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PubMed2002

Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.

There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescent dyes). The term normalization refers to the process of removing such variation. A constant adjustment is often used to force the distribution of the intensity log ratios to have a median of zero for each slide. However, such global normalization approaches are not adequate in situations where dye biases can depend on spot overall intensity and/or spatial location within the array. This article proposes normalization methods that are based on robust local regression and account for intensity and spatial dependence in dye biases for different types of cDNA microarray experiments. The selection of appropriate controls for normalization is discussed and a novel set of controls (microarray sample pool, MSP) is introduced to aid in intensity-dependent normalization. Lastly, to allow for comparisons of expression levels across slides, a robust method based on maximum likelihood estimation is proposed to adjust for scale differences among slides.

Animals↗
PubMed2002

Robustness of hen lysozyme monitored by random mutations.

We investigated the robustness of hen lysozyme by using random mutant libraries. Six random mutant libraries containing 1, 1.5, 2, 3, 5 and 14 amino acid mutations per hen lysozyme were systematically constructed by varying the concentrations of Mg(2+) and Mn(2+) on polymerase chain reaction. The mutated genes from the six libraries were cloned to a yeast expression vector and a total of 4000 clones were screened on the basis of lysis activity and ELISA employing monoclonal antibody that recognized only lysozyme with native conformation. About 80% of the clones with an average of two amino acid mutations retained active structure. Almost all clones with an average of five mutations lost active structure. On the other hand, 80% of the clones with an average of two amino acid mutations retained both gross conformation and active structure and 24% of the clones with an average of 14 amino acid mutations retained gross conformation. These results show that gross conformation is robust against mutations and so is active structure to a lesser extent.

Amino Acids↗
PubMed2004

Robust homeostatic control of quadriceps pH during natural locomotor activity in man.

It is generally thought that intracellular pH (pHi) of skeletal muscle falls at least 0.5 units during intense activity, but evidence on natural (i.e., voluntary, two-legged (2L)) locomotor activity in man has exclusively come from invasive studies of upper leg muscle. Here, noninvasive (31)P nuclear magnetic resonance spectroscopy ((31)P NMRS) was used to study human quadriceps muscle energetics and pHi during incremental bicycling exercise to exhaustion in six normally active subjects. Cellular energy charge (CEC; [PCr]/([PCr]+[Pi])) linearly (r 0.90) dropped 83 +/- 3% during ramp exercise to exhaustion from 0.92 +/- 0.01 at rest to 0.16 +/- 0.03 at maximal sustained work rate (WR) (166+/-17 W; range: 108-223 W). Surprisingly, pHi likewise dropped linearly (r 0.82) no more than 0.2 units over the entire range of WR between rest and maximal (pHi 7.08+/-0.01 and 6.84+/-0.02, respectively). But after termination of exercise pHi dropped rapidly to textbook acidic values of 6.6 explaining classic biopsy results. Comparative coresponse analysis of pHi and CEC changes during 2L- vs. 1L-cycling showed that homeostatic control of quadriceps pHi during bicycling is robust and unique to natural locomotor exercise. These results highlight the robustness of the integrative set of physicochemical and physiological control mechanisms in acid-base balance during natural locomotor activity in man.

Adenosine Triphosphate↗
PubMed2000

Similarity and robustness of PET and SPECT binding parameters for benzodiazepine receptors.

The single photon emission computed tomography (SPECT) radiotracer [123I]iomazenil is used to assess benzodiazepine receptor binding parameters. These measurements are relative indices of benzodiazepine receptor concentration (B'max). To evaluate the ability of such indices in accurately accessing the B'max the authors compared them with absolute values of B'max, measured using positron emission tomography (PET). The authors performed SPECT, PET, and magnetic resonance imaging (MRI) studies on a group composed of seven subjects. For SPECT studies, the authors administered a single injection of [123I]iomazenil and estimated the total and specific distribution volumes (DV(T SPECT), DV(S SPECT)) and the binding potential (BP) using unconstrained (BP(SPECT)) and constrained (BP(C SPECT)) compartmental models. For PET studies, the authors used a multiinjection approach with [11C]flumazenil and unlabeled flumazenil to estimate absolute values of receptor concentration, B'max, and some other binding parameters. The authors studied the correlation of different binding parameters with B'max. To study the robustness of the binding parameter measurements at the pixel level, the authors applied a wavelet-based filter to improve signal-to-noise ratio of time-concentration curves, and the calculated kinetic parameters were used to build up parametric images. For PET data, the B'max and the DV(PET) were highly correlated (r = 0.988). This confirms that it is possible to use the DV(PET) to access benzodiazepine receptor density. For SPECT data, the correlation between DV(SPECT) estimated using a two- and three-compartment model was also high (r = 0.999). The DV(T SPECT) and BP(C SPECT) parameters estimated with a constrained three-compartment model or the DV(T''SPECT) parameter estimated with a two-compartment model were also highly correlated to the B'max parameter estimated with PET. Finally, the robustness of the binding parameters allowed the authors to build pixel-by-pixel parametric images using SPECT data.

Adult↗
PubMedDate not supplied

Computing the centerline of a colon: a robust and efficient method based on 3D skeletons.

We present a robust and efficient algorithm for calculating the centerline of a computer-generated colon model created from helical CT image data. The centerline is an essential aid for navigating through complex anatomy such as the colon. Our algorithm involves three steps. In the first step, we generate a 3D skeleton of the binary colon volume using a fast topological thinning algorithm. In the second step, we employ a graph search algorithm to remove extra loops and branches. These loops and branches are caused by holes in the object that are artifacts produced during image segmentation. In the final step, we compute a smooth representation of the centerline by approximating the skeleton with cubic B-splines. This final step is necessary because the skeleton contains many abrupt changes in direction due to the discrete nature of image data. The user supplies two endpoints for the centerline; otherwise, the algorithm is fully automated. Experimental results demonstrate that the algorithm is not only robust but also efficient.

Algorithms↗
PubMed2005

How robust are hospital ranks based on composite performance measures?

BACKGROUND: Composite indices of healthcare performance are an aggregation of underlying individual performance measures. They are increasingly being used to rank healthcare organizations. Although composite indicators present the "big picture" in a way that is easy to interpret, misleading conclusions may be drawn if attention is not paid to key methodological issues in their construction. OBJECTIVES: We examine variability in performance measures in the context of the construction and use of composite measures. We illustrate how variability in the underlying data and the resulting composite may undermine the robustness of performance measures in health care. We also illustrate how variation in the methodological rules applied to aggregate the individual indicators can have an important impact on composite scores. METHODS: We use data for 117 English acute hospitals to illustrate the generic methodological issues. The variance in performance measures is partitioned into "controllable" and "uncontrollable" elements. We create a composite index from the underlying performance indicators and use Monte Carlo simulations to examine the robustness of the composite. RESULTS: Random variation beyond the control of organizations gives rise to considerable uncertainty in hospital scores. Composites are also sensitive to changes made to the weighting system and to the aggregation rules. Some hospitals can jump almost half of the league table as a result of subtle changes. CONCLUSIONS: Great care is warranted in interpreting the results of composite performance measures. Suggestions for their future development are made.

Benchmarking↗
PubMed2006

Multiple feedback loop design in the tryptophan regulatory network of Escherichia coli suggests a paradigm for robust regulation of processes in series.

Biological networks have evolved through adaptation in uncertain environments. Of the different possible design paradigms, some may offer functional advantages over others. These designs can be quantified by the structure of the network resulting from molecular interactions and the parameter values. One may, therefore, like to identify the design motif present in the evolved network that makes it preferable over other alternatives. In this work, we focus on the regulatory networks characterized by serially arranged processes, which are regulated by multiple feedback loops. Specifically, we consider the tryptophan system present in Escherichia coli, which may be conceptualized as three processes in series, namely transcription, translation and tryptophan synthesis. The multiple feedback loop motif results from three distinct negative feedback loops, namely genetic repression, mRNA attenuation and enzyme inhibition. A framework is introduced to identify the key design components of this network responsible for its physiological performance. We demonstrate that the multiple feedback loop motif, as seen in the tryptophan system, enables robust performance to variations in system parameters while maintaining a rapid response to achieve homeostasis. Superior performance, if arising from a design principle, is intrinsic and, therefore, inherent to any similarly designed system, either natural or engineered. An experimental engineering implementation of the multiple feedback loop design on a two-tank system supports the generality of the robust attributes offered by the design.

Escherichia coli↗
PubMed2006

An entropic characterization of protein interaction networks and cellular robustness.

The structure of molecular networks is believed to determine important aspects of their cellular function, such as the organismal resilience against random perturbations. Ultimately, however, cellular behaviour is determined by the dynamical processes, which are constrained by network topology. The present work is based on a fundamental relation from dynamical systems theory, which states that the macroscopic resilience of a steady state is correlated with the uncertainty in the underlying microscopic processes, a property that can be measured by entropy. Here, we use recent network data from large-scale protein interaction screens to characterize the diversity of possible pathways in terms of network entropy. This measure has its origin in statistical mechanics and amounts to a global characterization of both structural and dynamical resilience in terms of microscopic elements. We demonstrate how this approach can be used to rank network elements according to their contribution to network entropy and also investigate how this suggested ranking reflects on the functional data provided by gene knockouts and RNAi experiments in yeast and Caenorhabditis elegans. Our analysis shows that knockouts of proteins with large contribution to network entropy are preferentially lethal. This observation is robust with respect to several possible errors and biases in the experimental data. It underscores the significance of entropy as a fundamental invariant of the dynamical system, and as a measure of structural and dynamical properties of networks. Our analytical approach goes beyond the phenomenological studies of cellular robustness based on local network observables, such as connectivity. One of its principal achievements is to provide a rationale to study proxies of cellular resilience and rank proteins according to their importance within the global network context.

Computer Simulation↗
PubMed2001

Robust stochastic resonance: signal detection and adaptation in impulsive noise.

Stochastic resonance (SR) occurs when noise improves a system performance measure such as a spectral signal-to-noise ratio or a cross-correlation measure. All SR studies have assumed that the forcing noise has finite variance. Most have further assumed that the noise is Gaussian. We show that SR still occurs for the more general case of impulsive or infinite-variance noise. The SR effect fades as the noise grows more impulsive. We study this fading effect on the family of symmetric alpha-stable bell curves that includes the Gaussian bell curve as a special case. These bell curves have thicker tails as the parameter alpha falls from 2 (the Gaussian case) to 1 (the Cauchy case) to even lower values. Thicker tails create more frequent and more violent noise impulses. The main feedback and feedforward models in the SR literature show this fading SR effect for periodic forcing signals when we plot either the signal-to-noise ratio or a signal correlation measure against the dispersion of the alpha-stable noise. Linear regression shows that an exponential law gamma(opt)(alpha)=cA(alpha) describes this relation between the impulsive index alpha and the SR-optimal noise dispersion gamma(opt). The results show that SR is robust against noise "outliers." So SR may be more widespread in nature than previously believed. Such robustness also favors the use of SR in engineering systems. We further show that an adaptive system can learn the optimal noise dispersion for two standard SR models (the quartic bistable model and the FitzHugh-Nagumo neuron model) for the signal-to-noise ratio performance measure. This also favors practical applications of SR and suggests that evolution may have tuned the noise-sensitive parameters of biological systems.

Journal Article↗
PubMed2004

Observation of robust quantum resonance peaks in an atom optics kicked rotor with amplitude noise.

The effect of pulse train noise on the quantum resonance peaks of the atom optics kicked rotor is investigated experimentally. Quantum resonance peaks in the late time mean energy of the atoms are found to be surprisingly robust against all levels of noise applied to the kicking amplitude, while even small levels of noise on the kicking period lead to their destruction. The robustness to amplitude noise of the resonance peak and of the fall-off in mean energy to either side of this peak are explained in terms of the occurrence of stable, epsilon classical dynamics [Nonlinearity 16, 1381 (2003)]] around each quantum resonance.

Journal Article↗
PubMed2005

Optimization of network robustness to waves of targeted and random attacks.

We study the robustness of complex networks to multiple waves of simultaneous (i) targeted attacks in which the highest degree nodes are removed and (ii) random attacks (or failures) in which fractions p(t) and p(r) , respectively, of the nodes are removed until the network collapses. We find that the network design which optimizes network robustness has a bimodal degree distribution, with a fraction r of the nodes having degree k2 = ((k)-1+r)/r and the remainder of the nodes having degree k1=1, where k is the average degree of all the nodes. We find that the optimal value of r is of the order of p(t)/p(r) for p(t)/p(r) << 1.

Journal Article↗
PubMed2006

Robust control for convection suppression in a fluid layer: The effects of boundary properties, actuator lag, and major parameter uncertainties.

The robustness of control is a requirement to maintain a fluid layer at conductive equilibrium heated to a highly supercritical condition. Robustness determines how much uncertainties, or design parameter mismatches, can be tolerated. Both linear stability analysis and three-dimensional fully nonlinear simulations are used for the study of the linear quadratic Gaussian (LQG) controller. The parameter mismatches from the nominal conditions are introduced into the plant model, while the LQG compensator assumes nominal conditions. The mismatches arise from boundary properties, actuator lag, sensor level uncertainty, and wall thickness, as well as from the major parameters such as Prandtl number, Rayleigh number, wave number, and truncation number in the reduced-order model. The results suggest that the LQG compensator action can preserve closed-loop stability at over ten times the critical Rayleigh number, provided that the mismatches in the sensor level and wall thickness are small. Mismatches in the Prandtl number and wall material properties have little impact. Mismatches in Rayleigh number and wave number are relatively benign compared with the sensor and thickness parameters. Techniques for measuring the plant output temperature at multiple levels with sufficient accuracy may be an implementation challenge.

Journal Article↗
PubMed2003

Optimization of robustness and connectivity in complex networks.

Scale-free networks rely on a relatively small number of highly connected nodes to achieve a high degree of interconnectivity and robustness to random failure, but suffer from a high sensitivity to directed attack. In this paper we describe a parameterized family of networks and analyze their connectivity and sensitivity, identifying a network that has an interconnectedness closer to that of a scale-free network, a robustness to attack closer to that of an exponential network, and a resistance to failure better than that of either of those networks.

Models, Biological↗
PubMed2006

Proactive robustness control of heterogeneously loaded networks.

A proactive measure to increase the robustness of heterogeneously loaded networks against cascades of overload failures is proposed. It is based on load-dependent weights. Compared to simple hop weights, respective shortest flow paths turn a previously heterogeneous load distribution into a more homogeneous one for the nodes and links of the network. The use of these flow paths increases the networks robustness and at the same time reduces the investment costs into the networks capacity layout. These findings are of relevance for critical infrastructures like communication and transportation networks.

Journal Article↗
PubMed2004

Robust-LongSAGE (RL-SAGE): a substantially improved LongSAGE method for gene discovery and transcriptome analysis.

Serial analysis of gene expression (SAGE) is a widely used technique for large-scale transcriptome analysis in mammalian systems. Recently, a modified version called LongSAGE (S. Saha, A.B. Sparks, C. Rago, V. Akmaev, C.J. Wang, B. Vogelstein, K.W. Kinzler [2002] Nat Biotechnol 20: 508-512) was reported by increasing tag length up to 21 bp. Although the procedures for these two methods are similar, a detailed protocol for LongSAGE library construction has not been reported yet, and several technical difficulties associated with concatemer cloning and purification have not been solved. In this study, we report a substantially improved LongSAGE method called Robust-LongSAGE, which has four major improvements when compared with the previously reported protocols. First, a small amount of mRNA (50 ng) was enough for a library construction. Second, enhancement of cDNA adapter and ditag formation was achieved through an extended ligation period (overnight). Third, only 20 ditag polymerase chain reactions were needed to obtain a complete library (up to 90% reduction compared with the original protocols). Fourth, concatemers were partially digested with NlaIII before cloning into vector (pZEro-1), greatly improving cloning efficiency. The significant contribution of Robust-LongSAGE is that it solved the major technical difficulties, such as low cloning efficiency and small insert sizes associated with existing SAGE and LongSAGE protocols. Using this protocol, one can generate two to three libraries, each containing over 4.5 million tags, within a month. We recently have constructed five libraries from rice (Oryza sativa), one from maize (Zea mays), and one from the rice blast fungus (Magnaporthe grisea).

Base Sequence↗
PubMed2001

Hierarchical estimation of a dense deformation field for 3-D robust registration.

A new method for medical image registration is formulated as a minimization problem involving robust estimators. We propose an efficient hierarchical optimization framework which is both multiresolution and multigrid. An anatomical segmentation of the cortex is introduced in the adaptive partitioning of the volume on which the multigrid minimization is based. This allows to limit the estimation to the areas of interest, to accelerate the algorithm, and to refine the estimation in specified areas. At each stage of the hierarchical estimation, we refine current estimate by seeking a piecewise affine model for the incremental deformation field. The performance of this method is numerically evaluated on simulated data and its benefits and robustness are shown on a database of 18 magnetic resonance imaging scans of the head.

Computer Simulation↗
PubMed2000

Genetic algorithms for a robust 3-D MR-CT registration.

The aim of this paper is to present an original usage of genetic algorithms as a robust search space sampler in application to 3-D medical image elastic registration. An overview of the standard steps of a registration algorithm is given. We focus on the genetic algorithms use and particularly on the problem of extraction of the optimal solution among the final genetic population. We provide an original encoding scheme relying on a structural approach of point matching and then point out the need for a local optimization process. We then illustrate the algorithm with a concrete registration example and assert the results with a direct multivolume rendering tool. Finally, the algorithm is applied on the vanderbilt medical image database to assert the robustness and in order to compare it with other techniques.

Algorithms↗
PubMed2001

Two-dimensional noise-robust blind deconvolution of ultrasound images.

This paper presents a new method for 2-D blind homomorphic deconvolution of medical B-scan ultrasound images. The method is based on noise-robust 2-D phase unwrapping and a noise-robust procedure to estimate the pulse in the complex cepstrum domain. Ordinary Wiener filtering is used in the subsequent deconvolution. The resulting images became much sharper with better defined tissue structures compared with the ordinary images. The deconvolved images had a resolution gain along the order of 3 to 7, and the signal-to-noise ratio (SNR) doubled for many of the images used in our experiments. The method gave stable results with respect to noise and grey levels through several image sequences.

Adult↗