Melina II: a web tool for comparisons among several predictive algorithms to find potential motifs from promoter regions

We present the second version of Melina, a web-based tool for promoter analysis. Melina II shows potential DNA motifs in promoter regions with a combination of several available programs, Consensus, MEME, Gibbs sampler, MDscan and Weeder, as well as several parameter settings. It allows running a maximum of four programs simultaneously, and comparing their results with graphical representations. In addition, users can build a weight matrix from a predicted motif and apply it to upstream sequences of several typical genomes (human, mouse, S. cerevisiae, E. coli, B. subtilis or A. thaliana) or to public motif databases (JASPAR or DBTBS) in order to find similar motifs. Melina II is a client/server system developed by using Adobe (Macromedia) Flash and is accessible over the web at http://melina.hgc.jp

Argument-based agreements in agent societies

In this paper, we present an abstract argumentation framework for the support of agreement processes in agent societies. It takes into account arguments, attacks among them, and the social context of the agents that put forward arguments. Then, we de¿ne the semantics of the framework, providing a mechanism to evaluate arguments in view of other arguments posed in the argumentation process. We also provide a translation of the framework into a neural network that computes the set of acceptable arguments and can be tuned to give more or less importance to argument attacks. Finally, the framework is illustrated with an example in a real domain of a water-rights transfer market. & 2011 Elsevier B.V. All rights reservedThis work is supported by the Spanish government Grants CONSOLIDER INGENIO 2010 CSD2007-00022, TIN2008-04446 and TIN2009-13839-C03-01 and by the GVA project PROMETEO 2008/051.Heras Barberá, SM.; Botti Navarro, VJ.; Julian Inglada, VJ. (2012). Argument-based agreements in agent societies. Neurocomputing. 75(1):156-162. doi:10.1016/j.neucom.2011.02.022S15616275

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery

<p>Abstract</p> <p>Background</p> <p>DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database.</p> <p>Results</p> <p>GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories.</p> <p>Conclusion</p> <p>GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at <url>http://cgs.pharm.kyoto-u.ac.jp/services/network</url>.</p

Sperm allocation in relation to female size in a semelparous salmonid

To maximize reproductive success, males have to adaptively tailor their sperm expenditure in relation to the quality of potential mates because they require time to replenish their sperm supply for subsequent mating opportunities. Therefore, in mating contexts where males must choose among females in a short period of time, as is the case with semelparous species (which die after one intensely competitive short duration breeding season), selection on sperm allocation can be expected to be a powerful selective agent that shapes the male reproductive success. We quantitatively investigated sperm allocation patterns in chum salmon in relation to perceived female quality by developing a novel method for determining the amount of sperm allocated per ejaculate during spawning bouts. We examined the relationship between sperm expenditure and the body size of paired females (a proxy of egg number and egg quality) in the absence of male–male competition in an experimental channel. The estimated amount of sperm released per spawning event was positively correlated with the size of paired females. However, the number of spawning events a female participated in, which reduces the number of eggs she spawns in each subsequent bout, did not affect this relationship. These results provide support for predictions arising from the sperm allocation hypothesis, male salmon do economize their sperm expenditure in accordance with paired female body size as predicted for their first spawning event, but males overestimate or are unable to assess the quality of females beyond size and provide more sperm than they should in theory when paired with a female that spawned previously. Overall, the observed sperm allocation pattern in chum salmon appears to be adapted to maximize reproductive success assuming female size is an honest indicator of quality, although temporal changes in a female\u27s quality during a reproductive season should be considered when examining sperm allocation strategies

A neural cognitive model of argumentation with application to legal inference and decision making

Formal models of argumentation have been investigated in several areas, from multi-agent systems and artificial intelligence (AI) to decision making, philosophy and law. In artificial intelligence, logic-based models have been the standard for the representation of argumentative reasoning. More recently, the standard logic-based models have been shown equivalent to standard connectionist models. This has created a new line of research where (i) neural networks can be used as a parallel computational model for argumentation and (ii) neural networks can be used to combine argumentation, quantitative reasoning and statistical learning. At the same time, non-standard logic models of argumentation started to emerge. In this paper, we propose a connectionist cognitive model of argumentation that accounts for both standard and non-standard forms of argumentation. The model is shown to be an adequate framework for dealing with standard and non-standard argumentation, including joint-attacks, argument support, ordered attacks, disjunctive attacks, meta-level attacks, self-defeating attacks, argument accrual and uncertainty. We show that the neural cognitive approach offers an adequate way of modelling all of these different aspects of argumentation. We have applied the framework to the modelling of a public prosecution charging decision as part of a real legal decision making case study containing many of the above aspects of argumentation. The results show that the model can be a useful tool in the analysis of legal decision making, including the analysis of what-if questions and the analysis of alternative conclusions. The approach opens up two new perspectives in the short-term: the use of neural networks for computing prevailing arguments efficiently through the propagation in parallel of neuronal activations, and the use of the same networks to evolve the structure of the argumentation network through learning (e.g. to learn the strength of arguments from data)

Dramatic effect of pop-up satellite tags on eel swimming

The journey of the European eel to the spawning area in the Sargasso Sea is still a mystery. Several trials have been carried out to follow migrating eels with pop-up satellite tags (PSATs), without much success. As eels are very efficient swimmers, tags likely interfere with their high swimming efficiency. Here we report a more than twofold increase in swimming cost caused by a regular small satellite tag. The impact was determined at a range of swimming speeds with and without tag in a 2-m swimming tunnel. These results help to explain why the previous use of PSATs to identify spawning sites in the Sargasso Sea was thus far unsuccessful

Using ultrasonography in evaluating the intramuscular injection techniques used for administering drug treatments to schizophrenic patients in Japan

This study was conducted with six patients with schizophrenia, four of whom received the atypical antipsychotic risperidone long-acting injectable (RLAI), and two patients receiving the typical depot injection (TDI). The purpose of this study was to determine the location (gluteus medius or maximus ; deltoid muscles) and diffusion of typical and atypical antipsychotic medications administered intramuscularly using ultrasonography. When using the standardized depth of needle insertion, in some cases, the drug was injected into the gluteus maximus instead of the gluteus medius. Similarly, in some cases the TDI was not visible in the ultrasonographic images until sixteen days after the injection. This verifies how hard the injection site becomes when microspheres of RLAI is injected as compared to other muscle areas. These results confirmed that the gluteus muscle structure was the ideal muscle for depot injection as evidenced by the injection solution being dispersed and rendered not visible immediately after intramuscular injection (IM). With the use of ultrasonography, injection sites and drug dispersions were evaluated under a direct visual guidance, suggesting that ultrasonography is a useful method for establishing evidence for determining correct insertion of IM injection, diffusion of medications, and the effective administration of IM injections