Genes2Networks: Connecting Lists of Proteins by Using Background Literature-based Mammalian Networks

In recent years, in-silico literature-based mammalian protein-protein interaction network datasets have been developed. These datasets contain binary interactions extracted manually from legacy experimental biomedical research literature. Placing lists of genes or proteins identified as significantly changing in multivariate experiments, in the context of background knowledge about binary interactions, can be used to place these genes or proteins in the context of pathways and protein complexes.
Genes2Networks is a software system that integrates the content of ten mammalian literature-based interaction network datasets. Filtering to prune low-confidence interactions was implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from “seed” lists of human Entrez gene names. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is available at http://actin.pharm.mssm.edu/genes2networks.
Genes2Network is a powerful web-based software application tool that can help experimental biologists to interpret high-throughput experimental results used in genomics and proteomics studies where the output of these experiments is a list of significantly changing genes or proteins. The system can be used to find relationships between nodes from the seed list, and predict novel nodes that play a key role in a common function

Calculation of W b bbar Production via Double Parton Scattering at the LHC

We investigate the potential to observe double parton scattering at the Large Hadron Collider in p p -> W b bbar X -> l nu b bbar X at 7 TeV. Our analysis tests the efficacy of several kinematic variables in isolating the double parton process of interest from the single parton process and relevant backgrounds for the first 10 inverse fb of integrated luminosity. These variables are constructed to expose the independent nature of the two subprocesses in double parton scattering, pp -> l nu X and pp -> b bbar X. We use next-to-leading order perturbative predictions for the double parton and single parton scattering components of W b bbar and for the pertinent backgrounds. The next-to-leading order contributions are important for a proper description of some of the observables we compute. We find that the double parton process can be identified and measured with significance S/sqrt(B) ~ 10, provided the double parton scattering effective cross section sigma_{eff} ~ 12 mb.Comment: 21 pages, 9 figures; v2: improved presentation and figures, version published in Phys. Rev.

Systems pharmacology and genome medicine: a future perspective

Genome medicine uses genomic information in the diagnosis of disease and in prescribing treatment. This transdisciplinary field brings together knowledge on the relationships between genetics, pathophysiology and pharmacology. Systems pharmacology aims to understand the actions and adverse effects of drugs by considering targets in the context of the biological networks in which they exist. Genome medicine forms the base on which systems pharmacology can develop. Experimental and computational approaches enable systems pharmacology to obtain holistic, mechanistic information on disease networks and drug responses, and to identify new drug targets and specific drug combinations. Network analyses of interactions involved in pathophysiology and drug response across various scales of organization, from molecular to organismal, will allow the integration of the systems-level understanding of drug action with genome medicine. The interface of the two fields will enable drug discovery for personalized medicine. Here we provide a perspective on the questions and approaches that drive the development of these new interrelated fields

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

<p>Abstract</p> <p>Background</p> <p>In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes.</p> <p>Results</p> <p>Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list.</p> <p>Conclusion</p> <p>Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.</p

Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure

<p>Abstract</p> <p>Background</p> <p>Although multiple templates are frequently used in comparative modeling, the effect of inclusion of additional template(s) on model accuracy (when compared to that of corresponding single-template based models) is not clear. To address this, we systematically analyze two-template models, the simplest case of multiple-template modeling. For an existing target-template pair (single-template modeling), a two-template based model of the target sequence is constructed by including an additional template without changing the original alignment to measure the effect of the second template on model accuracy.</p> <p>Results</p> <p>Even though in a large number of cases a two-template model showed higher accuracy than the corresponding one-template model, over the entire dataset only a marginal improvement was observed on average, as there were many cases where no change or the reverse change was observed. The increase in accuracy due to the structural complementarity of the templates increases at higher alignment accuracies. The combination of templates showing the highest potential for improvement is that where both templates share similar and low (less than 30%) sequence identity with the target, as well as low sequence identity with each other. The structural similarity between the templates also helps in identifying template combinations having a higher chance of resulting in an improved model.</p> <p>Conclusion</p> <p>Inclusion of additional template(s) does not necessarily improve model quality, but there are distinct combinations of the two templates, which can be selected <it>a priori</it>, that tend to show improvement in model quality over the single template model. The benefit derived from the structural complementarity is dependent on the accuracy of the modeling alignment. The study helps to explain the observation that a careful selection of templates together with an accurate target:template alignment are necessary to the benefit from using multiple templates in comparative modeling and provides guidelines to maximize the benefit from using multiple templates. This enables formulation of simple template selection rules to rank targets of a protein family in the context of structural genomics.</p

The Dymanics of Market Entry: The Effects of Mergers and Acquisitions on De Novo Entry and Small Business Lending in the Banking Industry,

We study the dynamics of market entry following mergers and acquisitions (M&As), and the behavior of recent entrants in supplying output that might be withdrawn by the consolidating firms. The data, drawn from the banking industry, suggests that M&As are associated with subsequent increases in the probability of entry. The estimates suggest that M&As explain more than 20% of entry in metropolitan markets, and more than 10% of entry in rural markets. Additional results suggest that bank age has a strong negative effect on the small business lending of small banks, but that M&As have little influence on this lending

Cosmological Histories for the New Variables

Histories and measures for quantum cosmology are investigated through a quantization of the Bianchi IX cosmology using path integral techniques. The result, derived in the context of Ashtekar variables, is compared with earlier work. A non-trivial correction to the measure is found, which may dominate the classical potential for universes on the Planck scale.Comment: 14, CGPG-94/2-

Short gamma-ray bursts from dynamically-assembled compact binaries in globular clusters: pathways, rates, hydrodynamics and cosmological setting

We present a detailed assessment of the dynamical pathways leading to the coalescence of compact objects in Globular Clusters (GCs) and Short Gamma-Ray Burst (SGRB) production. We consider primordial binaries, dynamically formed binaries (through tidal two-body and three-body exchange interactions) and direct impacts of compact objects (WD/NS/BH). We show that if the primordial binary fraction is small, close encounters dominate the production rate of coalescing compact systems. We find that the two dominant channels are the interaction of field NSs with dynamically formed binaries, and two-body encounters. We then estimate the redshift distribution and host galaxy demographics of SGRB progenitors, and find that GCs can provide a significant contribution to the overall observed rate. We have carried out hydrodynamical modeling of evolution of close stellar encounters with WD/NS/BH, and show that there is no problem in accounting for the energy budget of a typical SGRB. The particulars of each encounter are variable and lead to interesting diversity: the encounter characteristics are dependent on the impact parameter, in contrast to the merger scenario; the nature of the compact star itself can produce very different outcomes; the presence of tidal tails in which material falls back onto the central object at later times is a robust feature of these calculations, with the mass involved being larger than for binary mergers. It is thus possible to account generically in this scenario for a prompt episode of energy release, as well as for activity many dynamical time scales later (abridged).Comment: Accepted for publication in ApJ (24 pages, 19 figures