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

Table of Contents and Prologue

Editorial board, table of contents, and a prologue from the editor

Contributors

Biographical information on contributors to volume 40, and a list of benefactors and donor

Does Function Follow Organizational Form? Evidence From the Lending Practices of Large and Small Banks

Theories based on incomplete contracting suggest that small organizations may do better than large organizations in activities that require the processing of soft information. We explore this idea in the context of bank lending to small firms, an activity that is typically thought of as relying heavily on soft information. We find that large banks are less willing than small banks to lend to informationally 'difficult' credits, such as firms that do not keep formal financial records. Moreover, controlling for the endogeneity of bank-firm matching, large banks lend at a greater distance, interact more impersonally with their borrowers, have shorter and less exclusive relationships, and do not alleviate credit constraints as effectively. All of this is consistent with small banks being better able to collect and act on soft information than large banks.

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

Does Function Follow Organzizational Form? Evidence From the Lending Practices of Large and Small Banks

Theories based on incomplete contracting suggest that small organizations may do better than large organizations in activities that require the processing of soft information. We explore this idea in the context of bank lending to small firms, an activity that is typically thought of as relying heavily on soft information. We find that large banks are less willing than small banks to lend to informationally “difficult†credits, such as firms that do not keep formal financial records. Moreover, controlling for the endogeneity of bank-firm matching, large banks lend at a greater distance, interact more impersonally with their borrowers, have shorter and less exclusive relationships, and do not alleviate credit constraints as effectively. All of this is consistent with small banks being better able to collect and act on soft information than large banks. The opinions in this paper do not necessarily reflect those of the Federal Reserve Board or its staff. This work has been supported by the National Science Foundation (Rajan, Stein), and the George J. Stigler Center for Study of the State and Economy (Rajan). Thanks also to seminar participants at Yale, the Federal Reserve Bank of New York, Tulane, Babson, the University of Illinois, the Federal Reserve Bank of Chicago Bank Structure Conference, the NBER and the Western Finance Association meetings, as well as to Abhijit Banerjee, Michael Kremer, David Scharfstein, Andrei Shleifer, Greg Udell, Christopher Udry and James Weston for helpful comments and suggestions.

Exceptional sets for self-similar fractals in Carnot groups

We consider self-similar iterated function systems in the sub-Riemannian setting of Carnot groups. We estimate the Hausdorff dimension of the exceptional set of translation parameters for which the Hausdorff dimension in terms of the Carnot-Carathéodory metric is strictly less than the similarity dimension. This extends a recent result of Falconer and Miao from Euclidean space to Carnot group

Magnetic Field Topology in Low-Mass Stars: Spectropolarimetric Observations of M Dwarfs

(ABRIDGED) We report here our mapping of the magnetic field topology of the M4 dwarf G 164-31 (or Gl 490B), which is expected to be fully convective, based on time series data collected from 20 hours of observations spread over 3 successive nights with the ESPaDOnS spectropolarimeter. Our tomographic imaging technique applied to time series of rotationally modulated circularly polarized profiles reveals an axisymmetric large-scale poloidal magnetic field on the M4 dwarf. We then apply a synthetic spectrum fitting technique for measuring the average magnetic flux on the star. The flux measured in G 164-31 is Bf = 3.2+-0.4 kG, which is significantly greater than the average value of 0.68 kG determined from the imaging technique. The difference indicates that a significant fraction of the stellar magnetic energy is stored in small-scale structures at the surface of G 164-31. Our H_alpha emission light curve shows evidence for rotational modulation suggesting the presence of localized structure in the chromosphere of this M dwarf. The radius of the M4 dwarf derived from the rotational period and the projected equatorial velocity is at least 30% larger than that predicted from theoretical models. We argue that this discrepancy is likely primarily due to the young nature of G 164-31 rather than primarily due to magnetic field effects, indicating that age is an important factor which should be considered in the interpretation of this observational result. We also report here our polarimetric observations of five other M dwarfs with spectral types from M0 to M4.5, three of them showing strong Zeeman signatures.Comment: 16 pages, 6 figures, accepted by Ap

Interactive Learning-Based Realizability for Heyting Arithmetic with EM1

We apply to the semantics of Arithmetic the idea of ``finite approximation'' used to provide computational interpretations of Herbrand's Theorem, and we interpret classical proofs as constructive proofs (with constructive rules for $\vee, \exists$) over a suitable structure \StructureN for the language of natural numbers and maps of G\"odel's system \SystemT. We introduce a new Realizability semantics we call ``Interactive learning-based Realizability'', for Heyting Arithmetic plus \EM_1 (Excluded middle axiom restricted to $\Sigma^0_1$ formulas). Individuals of \StructureN evolve with time, and realizers may ``interact'' with them, by influencing their evolution. We build our semantics over Avigad's fixed point result, but the same semantics may be defined over different constructive interpretations of classical arithmetic (Berardi and de' Liguoro use continuations). Our notion of realizability extends intuitionistic realizability and differs from it only in the atomic case: we interpret atomic realizers as ``learning agents''