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PubMed2005

HalX: an open-source LIMS (Laboratory Information Management System) for small- to large-scale laboratories.

Structural genomics aims at the establishment of a universal protein-fold dictionary through systematic structure determination either by NMR or X-ray crystallography. In order to catch up with the explosive amount of protein sequence data, the structural biology laboratories are spurred to increase the speed of the structure-determination process. To achieve this goal, high-throughput robotic approaches are increasingly used in all the steps leading from cloning to data collection and even structure interpretation is becoming more and more automatic. The progress made in these areas has begun to have a significant impact on the more 'classical' structural biology laboratories, dramatically increasing the number of individual experiments. This automation creates the need for efficient data management. Here, a new piece of software, HalX, designed as an 'electronic lab book' that aims at (i) storage and (ii) easy access and use of all experimental data is presented. This should lead to much improved management and tracking of structural genomics experimental data.

Crystallography, X-Ray↗
PubMed2006

An introduction to stereochemical restraints.

At the resolution available from most macromolecular crystals, the X-ray data alone are insufficient to lead to a chemically reasonable structure, so stereochemical restraints are essential. These usually restrain bond lengths, bond angles, planes and chiral volumes. The definition of these restraints and where the values come from are described. A dictionary entry contains information about the atom types, their connectivity and all the appropriate restraints. Torsion angles are not usually restrained, but they do have optimum values. In the special case of flexible five- and six-membered rings, including pentose and hexose sugars, the ring pucker is defined by combinations of torsion angles and the pucker affects the position of substituents.

Carbon↗
PubMed1998

Transferability of multipole charge-density parameters: application to very high resolution oligopeptide and protein structures.

Crystallography at sub-atomic resolution permits the observation and measurement of the non-spherical character of the electron density (parameterized as multipoles) and of the atomic charges. This fine description of the electron density can be extended to structures of lower resolution by applying the notion of transferability of the charge and multipole parameters. A database of such parameters has been built from charge-density analysis of several peptide crystals. The aim of this study is to assess for which X-ray structures the application of transferability is physically meaningful. The charge-density multipole parameters have been transferred and the X-ray structure of a 310 helix octapeptide Ac-Aib2-L-Lys(Bz)-Aib2-L-Lys(Bz)-Aib2-NHMe refined subsequently, for which diffraction data have been collected to a resolution of 0.82 A at a cryogenic temperature of 100 K. The multipoles transfer resulted in a significant improvement of the crystallographic residual factors wR and wR free. The accumulation of electrons in the covalent bonds and oxygen lone pairs is clearly visible in the deformation electron-density maps at its expected value. The refinement of the charges for nine different atom types led to an additional improvement of the R factor and the refined charges are in good agreement with those of the AMBER molecular modelling dictionary. The use of scattering factors calculated from average results of charge-density work gives a negligible shift of the atomic coordinates in the octapeptide but induces a significant change in the temperature factors (DeltaB approximately 0.4 A2). Under the spherical atom approximation, the temperature factors are biased as they partly model the deformation electron density. The transfer of the multipoles thus improves the physical meaning of the thermal-displacement parameters. The contribution to the diffraction of the different components of the electron density has also been analyzed. This analysis indicates that the electron-density peaks are well defined in the dynamic deformation maps when the thermal motion of the atoms is moderate (B typically lower than 4 A2). In this case, a non-truncated Fourier synthesis of the deformation density requires that the diffraction data are available to a resolution better than 0.9 A.

Crystallography, X-Ray↗
PubMed1996

A novel family of compression algorithms for ECG and other semiperiodical, one-dimensional, biomedical signals.

In this paper, a novel family of compression algorithms is presented, which is designed to exploit the redundancy of one-dimensional (1-D) semiperiodical biomedical signals resulting from the cyclic nature of the underlying physical process. The basic idea is that a pool of past-seen cycles is maintained and cycles to be encoded can be stored as transformed versions of those residing in the pool. Conceptually, this approach is an extension of dictionary-based coding schemes used for text compression to signal patterns residing in an n-dimensional space. A cycle transformation method is introduced in order to render the pattern matching process practical and to enable cycle substitution. Based on the principles of the algorithmic family and this transformation method, an electrocardiogram (ECG)-oriented algorithm is implemented and thoroughly tested. The performance of this implementation is examined theoretically and deductions about the optimal algorithm settings are made. The ECG compression algorithm is superior to the average beat subtraction algorithm as proposed by Hamilton and Tompkins in cases where high compression ratios are required.

Algorithms↗
PubMed1998

Analysis-synthesis of the phonocardiogram based on the matching pursuit method.

The matching pursuit method of Mallat and Zhang is applied to the analysis and synthesis of phonocardiograms (PCG's). The method is based on a classical Gabor wavelet or time-frequency atom which is the product of a sinusoid and a Gaussian window function. It decomposes a signal into a series of time-frequency atoms by an iterative process based on selecting the largest inner product of the signal (and the subsequent residues) with atoms from a redundant dictionary. The Gaussian window controls the envelope duration and time position of each atom; and the sinusoid represents the frequency. The method was applied to two sets of PCG's: one with very low-noise level and the other with 10% noise energy. Each data base includes 11 PCG's representing the normal and the pathological conditions of the heart. The normalized root-mean-square error (NRMSE) was computed between the original and the reconstructed signals. The results show that the matching pursuit method is very suitable to the transient and complex properties of the PCG's, as it yielded excellent NRMSE's around 2.2% for the two sets of 11 PCG's tested.

Heart Murmurs↗
PubMed1999

Context-based lossless and near-lossless compression of EEG signals.

In this paper, we study compression techniques for electroencephalograph (EEG) signals. A variety of lossless compression techniques, including compress, gzip, bzip, shorten, and several predictive coding methods, are investigated and compared. The methods range from simple dictionary-based approaches to more sophisticated context modeling techniques. It is seen that compression ratios obtained by lossless compression are limited even with sophisticated context-based bias cancellation and activity-based conditional coding. Though lossy compression can yield significantly higher compression ratios while potentially preserving diagnostic accuracy, it is not usually employed due to legal concerns. Hence, we investigate a near-lossless compression technique that gives quantitative bounds on the errors introduced during compression. It is observed that such a technique gives significantly higher compression ratios (up to 3-bit/sample saving with less than 1% error). Compression results are reported for EEG's recorded under various clinical conditions.

Electroencephalography↗
PubMed2006

Low-rate and flexible image coding with redundant representations.

New breakthroughs in image coding possibly lie in signal decomposition through nonseparable basis functions that can efficiently capture edge characteristics, present in natural images. The work proposed in this paper provides an adaptive way of representing images as a sum of two-dimensional features. It presents a low bit-rate image coding method based on a matching pursuit (MP) expansion, over a dictionary built on anisotropic refinement and rotation of contour-like atoms. This method is shown to provide, at low bit rates, results comparable to the state of the art in image compression, represented here by JPEG2000 and SPIHT, with generally a better visual quality in the MP scheme. The coding artifacts are less annoying than the ringing introduced by wavelets at very low bit rate, due to the smoothing performed by the basis functions used in the MP algorithm. In addition to good compression performances at low bit rates, the new coder has the advantage of producing highly flexible streams. They can easily be decoded at any spatial resolution, different from the original image, and the bitstream can be truncated at any point to match diverse bandwidth requirements. The spatial adaptivity is shown to be more flexible and less complex than transcoding operations generally applied to state of the art codec bitstreams. Due to both its ability for capturing the most important parts of multidimensional signals, and a flexible stream structure, the image coder proposed in this paper represents an interesting solution for low to medium rate image coding in visual communication applications.

Algorithms↗
PubMed2006

Line detection in images through regularized Hough transform.

The problem of determining the location and orientation of straight lines in images is of great importance in the fields of computer vision and image processing. Traditionally the Hough transform, (a special case of the Radon transform) has been widely used to solve this problem for binary images. In this paper, we pose the problem of detecting straight lines in gray-scale images as an inverse problem. Our formulation is based on use of the inverse Radon operator, which relates the parameters determining the location and orientation of the lines in the image to the noisy input image. The advantage of this formulation is that we can then approach the problem of line detection within a regularization framework and enhance the performance of the Hough-based line detector through the incorporation of prior information in the form of regularization. We discuss the type of regularizers that are useful for this problem and derive efficient computational schemes to solve the resulting optimization problems enabling their use in large applications. Finally, we show how our new approach can be alternatively viewed as one of finding an optimal representation of the noisy image in terms of elements chosen from a dictionary of lines. This interpretation relates the problem of Hough-based line finding to the body of work on adaptive signal representation.

Algorithms↗
PubMed2006

Context-based coding of bilevel images enhanced by digital straight line analysis.

A new efficient compression scheme for bilevel images containing locally straight edges is presented. This paper is especially focused on lossless (intra) coding of binary shapes for image and video objects, but other images with similar characteristics such as line drawings, layers of digital maps, or segmentation maps are also encoded efficiently. The algorithm is not targeted at document images with text, which can be coded efficiently with dictionary-based techniques as in JBIG2. The scheme is based on a local analysis of the digital straightness of the causal part of the object boundary, which is used in the context definition for arithmetic encoding. Tested on individual images of standard TV resolution binary shapes and the binary layers of a digital map, the proposed algorithm outperforms PWC, JBIG, JBIG2, and MPEG-4 CAE. On the binary shapes, the code lengths are reduced by 21%, 27%, 28%, and 41%, respectively. On the map layers, the reductions are 31%, 34%, 32%, and 64%, respectively. The algorithm is also more efficient on the test material than the state-of-the-art generic bilevel image coder free tree.

Algorithms↗
PubMed2006

Hierarchical stochastic image grammars for classification and segmentation.

We develop a new class of hierarchical stochastic image models called spatial random trees (SRTs) which admit polynomial-complexity exact inference algorithms. Our framework of multitree dictionaries is the starting point for this construction. SRTs are stochastic hidden tree models whose leaves are associated with image data. The states at the tree nodes are random variables, and, in addition, the structure of the tree is random and is generated by a probabilistic grammar. We describe an efficient recursive algorithm for obtaining the maximum a posteriori estimate of both the tree structure and the tree states given an image. We also develop an efficient procedure for performing one iteration of the expectation-maximization algorithm and use it to estimate the model parameters from a set of training images. We address other inference problems arising in applications such as maximization of posterior marginals and hypothesis testing. Our models and algorithms are illustrated through several image classification and segmentation experiments, ranging from the segmentation of synthetic images to the classification of natural photographs and the segmentation of scanned documents. In each case, we show that our method substantially improves accuracy over a variety of existing methods.

Algorithms↗
PubMed2004

Performance of the Alex AVX-2 MIMD architecture in learning the NetTalk database.

The process of training neural networks on parallel architectures has been used to assess the performance of so many parallel machines. In this paper, we are investigating the implementation of backpropagation (BP) on the Alex AVX-2 coarse-grained MIMD machine. A host-worker parallel implementation is carried out in order to train different networks to learn the NetTalk dictionary. First, a computational model is constructed using a single processor to complete the learning process. Also, a communication model for the host-worker topology is developed in order to compute the communication overhead in the broadcasting/gathering process. Both models are then used to predict the machine performance when p processors are used and a comparison with the actual measured performance of the parallel architecture implementation is carried out. Simulation results show that both models can be used effectively to predict the machine performance for the NetTalk problem. Finally, a comparison between the AVX-2 NetTalk implementation and the performance of other parallel platforms is presented.

Artificial Intelligence↗
PubMed2005

Sparse basis selection: new results and application to adaptive prediction of video source traffic.

Real-time prediction of video source traffic is an important step in many network management tasks such as dynamic bandwidth allocation and end-to-end quality-of-service (QoS) control strategies. In this paper, an adaptive prediction model for MPEG-coded traffic is developed. A novel technology is used, first developed in the signal processing community, called sparse basis selection. It is based on selecting a small subset of inputs (basis) from among a large dictionary of possible inputs. A new sparse basis selection algorithm is developed that is based on efficiently updating the input selection adaptively. When a new measurement is received, the proposed algorithm updates the selected inputs in a recursive manner. Thus, adaptability is not only in the weight adjustment, but also in the dynamic update of the inputs. The algorithm is applied to the problem of single-step-ahead prediction of MPEG-coded video source traffic, and the developed method achieves improved results, as compared to the published results in the literature. The present analysis indicates that the adaptive feature of the developed algorithm seems to add significant overall value.

Algorithms↗
PubMed2006

Sparse representation for coarse and fine object recognition.

This paper offers a sparse, multiscale representation of objects. It captures the object appearance by selection from a very large dictionary of Gaussian differential basis functions. The learning procedure results from the matching pursuit algorithm, while the recognition is based on polynomial approximation to the bases, turning image matching into a problem of polynomial evaluation. The method is suited for coarse recognition between objects and, by adding more bases, also for fine recognition of the object pose. The advantages over the common representation using PCA include storing sampled points for recognition is not required, adding new objects to an existing data set is trivial because retraining other object models is not needed, and significantly in the important case where one has to scan an image over multiple locations in search for an object, the new representation is readily available as opposed to PCA projection at each location. The experimental result on the COIL-100 data set demonstrates high recognition accuracy with real-time performance.

Algorithms↗
PubMed2007

Robust object recognition with cortex-like mechanisms.

We introduce a new general framework for the recognition of complex visual scenes, which is motivated by biology: We describe a hierarchical system that closely follows the organization of visual cortex and builds an increasingly complex and invariant feature representation by alternating between a template matching and a maximum pooling operation. We demonstrate the strength of the approach on a range of recognition tasks: From invariant single object recognition in clutter to multiclass categorization problems and complex scene understanding tasks that rely on the recognition of both shape-based as well as texture-based objects. Given the biological constraints that the system had to satisfy, the approach performs surprisingly well: It has the capability of learning from only a few training examples and competes with state-of-the-art systems. We also discuss the existence of a universal, redundant dictionary of features that could handle the recognition of most object categories. In addition to its relevance for computer vision, the success of this approach suggests a plausibility proof for a class of feedforward models of object recognition in cortex.

Algorithms↗
PubMed2005

A fuzzy ontology and its application to news summarization.

In this paper, a fuzzy ontology and its application to news summarization are presented. The fuzzy ontology with fuzzy concepts is an extension of the domain ontology with crisp concepts. It is more suitable to describe the domain knowledge than domain ontology for solving the uncertainty reasoning problems. First, the domain ontology with various events of news is predefined by domain experts. The document preprocessing mechanism will generate the meaningful terms based on the news corpus and the Chinese news dictionary defined by the domain expert. Then, the meaningful terms will be classified according to the events of the news by the term classifier. The fuzzy inference mechanism will generate the membership degrees for each fuzzy concept of the fuzzy ontology. Every fuzzy concept has a set of membership degrees associated with various events of the domain ontology. In addition, a news agent based on the fuzzy ontology is also developed for news summarization. The news agent contains five modules, including a retrieval agent, a document preprocessing mechanism, a sentence path extractor, a sentence generator, and a sentence filter to perform news summarization. Furthermore, we construct an experimental website to test the proposed approach. The experimental results show that the news agent based on the fuzzy ontology can effectively operate for news summarization.

Abstracting and Indexing↗
PubMed2003

Beta edge strands in protein structure prediction and aggregation.

It is well established that recognition between exposed edges of beta-sheets is an important mode of protein-protein interaction and can have pathological consequences; for instance, it has been linked to the aggregation of proteins into a fibrillar structure, which is associated with a number of predominantly neurodegenerative disorders. A number of protective mechanisms have evolved in the edge strands of beta-sheets, preventing the aggregation and insolubility of most natural beta-sheet proteins. Such mechanisms are unfavorable in the interior of a beta-sheet. The problem of distinguishing edge strands from central strands based on sequence information alone is important in predicting residues and mutations likely to be involved in aggregation, and is also a first step in predicting folding topology. Here we report support vector machine (SVM) and decision tree methods developed to classify edge strands from central strands in a representative set of protein domains. Interestingly, rules generated by the decision tree method are in close agreement with our knowledge of protein structure and are potentially useful in a number of different biological applications. When trained on strands from proteins of known structure, using structure-based (Dictionary of Secondary Structure in Proteins) strand assignments, both methods achieved mean cross-validated, prediction accuracies of approximately 78%. These accuracies were reduced when strand assignments from secondary structure prediction were used. Further investigation of this effect revealed that it could be explained by a significant reduction in the accuracy of standard secondary structure prediction methods for edge strands, in comparison with central strands.

Algorithms↗
PubMed2001

Lexical studies of indigenous personality factors: premises, products, and prospects.

The rationale for lexical studies rests on the assumption that the most meaningful personality attributes tend to become encoded in language as single-word descriptors. We articulate some key premises of the lexical approach and then review a number of studies that have been conducted examining the factor structure of personality descriptors extracted from dictionaries. We compare lexical studies in English and 12 other languages, with attention to delineating consistencies between the structures found in diverse languages. Our review suggests that the Anglo-Germanic Big Five is reproduced better in some languages than in others. We propose some organizing rules for lexical factor structures that may be more generalizable than the contemporary Big-Five model. And, we propose several candidate structural models that should be compared with the Big Five in future studies, including structures with one, two, and three very broad factors, an alternative five-factor structure identified in Italian and Hungarian studies, and a seven-factor structure represented in Hebrew and Philippine studies. We recommend that in future studies more attention be paid to middle-level personality constructs and to examining the effects of methodological variations on the resulting factor structures.

Culture↗
PubMed1993

Cell death by apoptosis in epidermal biology.

Homeostasis in continually renewing tissues is maintained by a tightly regulated balance between cell proliferation, cell differentiation, and cell death. Until recently, proliferation was thought to be the primary point of control in the regulation of normal tissue kinetic homeostasis and as such has been the major focus of both understanding the etiology of disease and developing therapeutic strategies. Now, physiologic cell death, known as apoptosis (ă-pŏp-to' sĭs, ă-po-to' sĭs [Thomas CL (ed.): Taber's Cyclopedic Medical Dictionary. F.A. Davis, Co., Philadelphia, 1989)] has gained scientific recognition as an active regulatory mechanism, complementary, but functionally opposite, to proliferation with important roles in shaping and maintaining tissue size and prevention of disease. In this review we will describe the concept of apoptosis and discuss possible molecular mechanisms of its regulation that may have implications for skin biology.

Apoptosis↗