Ultra Low-Power Analog Median Filters

The design and implementation of three analog median filter topologies, whose transistors operate in the deep weak-inversion region, is described. The first topology is a differential pairs array, in which drain currents are driven into two nodes in a differential fashion, while the second topology is based on a wide range OTA, which is used to maximize the dynamic range. Finally, the third topology uses three range-extended OTAs. The proposed weak-inversion filters were designed and fabricated in ON Semiconductor 0.5 micrometer technology through MOSIS. Experimental results of three-input fabricated prototypes for all three topologies are show, where power consumptions of 90nW in the first case, and 270nW in the other two cases can be noticed. A dual power supply +/-1.5 Volts were used

Network Archaeology: Uncovering Ancient Networks from Present-day Interactions

Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the Last.fm social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved. Our likelihood-based method finds a probable previous state of the network by reversing the forward growth model. This approach retains node identities so that the history of individual nodes can be tracked. We apply these algorithms to uncover older, non-extant biological and social networks believed to have grown via several models, including duplication-mutation with complementarity, forest fire, and preferential attachment. Through experiments on both synthetic and real-world data, we find that our algorithms can estimate node arrival times, identify anchor nodes from which new nodes copy links, and can reveal significant features of networks that have long since disappeared.Comment: 16 pages, 10 figure

Using perturbation methods and Laplace–Padé approximation to solve nonlinear problems

WOS: 000328081500009In this paper, the perturbation method and Pade transformation are used to provide an approximate solution of elliptic integrals of the second kind and of complete integrals of the first kind. Besides, we used the obtained results to calculate an analytic expression for the period of a simple pendulum. The method has an acceptable accuracy for high values of the initial amplitude, compared to the relative error < 1.7% for initial angles theta <= 70 degree

An Orthogonal-based Self-starting Numerical Integrator for Second Order Initial and Boundary Value Problems ODEs

The direct integration of second order initial and boundary value problems is considered in this paper. We employ a new class of orthogonal polynomials constructed as basis function to develop a two-step hybrid block method (2SHBM) adopting collocation technique. The recursive formula of the class of polynomials have been constructed, and then we give analysis of the basic properties of 2SHBM as findings show that the method is accurate and convergent. The boundary locus of the proposed 2SHBM shows that the new scheme is A-stable

Protein Function Assignment through Mining Cross-Species Protein-Protein Interactions

Background: As we move into the post genome-sequencing era, an immediate challenge is how to make best use of the large amount of high-throughput experimental data to assign functions to currently uncharacterized proteins. We here describe CSIDOP, a new method for protein function assignment based on shared interacting domain patterns extracted from cross-species protein-protein interaction data. Methodology/Principal Findings: The proposed method is assessed both biologically and statistically over the genome of H. sapiens. The CSIDOP method is capable of making protein function prediction with accuracy of 95.42 % using 2,972 gene ontology (GO) functional categories. In addition, we are able to assign novel functional annotations for 181 previously uncharacterized proteins in H. sapiens. Furthermore, we demonstrate that for proteins that are characterized by GO, the CSIDOP may predict extra functions. This is attractive as a protein normally executes a variety of functions in different processes and its current GO annotation may be incomplete. Conclusions/Significance: It can be shown through experimental results that the CSIDOP method is reliable and practical in use. The method will continue to improve as more high quality interaction data becomes available and is readily scalable t

A novel thymidylate synthase from the Vibrionales, Alteromonadales, Aeromonadales, and Pasteurellales (VAAP) clade with altered nucleotide and folate binding sites

Thymidylate synthase (TS, E.C. 2.1.1.45) is a crucial enzyme for de novo deoxythymidine monophosphate (dTMP) biosynthesis. The gene for this enzyme is thyA, which encodes the folate-dependent TS that converts deoxyuridine monophosphate group (dUMP) into (dTMP) using the cofactor 5,10-methylenetetrahydrofolate (mTHF) as a carbon donor. We identified the thyA gene in the genome of the Vibrio parahaemolyticus strain FIM-S1708+ that is innocuous to humans but pathogenic to crustaceans. Surprisingly, we found changes in the residues that bind the substrate dUMP and mTHF, previously postulated as invariant among all TSs known (Finer-Moore, Santi & Stroud, 2003). Interestingly, those amino acid changes were also found in a clade of microorganisms that contains Vibrionales, Alteromonadales, Aeromonadales, and Pasteurellales (VAAP) from the Gammaproteobacteria class. In this work, we studied the biochemical properties of recombinant TS from V. parahemolyticus FIM-S1708+ (VpTS) to address the natural changes in the TS amino acid sequence of the VAAP clade. Interestingly, the Km for dUMP was 27.3 ± 4.3 µM, about one-fold larger compared to other TSs. The Km for mTHF was 96.3 ± 18 µM, about three- to five-fold larger compared to other species, suggesting also loss of affinity. Thus, the catalytic efficiency was between one or two orders of magnitude smaller for both substrates. We used trimethoprim, a common antibiotic that targets both TS and DHFR for inhibition studies. The IC50 values obtained were high compared to other results in the literature. Nonetheless, this molecule could be a lead for the design antibiotics towards pathogens from the VAAP clade. Overall, the experimental results also suggest that in the VAAP clade the nucleotide salvage pathway is important and should be investigated, since the de novo dTMP synthesis appears to be compromised by a less efficient thymidylate synthase

Evaluation of clustering algorithms for protein-protein interaction networks

BACKGROUND: Protein interactions are crucial components of all cellular processes. Recently, high-throughput methods have been developed to obtain a global description of the interactome (the whole network of protein interactions for a given organism). In 2002, the yeast interactome was estimated to contain up to 80,000 potential interactions. This estimate is based on the integration of data sets obtained by various methods (mass spectrometry, two-hybrid methods, genetic studies). High-throughput methods are known, however, to yield a non-negligible rate of false positives, and to miss a fraction of existing interactions. The interactome can be represented as a graph where nodes correspond with proteins and edges with pairwise interactions. In recent years clustering methods have been developed and applied in order to extract relevant modules from such graphs. These algorithms require the specification of parameters that may drastically affect the results. In this paper we present a comparative assessment of four algorithms: Markov Clustering (MCL), Restricted Neighborhood Search Clustering (RNSC), Super Paramagnetic Clustering (SPC), and Molecular Complex Detection (MCODE). RESULTS: A test graph was built on the basis of 220 complexes annotated in the MIPS database. To evaluate the robustness to false positives and false negatives, we derived 41 altered graphs by randomly removing edges from or adding edges to the test graph in various proportions. Each clustering algorithm was applied to these graphs with various parameter settings, and the clusters were compared with the annotated complexes. We analyzed the sensitivity of the algorithms to the parameters and determined their optimal parameter values. We also evaluated their robustness to alterations of the test graph. We then applied the four algorithms to six graphs obtained from high-throughput experiments and compared the resulting clusters with the annotated complexes. CONCLUSION: This analysis shows that MCL is remarkably robust to graph alterations. In the tests of robustness, RNSC is more sensitive to edge deletion but less sensitive to the use of suboptimal parameter values. The other two algorithms are clearly weaker under most conditions. The analysis of high-throughput data supports the superiority of MCL for the extraction of complexes from interaction networks

Analytical Solutions for Systems of Singular Partial Differential-Algebraic Equations

This paper proposes power series method (PSM) in order to find solutions for singular partial differential-algebraic equations (SPDAEs). We will solve three examples to show that PSM method can be used to search for analytical solutions of SPDAEs. What is more, we will see that, in some cases, Padé posttreatment, besides enlarging the domain of convergence, may be employed in order to get the exact solution from the truncated series solutions of PSM