A survey of statistical network models

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.Comment: 96 pages, 14 figures, 333 reference

Genomic and phenotypic signatures of climate adaptation in an Anolis lizard

Integrated knowledge on phenotype, physiology and genomic adaptations is required to understand the effects of climate on evolution. The functional genomic basis of organismal adaptation to changes in the abiotic environment, its phenotypic consequences, and its possible convergence across vertebrates, are still understudied. In this study, we use a comparative approach to verify predicted gene functions for vertebrate thermal adaptation with observed functions underlying repeated genomic adaptations in response to elevation in the lizard Anolis cybotes. We establish a direct link between recurrently evolved phenotypes and functional genomics of altitude-related climate adaptation in three highland and lowland populations in the Dominican Republic. We show that across vertebrates, genes contained in this interactome are expressed within the brain and during development. These results are relevant to elucidate the effect of global climate change across vertebrates, and might aid in furthering insight into gene-environment relationships under disturbances to external homeostasis

Biomedical data integration in computational drug design and bioinformatics

[Abstract In recent years, in the post genomic era, more and more data is being generated by biological high throughput technologies, such as proteomics and transcriptomics. This omics data can be very useful, but the real challenge is to analyze all this data, as a whole, after integrating it. Biomedical data integration enables making queries to different, heterogeneous and distributed biomedical data sources. Data integration solutions can be very useful not only in the context of drug design, but also in biomedical information retrieval, clinical diagnosis, system biology, etc. In this review, we analyze the most common approaches to biomedical data integration, such as federated databases, data warehousing, multi-agent systems and semantic technology, as well as the solutions developed using these approaches in the past few years.Red Gallega de Investigación sobre Cáncer Colorrectal; Ref. 2009/58Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo; 209RT- 0366Instituto de Salud Carlos III; PIO52048Instituto de Salud Carlos III; RD07/0067/0005Ministerio de Industria, Turismo y Comercio; TSI-020110-2009-

A synthetic biology approach for consistent production of plant-made recombinant polyclonal antibodies against snake venom toxins

Antivenoms developed from the plasma of hyperimmunized animals are the only effective treatment available against snakebite envenomation but shortage of supply contributes to the high morbidity and mortality toll of this tropical disease. We describe a synthetic biology approach to affordable and cost-effective antivenom production based on plant-made recombinant polyclonal antibodies (termed pluribodies). The strategy takes advantage of virus superinfection exclusion to induce the formation of somatic expression mosaics in agroinfiltrated plants, which enables the expression of complex antibody repertoires in a highly reproducible manner. Pluribodies developed using toxin-binding genetic information captured from peripheral blood lymphocytes of hyperimmunized camels recapitulated the overall binding activity of the immune response. Furthermore, an improved plant-made antivenom (plantivenom) was formulated using an in vitro selected pluribody against Bothrops asper snake venom toxins and has been shown to neutralize a wide range of toxin activities and provide protection against lethal venom doses in mice.Fil: Julve Parreño, Jose Manuel. Universidad Politécnica de Valencia; EspañaFil: Huet, Estefanía. Universidad Politécnica de Valencia; EspañaFil: Fernández del Carmen, Asun. Universidad Politécnica de Valencia; EspañaFil: Segura, Alvaro. Universidad de Costa Rica; Costa RicaFil: Venturi, Micol. Universidad Politécnica de Valencia; EspañaFil: Gandía, Antoni. Universidad Politécnica de Valencia; EspañaFil: Pan, Wei-Song. Universidad Politécnica de Valencia; EspañaFil: Albaladejo, Irene. Universidad Politécnica de Valencia; EspañaFil: Forment, Javier. Universidad Politécnica de Valencia; EspañaFil: Pla, Davinia. Instituto de Biomedicina de Valencia; EspañaFil: Wigdorovitz, Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Genética; ArgentinaFil: Calvete, Juan J.. Instituto de Biomedicina de Valencia; EspañaFil: Gutiérrez, Carlos. Universidad de Las Palmas de Gran Canaria; EspañaFil: Gutiérrez, José María. Universidad de Costa Rica; Costa RicaFil: Granell, Antonio. Universidad Politécnica de Valencia; EspañaFil: Orzáez, Diego. Universidad Politécnica de Valencia; Españ

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

Background: To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results: To address this challenge we previously developed a generic knowledge management framework, BioXM , which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions: We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development