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PubMed2005

A robust algorithm for ratio estimation in two-color microarray experiments.

The reliability of the algorithms for ratio estimation in two-color microarray image analysis is very important, as these ratios build up the primary source of information for the subsequent analytical procedures (normalization, clustering, classification, etc). Although various algorithms already exist, there is still a need to develop procedures having higher levels of accuracy and robustness. We present a statistical procedure for the detection and removal of aberrant pixels in two-color microarray images. It is based on a linear regression approach, assuming reasonably high level of correlation between the two color channels. This procedure ensures more robust ratio estimation for the spots in both linear regression and traditional segmentation algorithms. The developed algorithms have been evaluated using simulated artificial images and experimental images of different designs. A demonstration version of the software can be downloaded from http://bioinfo.curie.fr/projects/maia/.

Algorithms↗
PubMedDate not supplied

Medical image segmentation with knowledge-guided robust active contours.

Medical image segmentation techniques typically require some form of expert human supervision to provide accurate and consistent identification of anatomic structures of interest. A novel segmentation technique was developed that combines a knowledge-based segmentation system with a sophisticated active contour model. This approach exploits the guidance of a higher-level process to robustly perform the segmentation of various anatomic structures. The user need not provide initial contour placement, and the high-level process carries out the required parameter optimization automatically. Knowledge about the anatomic structures to be segmented is defined statistically in terms of probability density functions of parameters such as location, size, and image intensity (eg, computed tomographic [CT] attenuation value). Preliminary results suggest that the performance of the algorithm at chest and abdominal CT is comparable to that of more traditional segmentation techniques like region growing and morphologic operators. In some cases, the active contour-based technique may outperform standard segmentation methods due to its capacity to fully enforce the available a priori knowledge concerning the anatomic structure of interest. The active contour algorithm is particularly suitable for integration with high-level image understanding frameworks, providing a robust and easily controlled low-level segmentation tool. Further study is required to determine whether the proposed algorithm is indeed capable of providing consistently superior segmentation.

Algorithms↗
PubMed2007

Impaired NO-mediated vasodilation with increased superoxide but robust EDHF function in right ventricular arterial microvessels of pulmonary hypertensive rats.

Pulmonary hypertension (PH) causes right ventricular (RV) hypertrophy and, according to the extent of pressure overload, eventual heart failure. We tested the hypothesis that the mechanical stress in PH-RV impairs the vasoreactivity of the RV coronary microvessels of different sizes with increased superoxide levels. Five-week-old male Sprague-Dawley rats were injected with monocrotaline (n=126) to induce PH or with saline as controls (n=114). After 3 wk, coronary arterioles (diameter = 30-100 microm) and small arteries (diameter = 100-200 microm) in the RV were visualized using intravital videomicroscopy. We evaluated ACh-induced vasodilation alone, in the presence of N(omega)-nitro-L-arginine methyl ester (L-NAME), in the presence of tetraethylammonium (TEA) or catalase with or without L-NAME, and in the presence of SOD. The degree of suppression in vasodilation by L-NAME and TEA was used as indexes of the contributions of endothelial nitric oxide (NO) and endothelium-derived hyperpolarizing factor (EDHF), respectively. In PH rats, ACh-induced vasodilation was significantly attenuated in both arterioles and small arteries, especially in arterioles. This decreased vasodilation was largely attributable to reduced NO-mediated vasoreactivity, whereas the EDHF-mediated vasodilation was relatively robust. The suppressive effect on arteriolar vasodilation by catalase was similar to TEA in both groups. Superoxide, as measured by lucigenin chemiluminescence, was significantly elevated in the RV tissues in PH. SOD significantly ameliorated the impairment of ACh-induced vasodilation in PH. Robust EDHF function will play a protective role in preserving coronary microvascular homeostasis in the event of NO dysfunction with increased superoxide levels.

Acetylcholine↗
PubMed2006

Muscle synergy organization is robust across a variety of postural perturbations.

We recently showed that four muscle synergies can reproduce multiple muscle activation patterns in cats during postural responses to support surface translations. We now test the robustness of functional muscle synergies, which specify muscle groupings and the active force vectors produced during postural responses under several biomechanically distinct conditions. We aimed to determine whether such synergies represent a generalized control strategy for postural control or if they are merely specific to each postural task. Postural responses to multidirectional translations at different fore-hind paw distances and to multidirectional rotations at the preferred stance distance were analyzed. Five synergies were required to adequately reconstruct responses to translation at the preferred stance distance-four were similar to our previous analysis of translation, whereas the fifth accounted for the newly added background activity during quiet stance. These five control synergies could account for > 80% total variability or r2 > 0.6 of the electromyographic and force tuning curves for all other experimental conditions. Forces were successfully reconstructed but only when they were referenced to a coordinate system that rotated with the limb axis as stance distance changed. Finally, most of the functional muscle synergies were similar across all of the six cats in terms of muscle synergy number, synergy activation patterns, and synergy force vectors. The robustness of synergy organization across perturbation types, postures, and animals suggests that muscle synergies controlling task-variables are a general construct used by the CNS for balance control.

Animals↗
PubMed1999

Robust suppression of afferent-induced excitation in the rat spinal dorsal horn after conditioning low-frequency stimulation.

The neuronal plasticity in the spinal dorsal horn induced after conditioning low-frequency stimulation of afferent A fibers, and its relationship with spinal inhibitory networks, was investigated with an optical-imaging method that detects neuronal excitation. High-intensity single-pulse stimulation of the dorsal root activating both A and C fibers evoked an optical response in the dorsal horn in transverse slices of 12- to 25-day-old rat spinal cords stained with a voltage-sensitive dye, RH-482. The optical response, reflecting the net excitation of neuronal elements along the thickness of each slice, was suppressed after a conditioning low-frequency stimulation (0.2-1 Hz for 10 min) to A fibers in the dorsal root. The degree of suppression was largest in the lamina II of the dorsal horn (48% reduction), where the majority of C fibers terminate, and much less in the deeper dorsal horn (5% reduction in laminae III-IV). The onset of suppression was somewhat slow; after the low-frequency stimulation, the magnitude of excitation gradually decreased, reached the maximum effect 30 min after the conditioning, and remained at the suppressed level for >1 h. Suppression was not observed when the low-frequency stimulation was given during a 20-min perfusion with a solution containing an NMDA-receptor antagonist, DL-2-amino-5-phosphonovaleric acid (30 microM). A brief application of an opioid-receptor antagonist, naloxone (0.5 microM), inhibited the induction, but not the maintenance, of low-frequency stimulus-induced suppression. However, treatments with the GABA(A) receptor antagonist bicuculline (1 microM) and the glycine receptor antagonist strychnine (0.3 microM) did not affect suppression induction and maintenance. In conclusion, conditioning low-frequency stimulation to A fibers interferes with the afferent-induced excitation in the dorsal horn. The low-frequency stimulation-induced suppression is maintained by a reduction of glutamatergic excitatory transmissions in the dorsal horn, not by an enhanced inhibition. Activation of the spinal opioid-mediated system by low-frequency stimulation, but not the inhibitory amino acid-mediated system, is necessary to initiate robust suppression. The long-term depression of afferent synaptic efficacy onto excitatory interneurons likely takes the primary role in the robust suppression of neuronal excitation in the dorsal horn.

2-Amino-5-phosphonovalerate↗
PubMed2003

Efficiency robust tests for mapping quantitative trait loci using extremely discordant sib pairs.

In 1972, Haseman and Elston proposed a pioneering regression method for mapping quantitative trait loci using randomly selected sib pairs. Recently, the statistical power of their method was shown to be increased when extremely discordant sib pairs are ascertained. While the precise genetic model may not be known, prior information that constrains IBD probabilities is often available. We investigate properties of tests that are robust against model uncertainty and show that the power gain from further constraining IBD probabilities is marginal. The additional linkage information contained in the trait values can be incorporated by combining the Haseman-Elston regression method and a robust allele sharing test.

Chromosome Mapping↗
PubMed1975

Endocrine control of skeletal robusticity.

Changes of skeletal robusticity result from a mosaic response of various parts of the skeleton to given endocrine changes. The character of these reactions corresponds to that of muscles which act as selective target areas for specific hormones. Robusticity changes are mediated by increases or decreases of the length and weight of the bones. The changes are probably species- or even subspecies-specific.

Animals↗
PubMed2005

A robust information clustering algorithm.

We focus on the scenario of robust information clustering (RIC) based on the minimax optimization of mutual information (MI). The minimization of MI leads to the standard mass-constrained deterministic annealing clustering, which is an empirical risk-minimization algorithm. The maximization of MI works out an upper bound of the empirical risk via the identification of outliers (noisy data points). Furthermore, we estimate the real risk VC-bound and determine an optimal cluster number of the RIC based on the structural risk-minimization principle. One of the main advantages of the minimax optimization of MI is that it is a nonparametric approach, which identifies the outliers through the robust density estimate and forms a simple data clustering algorithm based on the square error of the Euclidean distance.

Algorithms↗
PubMed1998

A Fast and Robust Cluster Update Algorithm for Image Segmentation in Spin-Lattice Models Without Annealing. Visual Latencies Revisited.

Image segmentation in spin-lattice models relies on the fast and reliable assignment of correct labels to those groups of spins that represent the same object. Commonly used local spin-update algorithms are slow because in each iteration only a single spin is flipped and a careful annealing schedule has to be designed in order to avoid local minima and correctly label larger areas. Updating of complete spin clusters is more efficient, but often clusters that should represent different objects will be conjoined. In this study, we propose a cluster update algorithm that, similar to most local update algorithms, calculates an energy function and determines the probability for flipping a whole cluster of spins by the energy gain calculated for a neighborhood of the regarded cluster. The novel algorithm, called energy-based cluster update (ECU algorithm), is compared to its predecessors. A convergence proof is derived, and it is shown that the algorithm outperforms local update algorithms by far in speed and reliability. At the same time it is more robust and noise tolerant than other versions of cluster update algorithms, making annealing completely unnecessary. The reduction in computational effort achieved this way allows us to segment real images in about 1-5 sec on a regular workstation. The ECU-algorithm can recover fine details of the images, and it is to a large degree robust with respect to luminance-gradients across objects. In a final step, we introduce luminance dependent visual latencies (Opara and Worgotter, 1996; Worgotter, Opara, Funke, and Eysel, 1996) into the spin-lattice model. This step guarantees that only spins representing pixels with similar luminance become activated at the same time. The energy function is then computed only for the interaction of the regarded cluster with the currently active spins. This latency mechanism improves the quality of the image segmentation by another 40%. The results shown are based on the evaluation of gray-level differences. It is important to realize that all algorithmic components can be transferred easily to arbitrary image features, like disparity, texture, and motion.

Journal Article↗
PubMed2007

Second-order cone programming formulations for robust multiclass classification.

Multiclass classification is an important and ongoing research subject in machine learning. Current support vector methods for multiclass classification implicitly assume that the parameters in the optimization problems are known exactly. However, in practice, the parameters have perturbations since they are estimated from the training data, which are usually subject to measurement noise. In this article, we propose linear and nonlinear robust formulations for multiclass classification based on the M-SVM method. The preliminary numerical experiments confirm the robustness of the proposed method.

Artificial Intelligence↗
PubMed2004

Robust motor speed control under time varying loads in moving actuator type artificial heart (AnyHeart).

The Moving Actuator type artificial heart(AnyHeart) as well as many other artificial hearts uses a motor as its power source. For controllability of control parameters such as pump rate, pump output, blood pressure profile and flow form, the precise motor speed control is important. However, because the implantable device has limited carrying capacity of hardware components in size and number, applying diverse motor control methods are not possible. In addition, the existing PI (Proportional-Integral) motor controller does not show satisfactory performance. A new controller that is sufficiently robust for the changes of load and physical system parameters has been designed and tested. The robust speed controller is based on the sliding mode control method that is applicable to a system of which the ranges of uncertainty in physical parameters are known. In a mock circulation system test, the actual speed showed good tracking characteristics in respect to the reference speed. Fast follow-up characteristics were also observed under high afterload and speed conditions. The speed error, current and power consumption were reduced by about 40%. The proposed control technique overcomes the limitations of the PI controller, and makes important improvements in both performance and stability.

Algorithms↗
PubMed1996

Robustness considerations in Bayesian analysis.

All statistical analyses demand uncertain inputs or assumptions. This is especially true of Bayesian analyses. In addition to the usual concerns about the agreement of the data and model, a Bayesian must contemplate the effect of an uncertain prior specification. The degree to which inferences are robust to changes in the prior is of primary interest. This article discusses some robust techniques that have been suggested in the literature. One goal is to make apparent the relevance of some of these techniques to biostatistical work.

Adrenergic beta-Antagonists↗
PubMed2006

Histone acetylation is associated with differential gene expression in the rapid and robust memory CD8(+) T-cell response.

To understand the molecular basis for the rapid and robust memory T-cell responses, we examined gene expression and chromatin modification by histone H3 lysine 9 (H3K9) acetylation in resting and activated human naive and memory CD8(+) T cells. We found that, although overall gene expression patterns were similar, a number of genes are differentially expressed in either memory or naive cells in their resting and activated states. To further elucidate the basis for differential gene expression, we assessed the role of histone H3K9 acetylation in differential gene expression. Strikingly, higher H3K9 acetylation levels were detected in resting memory cells, prior to their activation, for those genes that were differentially expressed following activation, indicating that hyperacetylation of histone H3K9 may play a role in selective and rapid gene expression of memory CD8(+) T cells. Consistent with this model, we showed that inducing high levels of H3K9 acetylation resulted in an increased expression in naive cells of those genes that are normally expressed differentially in memory cells. Together, these findings suggest that differential gene expression mediated at least in part by histone H3K9 hyperacetylation may be responsible for the rapid and robust memory CD8(+) T-cell response.

Acetylation↗
PubMed2004

Aspergillus antigen induces robust Th2 cytokine production, inflammation, airway hyperreactivity and fibrosis in the absence of MCP-1 or CCR2.

BACKGROUND: Asthma is characterized by type 2 T-helper cell (Th2) inflammation, goblet cell hyperplasia, airway hyperreactivity, and airway fibrosis. Monocyte chemoattractant protein-1 (MCP-1 or CCL2) and its receptor, CCR2, have been shown to play important roles in the development of Th2 inflammation. CCR2-deficient mice have been found to have altered inflammatory and physiologic responses in some models of experimental allergic asthma, but the role of CCR2 in contributing to inflammation and airway hyperreactivity appears to vary considerably between models. Furthermore, MCP-1-deficient mice have not previously been studied in models of experimental allergic asthma. METHODS: To test whether MCP-1 and CCR2 are each required for the development of experimental allergic asthma, we applied an Aspergillus antigen-induced model of Th2 cytokine-driven allergic asthma associated with airway fibrosis to mice deficient in either MCP-1 or CCR2. Previous studies with live Aspergillus conidia instilled into the lung revealed that MCP-1 and CCR2 play a role in anti-fungal responses; in contrast, we used a non-viable Aspergillus antigen preparation known to induce a robust eosinophilic inflammatory response. RESULTS: We found that wild-type C57BL/6 mice developed eosinophilic airway inflammation, goblet cell hyperplasia, airway hyperreactivity, elevations in serum IgE, and airway fibrosis in response to airway challenge with Aspergillus antigen. Surprisingly, mice deficient in either MCP-1 or CCR2 had responses to Aspergillus antigen similar to those seen in wild-type mice, including production of Th2 cytokines. CONCLUSION: We conclude that robust Th2-mediated lung pathology can occur even in the complete absence of MCP-1 or CCR2.

Animals↗
PubMed2005

Scoredist: a simple and robust protein sequence distance estimator.

BACKGROUND: Distance-based methods are popular for reconstructing evolutionary trees thanks to their speed and generality. A number of methods exist for estimating distances from sequence alignments, which often involves some sort of correction for multiple substitutions. The problem is to accurately estimate the number of true substitutions given an observed alignment. So far, the most accurate protein distance estimators have looked for the optimal matrix in a series of transition probability matrices, e.g. the Dayhoff series. The evolutionary distance between two aligned sequences is here estimated as the evolutionary distance of the optimal matrix. The optimal matrix can be found either by an iterative search for the Maximum Likelihood matrix, or by integration to find the Expected Distance. As a consequence, these methods are more complex to implement and computationally heavier than correction-based methods. Another problem is that the result may vary substantially depending on the evolutionary model used for the matrices. An ideal distance estimator should produce consistent and accurate distances independent of the evolutionary model used. RESULTS: We propose a correction-based protein sequence estimator called Scoredist. It uses a logarithmic correction of observed divergence based on the alignment score according to the BLOSUM62 score matrix. We evaluated Scoredist and a number of optimal matrix methods using three evolutionary models for both training and testing Dayhoff, Jones-Taylor-Thornton, and Muller-Vingron, as well as Whelan and Goldman solely for testing. Test alignments with known distances between 0.01 and 2 substitutions per position (1-200 PAM) were simulated using ROSE. Scoredist proved as accurate as the optimal matrix methods, yet substantially more robust. When trained on one model but tested on another one, Scoredist was nearly always more accurate. The Jukes-Cantor and Kimura correction methods were also tested, but were substantially less accurate. CONCLUSION: The Scoredist distance estimator is fast to implement and run, and combines robustness with accuracy. Scoredist has been incorporated into the Belvu alignment viewer, which is available at ftp://ftp.cgb.ki.se/pub/prog/belvu/.

Algorithms↗
PubMed2005

A robust two-way semi-linear model for normalization of cDNA microarray data.

BACKGROUND: Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative expression values. METHODS: We propose a robust semiparametric method in a two-way semi-linear model (TW-SLM) for normalization of cDNA microarray data. This method does not make the usual assumptions underlying some of the existing methods. For example, it does not assume that: (i) the percentage of differentially expressed genes is small; or (ii) the numbers of up- and down-regulated genes are about the same, as required in the LOWESS normalization method. We conduct simulation studies to evaluate the proposed method and use a real data set from a specially designed microarray experiment to compare the performance of the proposed method with that of the LOWESS normalization approach. RESULTS: The simulation results show that the proposed method performs better than the LOWESS normalization method in terms of mean square errors for estimated gene effects. The results of analysis of the real data set also show that the proposed method yields more consistent results between the direct and the indirect comparisons and also can detect more differentially expressed genes than the LOWESS method. CONCLUSIONS: Our simulation studies and the real data example indicate that the proposed robust TW-SLM method works at least as well as the LOWESS method and works better when the underlying assumptions for the LOWESS method are not satisfied. Therefore, it is a powerful alternative to the existing normalization methods.

Algorithms↗
PubMed2006

Genetic algorithm learning as a robust approach to RNA editing site prediction.

BACKGROUND: RNA editing is one of several post-transcriptional modifications that may contribute to organismal complexity in the face of limited gene complement in a genome. One form, known as C --> U editing, appears to exist in a wide range of organisms, but most instances of this form of RNA editing have been discovered serendipitously. With the large amount of genomic and transcriptomic data now available, a computational analysis could provide a more rapid means of identifying novel sites of C --> U RNA editing. Previous efforts have had some success but also some limitations. We present a computational method for identifying C --> U RNA editing sites in genomic sequences that is both robust and generalizable. We evaluate its potential use on the best data set available for these purposes: C --> U editing sites in plant mitochondrial genomes. RESULTS: Our method is derived from a machine learning approach known as a genetic algorithm. REGAL (RNA Editing site prediction by Genetic Algorithm Learning) is 87% accurate when tested on three mitochondrial genomes, with an overall sensitivity of 82% and an overall specificity of 91%. REGAL's performance significantly improves on other ab initio approaches to predicting RNA editing sites in this data set. REGAL has a comparable sensitivity and higher specificity than approaches which rely on sequence homology, and it has the advantage that strong sequence conservation is not required for reliable prediction of edit sites. CONCLUSION: Our results suggest that ab initio methods can generate robust classifiers of putative edit sites, and we highlight the value of combinatorial approaches as embodied by genetic algorithms. We present REGAL as one approach with the potential to be generalized to other organisms exhibiting C --> U RNA editing.

Algorithms↗
PubMed2005

Large-scale 13C-flux analysis reveals mechanistic principles of metabolic network robustness to null mutations in yeast.

BACKGROUND: Quantification of intracellular metabolite fluxes by 13C-tracer experiments is maturing into a routine higher-throughput analysis. The question now arises as to which mutants should be analyzed. Here we identify key experiments in a systems biology approach with a genome-scale model of Saccharomyces cerevisiae metabolism, thereby reducing the workload for experimental network analyses and functional genomics. RESULTS: Genome-scale 13C flux analysis revealed that about half of the 745 biochemical reactions were active during growth on glucose, but that alternative pathways exist for only 51 gene-encoded reactions with significant flux. These flexible reactions identified in silico are key targets for experimental flux analysis, and we present the first large-scale metabolic flux data for yeast, covering half of these mutants during growth on glucose. The metabolic lesions were often counteracted by flux rerouting, but knockout of cofactor-dependent reactions, as in the adh1, ald6, cox5A, fum1, mdh1, pda1, and zwf1 mutations, caused flux responses in more distant parts of the network. By integrating computational analyses, flux data, and physiological phenotypes of all mutants in active reactions, we quantified the relative importance of 'genetic buffering' through alternative pathways and network redundancy through duplicate genes for genetic robustness of the network. CONCLUSIONS: The apparent dispensability of knockout mutants with metabolic function is explained by gene inactivity under a particular condition in about half of the cases. For the remaining 207 viable mutants of active reactions, network redundancy through duplicate genes was the major (75%) and alternative pathways the minor (25%) molecular mechanism of genetic network robustness in S. cerevisiae.

Carbon↗