Biomedical subjects

Luciano da Fontoura Costa

Publications and source records attributed to Luciano da Fontoura Costa.

18 recordsLinked to original sources

PubMed2006

Spread of opinions and proportional voting.

Election results are determined by numerous social factors that affect the formation of opinion of the voters, including the network of interactions between them and the dynamics of opinion influence. In this work we study the result of proportional elections using an opinion dynamics model similar to simple opinion spreading over a complex network. Erdös-Rényi, Barabási-Albert, regular lattices, and randomly augmented lattices are considered as models of the underlying social networks. The model reproduces the power law behavior of a number of candidates with a given number of votes found in real elections with the correct slope, a cutoff for a larger number of votes, and a plateau for a small number of votes. It is found that the small world property of the underlying network is fundamental for the emergence of the power law regime.

Journal Article↗

PubMed2006

Learning about knowledge: a complex network approach.

An approach to modeling knowledge acquisition in terms of walks along complex networks is described. Each subset of knowledge is represented as a node, and relations between such knowledge are expressed as edges. Two types of edges are considered, corresponding to free and conditional transitions. The latter case implies that a node can only be reached after visiting previously a set of nodes (the required conditions). The process of knowledge acquisition can then be simulated by considering the number of nodes visited as a single agent moves along the network, starting from its lowest layer. It is shown that hierarchical networks--i.e., networks composed of successive interconnected layers--are related to compositions of the prerequisite relationships between the nodes. In order to avoid deadlocks--i.e., unreachable nodes--the subnetwork in each layer is assumed to be a connected component. Several configurations of such hierarchical knowledge networks are simulated and the performance of the moving agent quantified in terms of the percentage of visited nodes after each movement. The Barabási-Albert and random models are considered for the layer and interconnecting subnetworks. Although all subnetworks in each realization have the same number of nodes, several interconnectivities, defined by the average node degree of the interconnection networks, have been considered. Two visiting strategies are investigated: random choice among the existing edges and preferential choice to so far untracked edges. A series of interesting results are obtained, including the identification of a series of plateaus of knowledge stagnation in the case of the preferential movement strategy in the presence of conditional edges.

Journal Article↗

PubMed2006

A comparative analysis of highly conserved sex-determining genes between Apis mellifera and Drosophila melanogaster.

A comparison of the most conserved sex-determining genes between the fruit fly, Drosophila melanogaster, and the honey bee, Apis mellifera, was performed with bioinformatics tools developed for computational molecular biology. An initial set of protein sequences already described in the fruit fly as participants of the sex-determining cascade was retrieved from the Gene Ontology database (http://www.geneontology.org/) and aligned against a database of protein sequences predicted from the honey bee genome. The doublesex (dsx) gene is considered one of the most conserved sex-determining genes among metazoans, and a male-specific partial cDNA of putative A. mellifera dsx gene (Amdsx) was identified experimentally. The theoretical predictions were developed in the context of sequence similarity. Experimental evidence indicates that dsx is present in embryos and larvae, and that it encodes a transcription factor widely conserved in metazoans, containing a DM DNA-binding domain implicated in the regulation of the expression of genes involved in sexual phenotype formation.

Animals↗

PubMed2006

Pattern formation in a gene network model with boundary shape dependence.

A fundamental task in developmental biology is to identify the mechanisms which drive morphogenesis. Traditionally pattern formation have been modeled mainly using Turing-type mechanisms, where complex patterns arise by symmetry breaking. However, there is a growing experimental evidence that the influence of signals derived from surrounding tissues can contribute to the patterning processes. In this paper, we show that the interplay between the shape of surrounding tissues and a hierarchically organized gene regulatory network can be able to induce stable complex patterns. The rise of these patterns depends strongly on the shape of the surrounding tissues.

Animals↗

PubMed2006

Characterizing polygonality in biological structures.

Several systems involve spatial arrangements of elements such as molecules or cells, the characterization of which bears important implications to biological and physical investigations. Traditional approaches to quantify spatial order and regularity have relied on nearest neighbor distances or the number of sides of cells. The current work shows that enhanced performance can be achieved by considering angular regularity. Voronoi tessellations are obtained for each basic element and the angular regularity is then estimated from the differences between the angles defined by adjacent cells and a reference angle. In case this angle is 60 degrees, the measurement quantifies the hexagonality of the system. Other reference angles can be considered in order to quantify other types of spatial symmetries. The performance of the angular regularity is compared with other measurements including the conformity ratio (based on nearest neighbor distances) and the number of sides of the cells, indicating its improved sensitivity and discrimination power. The performance evaluation included synthetic (progressively perturbed hexagonal lattices) and real data (retinal mosaics). The good performance of the hexagonality measurements are illustrated also with respect to the problem of quantifying local spatial order in structures involving regions with different organizations as well as systems of points characterized by gradients of local order.

Journal Article↗

PubMed2005

Topographical maps as complex networks.

The neuronal networks in the mammalian cortex are characterized by the coexistence of hierarchy, modularity, short and long range interactions, spatial correlations, and topographical connections. Particularly interesting, the latter type of organization implies special demands on developing systems in order to achieve precise maps preserving spatial adjacencies, even at the expense of isometry. Although the object of intensive biological research, the elucidation of the main anatomic-functional purposes of the ubiquitous topographical connections in the mammalian brain remains an elusive issue. The present work reports on how recent results from complex network formalism can be used to quantify and model the effect of topographical connections between neuronal cells over the connectivity of the network. While the topographical mapping between two cortical modules is achieved by connecting nearest cells from each module, four kinds of network models are adopted for implementing intramodular connections, including random, preferential-attachment, short-range, and long-range networks. It is shown that, though spatially uniform and simple, topographical connections between modules can lead to major changes in the network properties in some specific cases, depending on intramodular connections schemes, fostering more effective intercommunication between the involved neuronal cells and modules. The possible implications of such effects on cortical operation are discussed.

Animals↗

PubMed2005

An integrated approach to the characterization of cell movement.

BACKGROUND: Most phenomena in developmental biology involve or depend upon cell migration. This article describes a comprehensive framework for the characterization and analysis of trajectories defined by cell movement. The following two perspectives are considered: (a) the behavior of each individual cell and (b) interactions between neighboring pairs of cells. METHODS: The measurements considered for individual trajectories include the velocity magnitude and orientation, maximum spatial dispersion, displacement effectiveness, and displacement entropies. Interactions between two trajectories are characterized by comparing the respective velocities. RESULTS: The potential of the overall framework is illustrated using data of moving cells in different biological environments. The work shows that it is possible to use the new algorithm presented here to characterize cell motility. CONCLUSIONS: The features of the algorithm were successful in determining the motility changes under different experimental conditions.

Algorithms↗

PubMed2005

A comparison of morphometric characteristics of sperm from fertile Bos taurus and Bos indicus bulls in Brazil.

The current work has as main objective the systematic investigation of sperm morphometric characteristics of fertile Bos taurus and Bos indicus bulls living in Brazil by using several traditional as well as more modern and advanced computer vision concepts and methodologies. Ten smears of B. taurus semen and ten smears of B. indicus semen have been evaluated. Sperm morphology was quantified in terms of the following morphological features: head area, perimeter, width, length, width:length ratio, ellipticity, shape factor, width of sperm basis, the three first Fourier values, symmetry and hydrodynamics. Morphometric differences have been observed between the sperm cell of B. taurus and B. indicus bulls. The sperm cells of Zebu bulls tend to be smaller and less elliptic, however without modifying hydrodynamic, side symmetry and width of sperm head base. These differences clearly indicate that the geometrical characterization of bull sperm cells should take into account morphological peculiarities that are specific to each subspecies. Another important contribution is the identification that morphological differences implied by bulls of different fertility, as characterized by other authors, were found to be less as compared with those obtained in the current study where highly fertile animals from the two subspecies were studied.

Animals↗

PubMed2005

A spectral framework for sperm shape characterization.

A novel methodology for characterization of animal sperm shape involving the use of a spectral approach to multiscale curvature estimation is proposed. By using the derivative property of the Fourier transform, allied to Gaussian smoothing, accurate estimates of the curvature along the sperm contour can be obtained in such a way that the curvature peaks corresponding to the sperm head vertices can be effectively identified. The measurements derived from such a processing, namely the width of the basal region of the head, the centralization of tail implantation, and the multiscale bending energy, provide valuable resources for fertility and phylogenetic studies.

Animals↗

PubMed2004

Bioinformatics: perspectives for the future.

I give here a very personal perspective of Bioinformatics and its future, starting by discussing the origin of the term (and area) of bioinformatics and proceeding by trying to foresee the development of related issues, including pattern recognition/data mining, the need to reintegrate biology, the potential of complex networks as a powerful and flexible framework for bioinformatics and the interplay between bio- and neuroinformatics. Human resource formation and market perspective are also addressed. Given the complexity and vastness of these issues and concepts, as well as the limited size of a scientific article and finite patience of the reader, these perspectives are surely incomplete and biased. However, it is expected that some of the questions and trends that are identified will motivate discussions during the IcoBiCoBi round table (with the same name as this article) and perhaps provide a more ample perspective among the participants of that conference and the readers of this text.

Bioethics↗

PubMed2004

L -percolations of complex networks.

Given a complex network, its L-paths correspond to sequences of L+1 distinct nodes connected through L distinct edges. The L-conditional expansion of a complex network can be obtained by connecting all its pairs of nodes which are linked through at least one L-path, and the respective conditional L-expansion of the original network is defined as the intersection between the original network and its L-expansion. Such expansions are verified to act as filters enhancing the network connectivity, consequently contributing to the identification of communities in small-world models. It is shown in this paper for L=2 and 3, in both analytical and experimental fashions, that an evolving complex network with a fixed number of nodes undergoes successive phase transitions--the so-called L-percolations, giving rise to Eulerian giant clusters. It is also shown that the critical values of such percolations are a function of the network size and that the network percolates for L=3 before L=2 .

Journal Article↗

PubMed2004

Biological sequence analysis through the one-dimensional percolation transform and its enhanced version.

MOTIVATION: The necessity to characterize the spatial uniformity (or lack of it) of symbols in biological sequences, given its implications for identification of the properties of the structures associated with the sequences. METHODS: A one-dimensional version of a recently introduced percolation-based approach is presented, which allows the accurate quantification of symbol distributions even in the presence of co-existing densities. An enhanced version of this methodology, which uses an agglomerative process to organize hierarchically the sequence into subsequences, is also proposed and illustrated. 3. RESULTS: The potential of the proposed methodology is illustrated with respect to synthetic and real data (1881 zebrafish and 1200 Xenopus proteins) and compared to two alternative multiscale methodologies, with encouraging results including the possibility to identify particularly remarkable amino acid arrangements in proteins. 4. CONTACT: luciano@if.sc.usp.br.

Algorithms↗

PubMed2004

The hierarchical backbone of complex networks.

Given any complex directed network, a set of acyclic subgraphs can be extracted that will provide valuable information about its hierarchical structure. This Letter presents how the interpretation of the network weight matrix as a transition matrix allows the hierarchical backbone to be identified and characterized in terms of the concepts of hierarchical degree, which expresses the total weights of virtual edges established along successive transitions. The potential of the proposed approach is illustrated with respect to simulated random and preferential-attachment networks as well as real data related to word associations and gene sequencing.

Biophysics↗

PubMed2004

Reinforcing the resilience of complex networks.

Given a connected network, it can be augmented by applying a growing strategy (e.g., random- or preferential-attachment rules) over the previously existing structure. Another approach for augmentation, recently introduced, involves incorporating a direct edge between any two nodes which are found to be connected through at least one self-avoiding path of length L. This work investigates the resilience of random- and preferential-attachment models augmented by using the three schemes identified above. Considering random- and preferential-attachment networks, their giant cluster are identified and reinforced, then the resilience of the resulting networks with respect to highest-degree node attack is quantified through simulations. Statistical characterization of the effects of augmentations over some of the network properties is also provided. The results, which indicate that substantial reinforcement of the resilience of complex networks can be achieved by the expansions, also confirm the superior robustness of the random expansion. An important obtained result is that the initial growth scheme was found to have little effect over the possibilities of further enhancement of the network by subsequent reinforcement schemes.

Journal Article↗

PubMed2003

Neuromorphometric characterization with shape functionals.

This work presents a procedure to extract morphological information from neuronal cells based on the variation of shape functionals as the cell geometry undergoes a dilation through a wide interval of spatial scales. The targeted shapes are alpha and beta cat retinal ganglion cells, which are characterized by different ranges of dendritic field diameter. Image functionals are expected to act as descriptors of the shape, gathering relevant geometric and topological features of the complex cell form. We present a comparative study of classification performance of additive shape descriptors, namely, Minkowski functionals, and the nonadditive multiscale fractal. We found that the proposed measures perform efficiently the task of identifying the two main classes alpha and beta based solely on scale invariant information, while also providing intraclass morphological assessment.

Animals↗

PubMed2003

A percolation approach to neural morphometry and connectivity.

This article addresses the issues of neural shape characterization and analysis from the perspective of one of the main roles played by neural shapes, namely, connectivity. This study is oriented toward the geometry at the individual cell level and involves the use of the percolation concept from statistical mechanics, which is reviewed in an accessible fashion. The characterization of the neural cell geometry with respect to connectivity is performed in terms of critical percolation probability obtained experimentally while considering several types of geometrical interactions between cells, therefore directly expressing the potential for connections defined by each situation. Two basic situations are considered: dendrite-dendrite and dendrite-axon interactions. The obtained results corroborate the potential of the critical percolation probability as a valuable resource for characterizing, classifying, and analyzing the morphology of neural cells.

Algorithms↗

PubMed2003

A systematic approach to multispecies sperm morphometric characterization.

OBJECTIVE: To investigate the morphologic variety of sperm heads between several species through a comprehensive set of measurements, some of which are presented here for the first time, and to perform cluster analysis. STUDY DESIGN: Fifty images were obtained for each species, preprocessed, normalized and characterized through a series of morphologic measures. All possible 2 x 2 combinations of measurements were assessed in terms of objective (discriminant analysis) and subjective (visual inspection) methods. RESULTS: The specific potential of each measure and 2 x 2 combinations were identified with respect to 2 main situations: separation between species and separation of alterations within a species, possibly corresponding to anomalies or subpopulations. Several of the measurements led to reasonable separation between species, and some specific measurements allowed the identification of morphologic alterations. CONCLUSION: The potential of relatively more sophisticated measurements and concepts for sperm analysis was corroborated. Although most of the measures considered were observed to allow good separation between species, some of the measurements, such as hydrodynamic coefficients, anterior-posterior and side symmetry, shape factor and first Fourier descriptor, accounted for the identification of secondary clusters within specific species, possibly indicating pathologic alterations or signaling the presence of subpopulations.

Animals↗

PubMed2002

A shape analysis framework for neuromorphometry.

This paper addresses in an integrated and systematic fashion the relatively overlooked but increasingly important issue of measuring and characterizing the geometrical properties of nerve cells and structures, an area often called neuromorphology. After discussing the main motivation for such an endeavour, a comprehensive mathematical framework for characterizing neural shapes, capable of expressing variations over time, is presented and used to underline the main issues in neuromorphology. Three particularly powerful and versatile families of neuromorphological approaches, including differential measures, symmetry axes/skeletons, and complexity, are presented and their respective potentials for applications in neuroscience are identified. Examples of applications of such measures are provided based on experimental investigations related to automated dendrogram extraction, mental retardation characterization, and axon growth analysis.

Animals↗