Explorative search of distributed bio-data to answer complex biomedical questions

Background The huge amount of biomedical-molecular data increasingly produced is providing scientists with potentially valuable information. Yet, such data quantity makes difficult to find and extract those data that are most reliable and most related to the biomedical questions to be answered, which are increasingly complex and often involve many different biomedical-molecular aspects. Such questions can be addressed only by comprehensively searching and exploring different types of data, which frequently are ordered and provided by different data sources. Search Computing has been proposed for the management and integration of ranked results from heterogeneous search services. Here, we present its novel application to the explorative search of distributed biomedical-molecular data and the integration of the search results to answer complex biomedical questions. Results A set of available bioinformatics search services has been modelled and registered in the Search Computing framework, and a Bioinformatics Search Computing application (Bio-SeCo) using such services has been created and made publicly available at http://www.bioinformatics.deib.polimi.it/bio-seco/seco/. It offers an integrated environment which eases search, exploration and ranking-aware combination of heterogeneous data provided by the available registered services, and supplies global results that can support answering complex multi-topic biomedical questions. Conclusions By using Bio-SeCo, scientists can explore the very large and very heterogeneous biomedical-molecular data available. They can easily make different explorative search attempts, inspect obtained results, select the most appropriate, expand or refine them and move forward and backward in the construction of a global complex biomedical query on multiple distributed sources that could eventually find the most relevant results. Thus, it provides an extremely useful automated support for exploratory integrated bio search, which is fundamental for Life Science data driven knowledge discovery

Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks

For hard computational problems, stochastic local search has proven to be a competitive approach to finding optimal or approximately optimal problem solutions. Two key research questions for stochastic local search algorithms are: Which algorithms are effective for initialization? When should the search process be restarted? In the present work we investigate these research questions in the context of approximate computation of most probable explanations (MPEs) in Bayesian networks (BNs). We introduce a novel approach, based on the Viterbi algorithm, to explanation initialization in BNs. While the Viterbi algorithm works on sequences and trees, our approach works on BNs with arbitrary topologies. We also give a novel formalization of stochastic local search, with focus on initialization and restart, using probability theory and mixture models. Experimentally, we apply our methods to the problem of MPE computation, using a stochastic local search algorithm known as Stochastic Greedy Search. By carefully optimizing both initialization and restart, we reduce the MPE search time for application BNs by several orders of magnitude compared to using uniform at random initialization without restart. On several BNs from applications, the performance of Stochastic Greedy Search is competitive with clique tree clustering, a state-of-the-art exact algorithm used for MPE computation in BNs

Numerical Modeling of Multiphase, Turbulent Galactic Disks with Star Formation Feedback

Star formation is self-regulated by its feedback that drives turbulence and heats the gas. In equilibrium, the star formation rate (SFR) should be directly related to the total (thermal plus turbulent) midplane pressure and hence the total weight of the diffuse gas if energy balance and vertical dynamical equilibrium hold simultaneously. To investigate this quantitatively, we utilize numerical hydrodynamic simulations focused on outer-disk regions where diffuse atomic gas dominates. By analyzing gas properties at saturation, we obtain relationships between the turbulence driving and dissipation rates, heating and cooling rates, the total midplane pressure and the total weight of gas, and the SFR and the total midplane pressure. We find a nearly linear relationship between the SFR and the midplane pressure consistent with the theoretical prediction.Comment: 2 pages, 1 figure. To appear in the proceeding of the IAU GA XXVIII, Special Session 12: Modern Views of the Interstellar Mediu

Understanding grapevine-microbiome interactions: implications for viticulture industry.

Until recently, the analysis of complex communities such as that of the grapevine-microbe holobiont has been limited by the fact that most microbes are not culturable under laboratory conditions (less than 1%). However, metagenomics, the study of the genetic material recovered directly from environmental samples without the need for enrichment or of culturing, has led to open an unprecedented era in the field of microbiology. Importantly, this technological advance has now become so pervasive that it is being regularly applied to explore soils and plants of agricultural interest. Interestingly, many large companies are taking notice, with significant financial investment being used to exploring ways to manipulate the productivity, disease resistance and stress tolerance for crops by influencing the microbiome. To understand which microbes one needs to manipulate to influence this valuable characteristics, we need to sequence the microbiome and capture the genetic and hence functional metabolic information contained therein. For viticulture and other agricultural fields where the crop is also associated to particular flavor properties that may also be manipulated, understanding how the bacteria, fungi and viruses influence the development and hence chemical makeup of the crop is essential

Materialization strategies for web based search computing applications

In the thesis we provide a characterization of view materialization in the context of multi domain heterogeneous search application. Web data view materialization is presented as a solution for technical constraints and problems implied by the unknown structure of the web data sources. The web data materialization model extends the search computing (SeCo) multi-layered model, where the search services are registered in a service repository that describes the functional (e.g. invocation end-point, input and output attributes) information of data end-points. Our first research goal is to solve the problem of finding a sequence of access patterns, which when executed produces a materialization output. For the first research goal we make the following novel contributions: 1) Formulation of the building blocks for the materialization feasibility analysis; 2) Definition of the materialization feasibility analysis method and the accompanying algorithms; 3) A detailed empirical study conducted on a set of materialization tasks ranging in their schema dependency complexity. Our second research goal is the optimization of the materialization process so that the most optimal sequence in terms of materialization output efficiency and quality, executes at all times. For this goal we make the following novel contributions: 1) Formulation of a set of performance dimensions and their metrics for web source materialization; 2) A cost model that utilizes optimization metrics in order to qualitatively differentiate between web services in terms of materialization time; 3) A query optimization procedure that explores the characteristics of the underlying source data domain in order to prioritize the execution of the most productive queries in terms of their data harvesting power; 4) Materialization process optimization strategies based on the web source performance dimension metrics and query optimization procedure; 5) A detailed empirical study conducted on several relevant web based data sources that clearly shows the effectiveness of the proposed solution

Ground-State Energy and Spin Gap of Spin-1/2 Kagome Heisenberg Antiferromagnetic Clusters: Large Scale Exact Diagonalization Results

We present a comprehensive list of ground state energies and spin gaps of finite kagome clusters with up to 42 spins obtained using large-scale exact diagonalization techniques. This represents the current limit of this exact approach. For a fixed number of spins N we study several cluster shapes under periodic boundary conditions in both directions resulting in a toroidal geometry. The clusters are characterized by their side length and diagonal as well as the shortest "Manhattan" diameter of the torii. A finite-size scaling analysis of the ground state energy as well as the spin gap is then performed in terms of the shortest toroidal diameter as well as the shortest "Manhattan" diameter. The structure of the spin-spin correlations further supports the importance of short loops wrapping around the torii.Comment: 4 pages, 4 figures, added one referenc