Predicting protein linkages in bacteria: Which method is best depends on task

<p>Abstract</p> <p>Background</p> <p>Applications of computational methods for predicting protein functional linkages are increasing. In recent years, several bacteria-specific methods for predicting linkages have been developed. The four major genomic context methods are: Gene cluster, Gene neighbor, Rosetta Stone, and Phylogenetic profiles. These methods have been shown to be powerful tools and this paper provides guidelines for when each method is appropriate by exploring different features of each method and potential improvements offered by their combination. We also review many previous treatments of these prediction methods, use the latest available annotations, and offer a number of new observations.</p> <p>Results</p> <p>Using <it>Escherichia coli </it>K12 and <it>Bacillus subtilis</it>, linkage predictions made by each of these methods were evaluated against three benchmarks: functional categories defined by COG and KEGG, known pathways listed in EcoCyc, and known operons listed in RegulonDB. Each evaluated method had strengths and weaknesses, with no one method dominating all aspects of predictive ability studied. For functional categories, as previous studies have shown, the Rosetta Stone method was individually best at detecting linkages and predicting functions among proteins with shared KEGG categories while the Phylogenetic profile method was best for linkage detection and function prediction among proteins with common COG functions. Differences in performance under COG versus KEGG may be attributable to the presence of paralogs. Better function prediction was observed when using a weighted combination of linkages based on reliability versus using a simple unweighted union of the linkage sets. For pathway reconstruction, 99 complete metabolic pathways in <it>E. coli </it>K12 (out of the 209 known, non-trivial pathways) and 193 pathways with 50% of their proteins were covered by linkages from at least one method. Gene neighbor was most effective individually on pathway reconstruction, with 48 complete pathways reconstructed. For operon prediction, Gene cluster predicted completely 59% of the known operons in <it>E. coli </it>K12 and 88% (333/418)in <it>B. subtilis</it>. Comparing two versions of the <it>E. coli </it>K12 operon database, many of the unannotated predictions in the earlier version were updated to true predictions in the later version. Using only linkages found by both Gene Cluster and Gene Neighbor improved the precision of operon predictions. Additionally, as previous studies have shown, combining features based on intergenic region and protein function improved the specificity of operon prediction.</p> <p>Conclusion</p> <p>A common problem for computational methods is the generation of a large number of false positives that might be caused by an incomplete source of validation. By comparing two versions of a database, we demonstrated the dramatic differences on reported results. We used several benchmarks on which we have shown the comparative effectiveness of each prediction method, as well as provided guidelines as to which method is most appropriate for a given prediction task.</p

Dynamic tailoring of beam-like structures. Application to High Aspect Ratio unitized box-beam and internal resonant structures

This work is a journey into the dynamic tailoring of beam-like structures which aims to exploit unconventional couplings and nonlinearities to enlarge the design space and improving the performances of engineering systems. Particularly, two examples pertaining dynamic tailoring of aerospace and mechanical systems are investigated in depth. In the first case, the work aims to attain a desired structural performance exploiting typical nonlinear structural phenomena and unconventional couplings offered by the unitized structures. As for the unitized structures, the present work, derives two equivalent plate models of curvilinear stiffened panels namely, constant (or homogenized) stiffness model and variable stiffness model. The models are assessed through finite element analysis. In the spirit of CAS (Circumferentially Asymmetric Stiffness), the equivalent plate stiffness’s are used to determine the cross- sectional beam stiffness’s. The governing equations for the Euler-Bernoulli, anisotropic beam with variable stiffness are derived and then used to address the optimization problem. The objective of the optimization is to attain a desired static or dynamic performance of the unitized beam exploiting the enlarged design space which arises from the stiffness variability and the unconventional couplings. In the second type of system analyzed, the aim is synthesize meaningful topologies for planar resonators. The topology optimization is addressed using as initial guess a ground structure. Motivated by the results of the optimization, a generalized reduced order model is derived for multi-members beam structures. The generalized model have been then specialized for three cases namely, V- Y- and Z-shaped resonators. The analytical solution for the V-shaped resonator is also derived along with the electro-mechanical equations of motion. Different solutions are studied aiming at investigating the effect of the folding angle on to the performances of a V-shaped harvester. Beside the study of the static and dynamic behavior of the systems, the thesis presents two novel optimization algorithms namely, the Stud^P GA and the GERM. The Stud^P GA, is a population based algorithm conceived to enhance the exploration capabilities, and hence the convergence rate, of classical GA. The Stud^P GA has been preliminary assessed through benchmark problems for composite layered structure and then used for the optimization of the stiffeners' path aiming at attaining a desired static or dynamic performances. The GERM (Graph-based Element Removal Method), is a double filtering technique conceived for the topology synthesis of planar ground structures. The GERM has been used, in combination with a standard GA, to address the topology optimization problem of the two types of system namely, planar resonator and compliant structures. The work introduces also the concept of trace-based scaling for predicting the behavior of anisotropic structures. The effectiveness of the trace-based scaling is assessed through comparison between scaled and analytical performances of anisotropic structures