Post-transcriptional knowledge in pathway analysis increases the accuracy of phenotypes classification

Motivation: Prediction of phenotypes from high-dimensional data is a crucial task in precision biology and medicine. Many technologies employ genomic biomarkers to characterize phenotypes. However, such elements are not sufficient to explain the underlying biology. To improve this, pathway analysis techniques have been proposed. Nevertheless, such methods have shown lack of accuracy in phenotypes classification. Results: Here we propose a novel methodology called MITHrIL (Mirna enrIched paTHway Impact anaLysis) for the analysis of signaling pathways, which has built on top of the work of Tarca et al., 2009. MITHrIL extends pathways by adding missing regulatory elements, such as microRNAs, and their interactions with genes. The method takes as input the expression values of genes and/or microRNAs and returns a list of pathways sorted according to their deregulation degree, together with the corresponding statistical significance (p-values). Our analysis shows that MITHrIL outperforms its competitors even in the worst case. In addition, our method is able to correctly classify sets of tumor samples drawn from TCGA. Availability: MITHrIL is freely available at the following URL: http://alpha.dmi.unict.it/mithril

Exploring the Role of Interdisciplinarity in Physics: Success, Talent and Luck

Although interdisciplinarity is often touted as a necessity for modern research, the evidence on the relative impact of sectorial versus to interdisciplinary science is qualitative at best. In this paper we leverage the bibliographic data set of the American Physical Society to quantify the role of interdisciplinarity in physics, and that of talent and luck in achieving success in scientific careers. We analyze a period of 30 years (1980-2009) tagging papers and their authors by means of the Physics and Astronomy Classification Scheme (PACS), to show that some degree of interdisciplinarity is quite helpful to reach success, measured as a proxy of either the number of articles or the citations score. We also propose an agent-based model of the publication-reputation-citation dynamics reproduces the trends observed in the APS data set. On the one hand, the results highlight the crucial role of randomness and serendipity in real scientific research; on the other, they shed light on a counter-intuitive effect indicating that the most talented authors are not necessarily the most successful ones.Comment: 21 pages, 19 figure

TemporalRI: subgraph isomorphism in temporal networks with multiple contacts

AbstractTemporal networks are graphs where each edge is associated with a timestamp denoting when two nodes interact. Temporal Subgraph Isomorphism (TSI) aims at retrieving all the subgraphs of a temporal network (called target) matching a smaller temporal network (called query), such that matched target edges appear in the same chronological order of corresponding query edges. Few algorithms have been proposed to solve the TSI problem (or variants of it) and most of them are applicable only to small or specific queries. In this paper we present TemporalRI, a new subgraph isomorphism algorithm for temporal networks with multiple contacts between nodes, which is inspired by RI algorithm. TemporalRI introduces the notion of temporal flows and uses them to filter the search space of candidate nodes for the matching. Our algorithm can handle queries of any size and any topology. Experiments on real networks of different sizes show that TemporalRI is very efficient compared to the state-of-the-art, especially for large queries and targets

Establish the expected number of induced motifs on unlabeled graphs through analytical models

AbstractComplex networks are usually characterized by the presence of small and recurrent patterns of interactions between nodes, called network motifs. These small modules can help to elucidate the structure and the functioning of complex systems. Assessing the statistical significance of a pattern as a motif in a network G is a time consuming task which entails the computation of the expected number of occurrences of the pattern in an ensemble of random graphs preserving some features of G, such as the degree distribution. Recently, few models have been devised to analytically compute expectations of the number of non-induced occurrences of a motif. Less attention has been payed to the harder analysis of induced motifs. Here, we illustrate an analytical model to derive the mean number of occurrences of an induced motif in an unlabeled network with respect to a random graph model. A comprehensive experimental analysis shows the effectiveness of our approach for the computation of the expected number of induced motifs up to 10 nodes. Finally, the proposed method is helpful when running subgraph counting algorithms to get the number of occurrences of a topology become unfeasible

A-to-I RNA Editing: Current Knowledge Sources and Computational Approaches with Special Emphasis on Non-Coding RNA Molecules

RNA editing is a dynamic mechanism for gene regulation attained through the alteration of the sequence of primary RNA transcripts. A-to-I (Adenosine-to-Inosine) RNA editing, which is catalyzed by members of the Adenosine Deaminase Acting on RNA (ADAR) family of enzymes, is the most common post-transcriptional modification in humans. The ADARs bind double-stranded regions and deaminate adenosine (A) into inosine (I), which in turn is interpreted by the translation and splicing machineries as guanosine (G). In recent years, this modification has been discovered to occur not only in coding RNAs but also in non-coding RNAs (ncRNA), such as microRNAs (miRNAs), small interfering RNAs (siRNAs), transfer RNAs (tRNAs), and long non-coding RNAs (lncRNAs). This may have several consequences, such as the creation or disruption of microRNA/mRNA binding sites, and thus affect the biogenesis, stability, and target recognition properties of ncRNAs. The malfunction of the editing machinery is not surprisingly associated with various human diseases, such as neurodegenerative, cardiovascular and carcinogenic diseases.Despite the enormous efforts made so far, the real biological function of this phenomenon, as well as the features of the ADAR substrate, in particular in non-coding RNAs, has still not been fully understood. In this work we focus on the current knowledge of RNA editing on ncRNA molecules and provide a few examples of computational approaches to elucidate its biological function

Prediction of human targets for viral-encoded microRNAs by thermodynamics and empirical constraints

MicroRNAs (miRNAs) are small RNA molecules that modulate gene expression through degradation of specific mRNAs and/or repression of their translation. miRNAs are involved in both physiological and pathological processes, such as apoptosis and cancer. Their presence has been demonstrated in several organisms as well as in viruses. Virus encoded miRNAs can act as viral gene expression regulators, but they may also interfere with the expression of host genes. Viral miRNAs may control host cell proliferation by targeting cell-cycle and apoptosis regulators. Therefore, they could be involved in cancer pathogenesis. Computational prediction of miRNA/target pairs is a fundamental step in these studies. Here, we describe the use of miRiam, a novel program based on both thermodynamics features and empirical constraints, to predict viral miRNAs/human targets interactions. miRiam exploits target mRNA secondary structure accessibility and interaction rules, inferred from validated miRNA/mRNA pairs. A set of genes involved in apoptosis and cell-cycle regulation was identified as target for our studies. This choice was supported by the knowledge that DNA tumor viruses interfere with the above processes in humans. miRNAs were selected from two cancer-related viruses, Epstein-Barr Virus (EBV) and Kaposi-Sarcoma-Associated Herpes Virus (KSHV). Results show that several transcripts possess potential binding sites for these miRNAs. This work has produced a set of plausible hypotheses of involvement of v-miRNAs and human apoptosis genes in cancer development. Our results suggest that during viral infection, besides the protein-based host regulation mechanism, a post-transcriptional level interference may exist. miRiam is freely available for downloading at http://ferrolab.dmi.unict.it/miriam

An Empirical Cross-Country Assessment of the Nexuses Between Insurance, Economic Growth, Human Development, and Institutional Quality

29 p.We contribute to the empirical literature exploring jointly the three nexuses between insurance development with economic growth, institutional, and human development, which in the past were analyzed separately. We built one database for 59 countries and selected evidence from 254 variables using principal component analysis. We hypothesize that “better institutions bring more opportunities for the development of the insurance sector through its impulse to economic growth and human development, which in turn generate an insurance demand increase to protect the enhanced amount and value of human and physical capital.” We estimate a cross-country recursive econometric model to corroborate the hypothesis.Contribuimos a la literatura empírica explorando conjuntamente los tres nexos entre el desarrollo de seguros con el crecimiento económico, institucional y humano, que en el pasado se analizaban por separado. Construimos una base de datos para 59 países y seleccionamos evidencia de 254 variables utilizando el análisis de componentes principales. Nuestra hipótesis es que “mejores instituciones brindan más oportunidades para el desarrollo del sector de seguros a través de su impulso al crecimiento económico y el desarrollo humano, lo que a su vez genera un aumento en la demanda de seguros para proteger la mayor cantidad y valor del capital humano y físico”. Estimamos un modelo econométrico recursivo entre países para corroborar la hipótesis

A Literature Review of the Nexuses Between Insurance, Economics, Institutions, and Human Development

30 p.A detailed survey of the literature examines the efforts made to establish the conceptual and empirical links between the development (penetration and density) of the insurance market and economic growth, insurance and institutional development, insurance, and human development, respectively. Accumulated evidence tests the hypothesis of a positive association (correlation and/or causality) between insurance and economic growth, insurance and institutions, and insurance and human development, the latter as measured by some internationally accepted indicators. The studies encompass different countries, and various time windows and employ disparate methods. This review puts together those results and permits recognizing stylized facts.Una revisión detallada de la literatura examina los esfuerzos realizados para establecer los vínculos conceptuales y empíricos entre el desarrollo (penetración y densidad) del mercado de seguros y el crecimiento económico, el desarrollo institucional y de seguros, los seguros y el desarrollo humano, respectivamente. La evidencia acumulada contrasta la hipótesis de una asociación positiva (correlación y/o causalidad) entre seguros y crecimiento económico, seguros e instituciones, y seguros y desarrollo humano, este último medido por algunos indicadores internacionalmente aceptados. Los estudios abarcan diferentes países y varias ventanas de tiempo y emplean métodos dispares. Esta revisión reúne esos resultados y permite reconocer hechos estilizado

SING: Subgraph search In Non-homogeneous Graphs

<p>Abstract</p> <p>Background</p> <p>Finding the subgraphs of a graph database that are isomorphic to a given query graph has practical applications in several fields, from cheminformatics to image understanding. Since subgraph isomorphism is a computationally hard problem, indexing techniques have been intensively exploited to speed up the process. Such systems filter out those graphs which cannot contain the query, and apply a subgraph isomorphism algorithm to each residual candidate graph. The applicability of such systems is limited to databases of small graphs, because their filtering power degrades on large graphs.</p> <p>Results</p> <p>In this paper, SING (Subgraph search In Non-homogeneous Graphs), a novel indexing system able to cope with large graphs, is presented. The method uses the notion of <it>feature</it>, which can be a small subgraph, subtree or path. Each graph in the database is annotated with the set of all its features. The key point is to make use of feature locality information. This idea is used to both improve the filtering performance and speed up the subgraph isomorphism task.</p> <p>Conclusions</p> <p>Extensive tests on chemical compounds, biological networks and synthetic graphs show that the proposed system outperforms the most popular systems in query time over databases of medium and large graphs. Other specific tests show that the proposed system is effective for single large graphs.</p

NetMatch: a Cytoscape plugin for searching biological networks.

Abstract Summary: NetMatch is a Cytoscape plugin which allows searching biological networks for subcomponents matching a given query. Queries may be approximate in the sense that certain parts of the subgraph-query may be left unspecified. To make the query creation process easy, a drawing tool is provided. Cytoscape is a bioinformatics software platform for the visualization and analysis of biological networks. Availability: The full package, a tutorial and associated examples are available at the following web sites: http://alpha.dmi.unict.it/~ctnyu/netmatch.html, http://baderlab.org/Software/NetMatch Contact: [email protected]