represented in OWL and as a SPARQL endpoint. These developments will further support the anticipated growth of PRO and facilitate discoverability of and allow aggregation of data relating to protein entities

Integrative annotation and knowledge discovery of kinase post-translational modifications and cancer-associated mutations through federated protein ontologies and resources.

Many bioinformatics resources with unique perspectives on the protein landscape are currently available. However, generating new knowledge from these resources requires interoperable workflows that support cross-resource queries. In this study, we employ federated queries linking information from the Protein Kinase Ontology, iPTMnet, Protein Ontology, neXtProt, and the Mouse Genome Informatics to identify key knowledge gaps in the functional coverage of the human kinome and prioritize understudied kinases, cancer variants and post-translational modifications (PTMs) for functional studies. We identify 32 functional domains enriched in cancer variants and PTMs and generate mechanistic hypotheses on overlapping variant and PTM sites by aggregating information at the residue, protein, pathway and species level from these resources. We experimentally test the hypothesis that S768 phosphorylation in the C-helix of EGFR is inhibitory by showing that oncogenic variants altering S768 phosphorylation increase basal EGFR activity. In contrast, oncogenic variants altering conserved phosphorylation sites in the \u27hydrophobic motif\u27 of PKCβII (S660F and S660C) are loss-of-function in that they reduce kinase activity and enhance membrane translocation. Our studies provide a framework for integrative, consistent, and reproducible annotation of the cancer kinomes. Sci Rep 2018 Apr 25; 8(1):6518

Enhanced superconducting pairing interaction in indium-doped tin telluride

The ferroelectric degenerate semiconductor Sn$_{1-\delta}$Te exhibits superconductivity with critical temperatures, $T_c$, of up to 0.3 K for hole densities of order 10$^{21}$ cm$^{-3}$. When doped on the tin site with greater than $x_c$ $= 1.7(3)$ indium atoms, however, superconductivity is observed up to 2 K, though the carrier density does not change significantly. We present specific heat data showing that a stronger pairing interaction is present for $x > x_c$ than for $x < x_c$. By examining the effect of In dopant atoms on both $T_c$ and the temperature of the ferroelectric structural phase transition, $T_{SPT}$, we show that phonon modes related to this transition are not responsible for this $T_c$ enhancement, and discuss a plausible candidate based on the unique properties of the indium impurities.Comment: 7 page

The Protein Ontology: a structured representation of protein forms and complexes

The Protein Ontology (PRO) provides a formal, logically-based classification of specific protein classes including structured representations of protein isoforms, variants and modified forms. Initially focused on proteins found in human, mouse and Escherichia coli, PRO now includes representations of protein complexes. The PRO Consortium works in concert with the developers of other biomedical ontologies and protein knowledge bases to provide the ability to formally organize and integrate representations of precise protein forms so as to enhance accessibility to results of protein research. PRO (http://pir.georgetown.edu/pro) is part of the Open Biomedical Ontology Foundry

Isolation of DNA sequences on human chromosome 21 by application of a recombination-based assay to DNA from flow-sorted chromosomes

By merging two efficient technologies, bivariate flow sorting of human metaphase chromosomes and a recombination-based assay for sequence complexity, we isolated 28 cloned DNA segments homologous to loci on human chromosome 21. Subregional mapping of these DNA segments with a somatic cell hybrid panel showed that 26 of the 28 cloned DNA sequences are distributed along the long arm of chromosome 21, while the other 2 hybridize with sequences on the short arm of both chromosome 21 and other chromosomes. This new collection of probes homologous to chromosome 21 should facilitate molecular analyses of trisomy 21 by providing DNA probes for the linkage map of chromosome 21, for studies of nondisjunction, for chromosome walking in clinically relevant subregions of chromosome 21, and for the isolation of genes on chromosome 21 following the screening of cDNA libraries.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47623/1/439_2004_Article_BF00366237.pd