Neuropeptide-like protein diversity in phylum Nematoda

This study reports the identification of nematode neuropeptide-like protein (nlp) sequelogs from the GenBank expressed sequence tag (EST) database, using BLAST (Basic Local Alignment Search Tool) search methodology. Search strings derived from peptides encoded by the 45 known Caenorhabatitis elegans nlp genes were used to identify more than 1000 ESTs encoding a total of 26 multi-species nlp sequelogs. The remaining 18 nlps (nlp-4, -16, -24 through -36, -39, -41 and -45) were identified only in C elegans, while the sole EST representative of nlp-23 was from Caenorhabditis remanei. Several ESTs encoding putative antibacterial peptides similar to those encoded by the C elegans genes nlp-24-33 were observed in several parasite species. A novel gene (nlp-46) was identified, encoding a single, amidated dodecapeptide (NIA[I/T]GR[G/A]DG[F/L]RPG) in eight species. Secretory signal peptides were identified in at least one species representing each nlp sequelog, confirming that all 46 nematode nlp genes encode secretory peptides. A random sub-set of C elegans NLPs was tested physiologically in Ascaris suum ovijector and body wall muscle bioassays. None of the peptides tested were able to modulate ovijector activity, while only three displayed measurable myoactivity on somatic body wall muscle. AFAAGWNRamide (from nlp-23) and AVNPFLDSIamide (nlp-3) both produced a relaxation of body wall muscle, while AIPFNGGMYamide (nlp-10) induced a transient contraction. Numerical analyses of nip-encoding ESTs demonstrate that nlp-3, -13, -14, -15 and -18 are amongst the most highly represented transcripts in the dataset. Using available bioinformatics resources, this study delineates the nlp complement of phylum Nematoda, providing a rich source of neuropeptide ligands for deorphanisation of nematode neuropeptide receptors. (C) 2008 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Exploratory analysis of spatiotemporal patterns of cellular automata by clustering compressibility

In this paper we study the classification of spatiotemporal pattern of one-dimensional cellular automata (CA) whereas the classification comprises CA rules including their initial conditions. We propose an exploratory analysis method based on the normalized compression distance (NCD) of spatiotemporal patterns which is used as dissimilarity measure for a hierarchical clustering. Our approach is different with respect to the following points. First, the classification of spatiotemporal pattern is comparative because the NCD evaluates explicitly the difference of compressibility among two objects, e.g., strings corresponding to spatiotemporal patterns. This is in contrast to all other measures applied so far in a similar context because they are essentially univariate. Second, Kolmogorov complexity, which underlies the NCD, was used in the classification of CA with respect to their spatiotemporal pattern. Third, our method is semiautomatic allowing us to investigate hundreds or thousands of CA rules or initial conditions simultaneously to gain insights into their organizational structure. Our numerical results are not only plausible confirming previous classification attempts but also shed light on the intricate influence of random initial conditions on the classification results.

Genetic Algorithm Search for Predictive Patterns in Multidimensional Time Series

Based on an algorithm for pattern matching in character strings, we implement a pattern matching machine that searches for occurrences of patterns in multidimensional time series. Before the search process takes place, time series are encoded in user-designed alphabets. The patterns, on the other hand, are formulated as regular expressions that are composed of letters from these alphabets and operators. Furthermore, we develop a genetic algorithm to breed patterns that maximize a user-defined fitness function. In an application to financial data, we show that patterns bred to predict high exchange rates volatility in training samples retain statistically significant predictive power in validation samples.

A similarity measure for graphs with low computational complexity

We present and analyze an algorithm to measure the structural similarity of generalized trees, a new graph class which includes rooted trees. For this, we represent structural properties of graphs as strings and define the similarity of two Graphs as optimal alignments of the corresponding property stings. We prove that the obtained graph similarity measures are so called Backward similarity measures. From this we find that the time complexity of our algorithm is polynomial and, hence, significantly better than the time complexity of classical graph similarity methods based on isomorphic relations. (c) 2006 Elsevier Inc. All rights reserved.

Observational tests of interstellar methanol formation

Context. It has been established that the classical gas-phase production of interstellar methanol (CH3OH) cannot explain observed abundances. Instead it is now generally thought that the main formation path has to be by successive hydrogenation of solid CO on interstellar grain surfaces. Aims. While theoretical models and laboratory experiments show that methanol is efficiently formed from CO on cold grains, our aim is to test this scenario by astronomical observations of gas associated with young stellar objects (YSOs). Methods. We have observed the rotational transition quartets J = 2K – 1K of 12CH3OH and 13CH3OH at 96.7 and 94.4 GHz, respectively, towards a sample of massive YSOs in different stages of evolution. In addition, the J = 1-0 transitions of 12C18O and 13C18O were observed towards some of these sources. We use the 12C/13C ratio to discriminate between gas-phase and grain surface origin: If methanol is formed from CO on grains, the ratios should be similar in CH3OH and CO. If not, the ratio should be higher in CH3OH due to 13C fractionation in cold CO gas. We also estimate the abundance ratios between the nuclear spin types of methanol (E and A). If methanol is formed on grains, this ratio is likely to have been thermalized at the low physical temperature of the grain, and therefore show a relative over-abundance of A-methanol. Results. We show that the 12C/13C isotopic ratio is very similar in gas-phase CH3OH and C18O, on the spatial scale of about 40 arcsec, towards four YSOs. For two of our sources we find an overabundance of A-methanol as compared to E-methanol, corresponding to nuclear spin temperatures of 10 and 16 K. For the remaining five sources, the methanol E/A ratio is less than unity. Conclusions. While the 12C/13C ratio test is consistent with methanol formation from hydrogenation of CO on grain surfaces, the result of the E/A ratio test is inconclusive.

A structural analysis of G-quadruplex/ligand interactions

This focused review article discusses in detail, all available high-resolution small molecule ligand/G-quadruplex structural data derived from crystallographic and NMR based techniques, in an attempt to understand key factors in ligand binding and to highlight the biological importance of these complexes. In contrast to duplex DNA, G-quadruplexes are four-stranded nucleic acid structures folded from guanine rich repeat sequences stabilized by the stacking of guanine G-quartets and extensive Watson-Crick/Hoogsteen hydrogen bonding. Thermally stable, these topologies can play a role in telomere regulation and gene expression. The core structures of G-quadruplexes form stable scaffolds while the loops have been shown, by the addition of small molecule ligands, to be sufficiently adaptable to generate new and extended binding platforms for ligands to associate, either by extending G-quartet surfaces or by forming additional planar dinucleotide pairings. Many of these structurally characterised loop rearrangements were totally unexpected opening up new opportunities for the design of selective ligands. However these rearrangements do significantly complicate attempts to rationally design ligands against well defined but unbound topologies, as seen for the series of napthalene diimides complexes. Drawing together previous findings and with the introduction of two new crystallographic quadruplex/ligand structures we aim to expand the understanding of possible structural adaptations available to quadruplexes in the presence of ligands, thereby aiding in the design of new selective entities. (C) 2011 Elsevier Masson SAS. All rights reserved.

Quantum superpositions of crystalline structures

A procedure is discussed for creating coherent superpositions of motional states of ion strings. The motional states are across the structural transition linear-zigzag, and their coherent superposition is achieved by means of spin-dependent forces, such that a coherent superposition of the electronic states of one ion evolves into an entangled state between the chain's internal and external degrees of freedom. It is shown that the creation of such an entangled state can be revealed by performing Ramsey interferometry with one ion of the chain.

SVM Training Phase Reduction Using Dataset Feature Filtering for Malware Detection

N-gram analysis is an approach that investigates the structure of a program using bytes, characters, or text strings. A key issue with N-gram analysis is feature selection amidst the explosion of features that occurs when N is increased. The experiments within this paper represent programs as operational code (opcode) density histograms gained through dynamic analysis. A support vector machine is used to create a reference model, which is used to evaluate two methods of feature reduction, which are 'area of intersect' and 'subspace analysis using eigenvectors.' The findings show that the relationships between features are complex and simple statistics filtering approaches do not provide a viable approach. However, eigenvector subspace analysis produces a suitable filter.