Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?

The organization and mining of malaria genomic and post-genomic data is highly motivated by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should therefore be as reliable and versatile as possible. In this context, we examined five aspects of the organization and mining of malaria genomic and post-genomic data: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5) the determination and prediction of protein structures and their molecular docking with drug candidate structures. Progresses toward a grid-enabled chemogenomic knowledge space are discussed.Comment: 43 pages, 4 figures, to appear in Malaria Journa

Adaptive Random Walks on the Class of Web Graph

We study random walk with adaptive move strategies on a class of directed graphs with variable wiring diagram. The graphs are grown from the evolution rules compatible with the dynamics of the world-wide Web [Tadi\'c, Physica A {\bf 293}, 273 (2001)], and are characterized by a pair of power-law distributions of out- and in-degree for each value of the parameter $\beta$, which measures the degree of rewiring in the graph. The walker adapts its move strategy according to locally available information both on out-degree of the visited node and in-degree of target node. A standard random walk, on the other hand, uses the out-degree only. We compute the distribution of connected subgraphs visited by an ensemble of walkers, the average access time and survival probability of the walks. We discuss these properties of the walk dynamics relative to the changes in the global graph structure when the control parameter $\beta$ is varied. For $\beta \geq 3$, corresponding to the world-wide Web, the access time of the walk to a given level of hierarchy on the graph is much shorter compared to the standard random walk on the same graph. By reducing the amount of rewiring towards rigidity limit \beta \to \beta_c \lesss im 0.1, corresponding to the range of naturally occurring biochemical networks, the survival probability of adaptive and standard random walk become increasingly similar. The adaptive random walk can be used as an efficient message-passing algorithm on this class of graphs for large degree of rewiring.Comment: 8 pages, including 7 figures; to appear in Europ. Phys. Journal

A critical cluster analysis of 44 indicators of author-level performance

This paper explores the relationship between author-level bibliometric indicators and the researchers the "measure", exemplified across five academic seniorities and four disciplines. Using cluster methodology, the disciplinary and seniority appropriateness of author-level indicators is examined. Publication and citation data for 741 researchers across Astronomy, Environmental Science, Philosophy and Public Health was collected in Web of Science (WoS). Forty-four indicators of individual performance were computed using the data. A two-step cluster analysis using IBM SPSS version 22 was performed, followed by a risk analysis and ordinal logistic regression to explore cluster membership. Indicator scores were contextualized using the individual researcher's curriculum vitae. Four different clusters based on indicator scores ranked researchers as low, middle, high and extremely high performers. The results show that different indicators were appropriate in demarcating ranked performance in different disciplines. In Astronomy the h2 indicator, sum pp top prop in Environmental Science, Q2 in Philosophy and e-index in Public Health. The regression and odds analysis showed individual level indicator scores were primarily dependent on the number of years since the researcher's first publication registered in WoS, number of publications and number of citations. Seniority classification was secondary therefore no seniority appropriate indicators were confidently identified. Cluster methodology proved useful in identifying disciplinary appropriate indicators providing the preliminary data preparation was thorough but needed to be supplemented by other analyses to validate the results. A general disconnection between the performance of the researcher on their curriculum vitae and the performance of the researcher based on bibliometric indicators was observed.Comment: 28 pages, 7 tables, 2 figures, 2 appendice