Morphometry based on effective and accurate correspondences of localized patterns (MEACOLP)

Local features in volumetric images have been used to identify correspondences of localized anatomical structures for brain morphometry. However, the correspondences are often sparse thus ineffective in reflecting the underlying structures, making it unreliable to evaluate specific morphological differences. This paper presents a morphometry method (MEACOLP) based on correspondences with improved effectiveness and accuracy. A novel two-level scale-invariant feature transform is used to enhance the detection repeatability of local features and to recall the correspondences that might be missed in previous studies. Template patterns whose correspondences could be commonly identified in each group are constructed to serve as the basis for morphometric analysis. A matching algorithm is developed to reduce the identification errors by comparing neighboring local features and rejecting unreliable matches. The two-sample t-test is finally adopted to analyze specific properties of the template patterns. Experiments are performed on the public OASIS database to clinically analyze brain images of Alzheimer's disease (AD) and normal controls (NC). MEACOLP automatically identifies known morphological differences between AD and NC brains, and characterizes the differences well as the scaling and translation of underlying structures. Most of the significant differences are identified in only a single hemisphere, indicating that AD-related structures are characterized by strong anatomical asymmetry. In addition, classification trials to differentiate AD subjects from NC confirm that the morphological differences are reliably related to the groups of interest.     

STRALCP--structure alignment-based clustering of proteins

Protein structural annotation and classification is an important and challenging problem in bioinformatics. Research towards analysis of sequence-structure correspondences is critical for better understanding of a protein's structure, function, and its interaction with other molecules. Clustering of protein domains based on their structural similarities provides valuable information for protein classification schemes. In this article, we attempt to determine whether structure information alone is sufficient to adequately classify protein structures. We present an algorithm that identifies regions of structural similarity within a given set of protein structures, and uses those regions for clustering. In our approach, called STRALCP (STRucture ALignment-based Clustering of Proteins), we generate detailed information about global and local similarities between pairs of protein structures, identify fragments (spans) that are structurally conserved among proteins, and use these spans to group the structures accordingly. We also provide a web server at http://as2ts.llnl.gov/AS2TS/STRALCP/ for selecting protein structures, calculating structurally conserved regions and performing automated clustering.     

Novel algorithm for coexpression detection in time-varying microarray data sets

When analyzing the results of microarray experiments, biologists generally use unsupervised categorization tools. However, such tools regard each time point as an independent dimension and utilize the Euclidean distance to compute the similarities between expressions. Furthermore, some of these methods require the number of clusters to be determined in advance, which is clearly impossible in the case of a new dataset. Therefore, this study proposes a novel scheme, designated as the Variation-based Coexpression Detection (VCD) algorithm, to analyze the trends of expressions based on their variation over time. The proposed algorithm has two advantages. First, it is unnecessary to determine the number of clusters in advance since the algorithm automatically detects those genes whose profiles are grouped together and creates patterns for these groups. Second, the algorithm features a new measurement criterion for calculating the degree of change of the expressions between adjacent time points and evaluating their trend similarities. Three real-world microarray datasets are employed to evaluate the performance of the proposed algorithm.     

Evolving fuzzy rules to model gene expression

This paper develops an algorithm that extracts explanatory rules from microarray data, which we treat as time series, using genetic programming (GP) and fuzzy logic. Reverse polish notation is used (RPN) to describe the rules and to facilitate the GP approach. The algorithm also allows for the insertion of prior knowledge, making it possible to find sets of rules that include the relationships between genes already known. The algorithm proposed is applied to problems arising in the construction of gene regulatory networks, using two different sets of real data from biological experiments on the Arabidopsis thaliana cold response and the rat central nervous system, respectively. The results show that the proposed technique can fit data to a pre-defined precision even in situations where the data set has thousands of features but only a limited number of points in time are available, a situation in which traditional statistical alternatives encounter difficulties, due to the scarcity of time points.     

An algorithm for associating the features of two images.

In this paper we describe an algorithm that operates on the distances between features in the two related images and delivers a set of correspondences between them. The algorithm maximizes the inner product of two matrices, one of which is the desired 'pairing matrix' and the other a 'proximity matrix' with elements exp (-rij2/2 sigma 2), where rij is the distance between two features, one in each image, and sigma is an adjustable scale parameter. The output of the algorithm may be compared with the movements that people perceive when viewing two images in quick succession, and it is found that an increase in sigma affects the computed correspondences in much the same way as an increase in interstimulus interval alters the perceived displacements. Provided that sigma is not too small the algorithm will recover the feature mappings that result from image translation, expansion or shear deformation--transformations of common occurrence in image sequences--even when the displacements of individual features depart slightly from the general trend.     

Pose estimation in automated visual inspection using genetic algorithm

In this paper, we propose a genetic algorithm based approach to determine the pose of an object in Automated Visual Inspection having three degrees of freedom. We have investigated the effect of noise at 20 dB SNR and also mismatch resulting from incorrect correspondences between the object space points and the image space points, on the estimation of pose parameters. The maximum error in translation parameters is less than 0.45 cm and rotational error is less than 0.2 degree at 20 dB SNR. The error in parameter estimation is insignificant upto 7 pairs of mismatched points out of 24 points in object space and the results skyrockets when 8 or more pairs of points are mismatched. We have compared our result with that obtained by least square technique and it shows that GA based method outperform the gradient based technique when the number of vertices of the object to be inspected is small. These results have clearly established the robustness of GA in estimating the pose of an object with small number of vertices in automated visual inspection.     

The Contraction-Expansion Algorithm and Its Use in Fitting Nonlinear Equation

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MORPHOMETRIC CORRELATION PATTERNS OF ADULT BIRDS (FRINGILLIDAE: PASSERIFORMES AND COLUMBIFORMES) MIRROR THE EXPRESSION OF DEVELOPMENTAL CONTROL GENES

Stimulated by the rapid progress in developmental genetics, recent approaches to evolutionary theory focus on the interface function of developmental processes in the study of genotype-phenotype mapping. From this viewpoint, the main result of the present analysis is that the expression patterns of developmental control genes are reflected in the infraspecific correlation patterns of phenotypic characters in the adult stage. The study is based on 42 logarithmically scaled skeletal measurements of two avian clades, finches (43 species, n = 313) and pigeons (27 species, n = 219). First, for each clade an “observed correlation matrix” was calculated by computing a bias-reduced pooled-species correlation matrix based on the clade-specific pooled within-species variance-covariance matrix between measurements. Second, the expression domains of diverse developmental control genes, that is, Hox, Msx, Pax, Mhox, Shh, Bmp, and Gdf, in characters were represented by “theoretical matrices.” Finally, the observed and the theoretical matrices were compared by Mantel's test to test hypotheses about pattern similarities between phenotypic correlations and the expression of developmental control genes. Seventeen percent of the single matrix comparisons revealed significant (P ≤ 0.05) pattern correspondences in finches, whereas 63% were significant in pigeons. The multiple comparisons revealed correspondences at the highest significance level (P ≤ 0.001) in both clades and disclosed that 15% of the observed matrix patterns are explained in finches versus 22% in pigeons. Presumably, as finches have less pronounced correspondences between gene expression and phenotypic correlation, they are more derived than pigeons. Out of the significant single matrix comparisons, four correspondences are common to both clades: one of them is connected with the Gdf gene expression concerning limb length relations and also harmonizes with the dominant pattern within the infraspecific correlation matrices. The general implication is that the significant correspondences detected here between observed and theoretical matrices are based on a correspondence between phenotypic and genetic modules. Because the phenotypic modules are potential candidates for a direct impact of selection, the important role of genotype-phenotype mapping in molding the body plan becomes apparent.     

Genomic multiple sequence alignments: refinement using a genetic algorithm

Background  

Genomic sequence data cannot be fully appreciated in isolation. Comparative genomics – the practice of comparing genomic sequences from different species – plays an increasingly important role in understanding the genotypic differences between species that result in phenotypic differences as well as in revealing patterns of evolutionary relationships. One of the major challenges in comparative genomics is producing a high-quality alignment between two or more related genomic sequences. In recent years, a number of tools have been developed for aligning large genomic sequences. Most utilize heuristic strategies to identify a series of strong sequence similarities, which are then used as anchors to align the regions between the anchor points. The resulting alignment is globally correct, but in many cases is suboptimal locally. We describe a new program, GenAlignRefine, which improves the overall quality of global multiple alignments by using a genetic algorithm to improve local regions of alignment. Regions of low quality are identified, realigned using the program T-Coffee, and then refined using a genetic algorithm. Because a better COFFEE (Consistency based Objective Function For alignmEnt Evaluation) score generally reflects greater alignment quality, the algorithm searches for an alignment that yields a better COFFEE score. To improve the intrinsic slowness of the genetic algorithm, GenAlignRefine was implemented as a parallel, cluster-based program.     

Interspecies activity correlations reveal functional correspondence between monkey and human brain areas

Evolution-driven functional changes in the primate brain are typically assessed by aligning monkey and human activation maps using cortical surface expansion models. These models use putative homologous areas as registration landmarks, assuming they are functionally correspondent. For cases in which functional changes have occurred in an area, this assumption prohibits to reveal whether other areas may have assumed lost functions. Here we describe a method to examine functional correspondences across species. Without making spatial assumptions, we assessed similarities in sensory-driven functional magnetic resonance imaging responses between monkey (Macaca mulatta) and human brain areas by temporal correlation. Using natural vision data, we revealed regions for which functional processing has shifted to topologically divergent locations during evolution. We conclude that substantial evolution-driven functional reorganizations have occurred, not always consistent with cortical expansion processes. This framework for evaluating changes in functional architecture is crucial to building more accurate evolutionary models.     

Branching,blending, and the evolution of cultural similarities and differences among human populations

It has been claimed that blending processes such as trade and exchange have always been more important in the evolution of cultural similarities and differences among human populations than the branching process of population fissioning. In this paper, we report the results of a novel comparative study designed to shed light on this claim. We fitted the bifurcating tree model that biologists use to represent the relationships of species to 21 biological data sets that have been used to reconstruct the relationships of species and/or higher level taxa and to 21 cultural data sets. We then compared the average fit between the biological data sets and the model with the average fit between the cultural data sets and the model. Given that the biological data sets can be confidently assumed to have been structured by speciation, which is a branching process, our assumption was that, if cultural evolution is dominated by blending processes, the fit between the bifurcating tree model and the cultural data sets should be significantly worse than the fit between the bifurcating tree model and the biological data sets. Conversely, if cultural evolution is dominated by branching processes, the fit between the bifurcating tree model and the cultural data sets should be no worse than the fit between the bifurcating tree model and the biological data sets. We found that the average fit between the cultural data sets and the bifurcating tree model was not significantly different from the fit between the biological data sets and the bifurcating tree model. This indicates that the cultural data sets are not less tree-like than are the biological data sets. As such, our analysis does not support the suggestion that blending processes have always been more important than branching processes in cultural evolution. We conclude from this that, rather than deciding how cultural evolution has proceeded a priori, researchers need to ascertain which model or combination of models is relevant in a particular case and why.     

Homology as a parsimony problem: a dynamic homology approach for morphological data

The primary data used to reconstruct phylogenies comes organized in the conceptual grid of homology correspondences, and the construction of this theory‐rich grid depends in part on knowledge of relationships. This situation is not satisfactory as a conceptual system, because the evidence is not clearly delimited from the results. I explore the testing of alternative hypotheses of morphological correspondences in a quantitative cladistic context. The varying homology assessments implied by classical criteria of homology (topological equivalence, or position and connections; composition of structures, or commonality in details of construction) can be expressed as regular characters in a cladistic analysis. Doing so provides adequate transformation costs for changes in schemas of correspondences. Correspondences imply evolutionary transformations, and multiple schemas of correspondences can be compared according to the evolutionary transformations that they imply. The method is used to test the correspondences in sclerites of the male copulatory organs of spiders of the subfamily Amaurobioidinae (Arachnida, Araneae, Anyphaenidae). The correspondences of three sclerites are tested, in a data set of 93 species having one, two or three sclerites, using a simultaneous analysis of all the morphological characters. Most parsimonious trees are identified together with the correspondences they imply. Once the correspondences are integrated in the phylogenetic analysis, it is easy to evaluate the robustness of trees or decay in optimality after changes in anatomical interpretations. A Bremer support for anatomical interpretations is proposed, calculated as the increase in tree length when the specific interpretation is not used. © The Willi Hennig Society 2007.     

Mapping cardiac surface mechanics with structured light imaging

Cardiovascular disease often manifests as a combination of pathological electrical and structural heart remodeling. The relationship between mechanics and electrophysiology is crucial to our understanding of mechanisms of cardiac arrhythmias and the treatment of cardiac disease. While several technologies exist for describing whole heart electrophysiology, studies of cardiac mechanics are often limited to rhythmic patterns or small sections of tissue. Here, we present a comprehensive system based on ultrafast three-dimensional (3-D) structured light imaging to map surface dynamics of whole heart cardiac motion. Additionally, we introduce a novel nonrigid motion-tracking algorithm based on an isometry-maximizing optimization framework that forms correspondences between consecutive 3-D frames without the use of any fiducial markers. By combining our 3-D imaging system with nonrigid surface registration, we are able to measure cardiac surface mechanics at unprecedented spatial and temporal resolution. In conclusion, we demonstrate accurate cardiac deformation at over 200,000 surface points of a rabbit heart recorded at 200 frames/s and validate our results on highly contrasting heart motions during normal sinus rhythm, ventricular pacing, and ventricular fibrillation.     

The probabilities of similarities in DNA sequence comparisons

We discuss the statistical significance of local similarities found between DNA sequences, and illustrate the procedure with reference to the Queen and Korn algorithm. If the longest similarity found for two sequences has length L, this length is said to be significant at the 5% level if there is a probability of no more than 0.05 of finding a length of L or greater between a pair of sequences consisting of randomly chosen bases with the same overall base frequencies. The distribution of longest lengths is related to that of lengths from any particular pair of starting positions on the two sequences. For our implementation of the Queen and Korn algorithm, this latter distribution is constructed by combining the five different blocks of bases that may be added to extend a similarity. A table is given to assess the significance of longest similarities in sequences of length up to 1000 bases. Quite long similarities are expected to occur by chance alone. The critical values we calculate for assessing significance are preferable to expected numbers of similarities used by some commercial computer packages.     

Differences among Yanomama Indian villages: Do the patterns of allele frequencies,anthropometrics and map locations correspond?

In order to determine the degree of correspondence between sets of multivariate observations based on different kinds of traits, two new methods, derived from fundamentally different notions of “correspondence,” are adopted here and compared. Using networks or trees to represent contemporary relationships, the first method tests the similarity of the cluster or hierarchic structures implicit in two sets of data. The second approach tests the departure from perfect geometric congruence or superimposability. Computer simulation was used to generate the distributions needed for significance tests under the null hypothesis. By the first technique, we find significant correspondence among the cluster structures for geographic, allele frequency, and anthropometric data on 19 Yanomama Indian villages. The results are similar and more precise for a subset consisting of seven villages. Some of these results differ from the conclusions which would be reached with the conventional correlations based upon entries in distance tables. The direct test of congruence, used only for the data on the subset of seven villages, gives results which differ substantially from those based on cluster-structure. There are, however, similarities between the measure of congruence and the simple correlations based on entries in the distance tables. The significant correspondences observed call for some explanation. Cultural and demographic features determine the particular non-random allocation of individuals to village fragments when a village splits. These social phenomena are invoked in tentative explanation of the agreement among historical, biological, and geographic relationships of villages.     

Correspondences in visual imaging and spatial orientation in dreaming and film viewing.

New directions in film and media theory have begun to focus on precognitive, embodied aspects of film viewing. Drawing on these recent theoretical approaches, this article examines correspondences between the brain–mind state of the dreamer and the film viewer and formal similarities between the cinematic image and dream images. First, the study asks whether cinema's evolution toward the production of images that are more easily processed by the brain has also made film images easily accessible during dream-sleep. Then it shows how the cinematic image and the visual imaging of dreams depend on a similar construction of navigable space. The analysis suggests that the bodily systems for simulating movement and establishing spatial orientation function in a similar manner during dreaming and film viewing. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Homologies in phylogenetic analyses—concept and tests

Analyzing morphological characters in a phylogenetic context comprises two steps, character analysis and cladistic analysis, which are equivalent to two independent tests for hypotheses on homology. The concept of homology concerns comparable parts of the same or different organisms if their correspondences are the consequence of the same genetic or epigenetic information, and consequently of the same origin. The concept of homology is more inclusive than the character concept. Characters are seen as parts of transformation series. In the first step of morphological character analyses correspondences and non-correspondences between two characters are analyzed. A range of different examination methods and accurate study contribute to the severity of test. The hypothesis that two characters are homologous is corroborated if the correspondences outweigh the non-correspondences because the non-correspondences contradict the homology hypothesis whereas the correspondences contradict the analogy hypothesis. Complex characters possess a higher empirical content than less complex characters because they are more severely testable. The cladistic analysis tests characters against other characters which have all passed the first test. Characters which are congruent with the most parsimonious topology are further corroborated; incongruent characters are not seen as ‘falsified’ but as not further corroborated and subject to re-analysis. To test both homologies and topologies repeatedly is consistent with Popperian testability, and it is in such cycles of research that hypotheses will be critically re-evaluated.     

Automated site-directed drug design: the formation of molecular templates in primary structure generation

In this paper the spacer skeleton concept is used to produce molecular graphs of putative ligands for binding sites. The skeletons are transformed into molecular templates within the constraints of the accessible surface of the ligand-binding site. A distance-matrix method is used to compare ligand points with vertices of the spacer skeleton through a permutation of all possible correspondences. A tolerance parameter is used to screen for poor matches. As a result, a small number of matched vertices and ligand points are produced. These are fitted into the site by a constrained optimization routine using an analytical function. Ligand points fall within the site and are optimally positioned adjacent to the corresponding site points; other vertices of the spacer skeleton lying beneath the accessible surface of the site are clipped off. A molecular template is thereby formed with its vertices linked to the ligand points. The final step is to verify that the bonding integrity of the skeleton remains. The computational methods outlined in this paper have been tested at two binding sites: the pteridine binding site in dihydrofolate reductase and the amidinophenylpyruvate site of trypsin. Molecular graphs for both sites were generated automatically; they showed strong similarity to those of the natural ligands.