AGMIAL: implementing an annotation strategy for prokaryote genomes as a distributed system

We have implemented a genome annotation system for prokaryotes called AGMIAL. Our approach embodies a number of key principles. First, expert manual annotators are seen as a critical component of the overall system; user interfaces were cyclically refined to satisfy their needs. Second, the overall process should be orchestrated in terms of a global annotation strategy; this facilitates coordination between a team of annotators and automatic data analysis. Third, the annotation strategy should allow progressive and incremental annotation from a time when only a few draft contigs are available, to when a final finished assembly is produced. The overall architecture employed is modular and extensible, being based on the W3 standard Web services framework. Specialized modules interact with two independent core modules that are used to annotate, respectively, genomic and protein sequences. AGMIAL is currently being used by several INRA laboratories to analyze genomes of bacteria relevant to the food-processing industry, and is distributed under an open source license.     

Convergence in a distributed nervous system: parallel processing and self-organization

The present findings show that the motor system of the carnivorous sea slug Pleurobranchaea californica consists of parallel, distributed, and interconnected neuronal channels by which motor activity may emerge from the dynamics of the system rather than from "switchboard" circuitry. The findings are shown primarily through the properties of the buccal-cerebral neurons (BCNs) that extensively converge and diverge monosynaptically and polysynaptically onto brain motoneurons, providing them with drive and patterned activity. The motoneurons, some of which are electrically coupled, feed back onto the BCNs. The BCNs are functionally heterogeneous both as a group and individually. Many are multifunctional in that they take part in the generation of different behaviors, and some also appear to change their timing with respect to the phase of the pattern generator in the different motor patterns. In the buccal ganglion, the BCNs affect the characteristics of the pattern generator and may be part of the pattern generator itself. By sending axons to buccal roots and to the brain, some BCNs may act as motoneurons and also integrate the activity of brain motoneurons. Because of the effects produced by the extensive interconnections among such functionally heterogeneous and nonlinear elements, and because the "history" of activity in the system can bias subsequent activity, there is ambiguity in assessing the response properties of neurons by examining them individually or in pairs. Such an assessment requires, first, an understanding of the context of activity in which a neuron becomes coactive, and, second, because of inherent variability in the system, it is necessary to consider the temporal, nonlinear computations of the system as a whole. We discuss the findings with regard to the attractor theory that has been used to study complex mammalian systems but that does not rely on modeling of any neuronal activity. The Pleurobranchaea nervous system may provide the means for studying individual neurons within such analyses of global activity.     

Mechanism of case processing in the brain: an FMRI study

In sentence comprehension research, the case system, which is one of the subsystems of the language processing system, has been assumed to play a crucial role in signifying relationships in sentences between noun phrases (NPs) and other elements, such as verbs, prepositions, nouns, and tense. However, so far, less attention has been paid to the question of how cases are processed in our brain. To this end, the current study used fMRI and scanned the brain activity of 15 native English speakers during an English-case processing task. The results showed that, while the processing of all cases activates the left inferior frontal gyrus and posterior part of the middle temporal gyrus, genitive case processing activates these two regions more than nominative and accusative case processing. Since the effect of the difference in behavioral performance among these three cases is excluded from brain activation data, the observed different brain activations would be due to the different processing patterns among the cases, indicating that cases are processed differently in our brains. The different brain activations between genitive case processing and nominative/accusative case processing may be due to the difference in structural complexity between them.     

The neural mechanisms of gustation: a distributed processing code

Whenever food is placed in the mouth, taste receptors are stimulated. Simultaneously, different types of sensory fibre that monitor several food attributes such as texture, temperature and odour are activated. Here, we evaluate taste and oral somatosensory peripheral transduction mechanisms as well as the multi-sensory integrative functions of the central pathways that support the complex sensations that we usually associate with gustation. On the basis of recent experimental data, we argue that these brain circuits make use of distributed ensemble codes that represent the sensory and post-ingestive properties of tastants.     

The fractal dimension of EEG as a physical measure of conscious human brain activities

In our previous paper we have given a neuroglia modulated neuronal network model which may display chaotic behaviours under certain parametric values. This work is an attempt to correlate the functions of conscious human brains with the chaotic states shown by the EEG patterns under different physiological conditions. Some of the difficulties and precautions of this kind of work are discussed.     

How to build an information gathering and processing system: lessons from naturally and artificially intelligent systems

Imagine a situation in which you had to design a physical agent that could collect information from its environment, then store and process that information to help it respond appropriately to novel situations. What kinds of information should it attend to? How should the information be represented so as to allow efficient use and re-use? What kinds of constraints and trade-offs would there be? There are no unique answers. In this paper, we discuss some of the ways in which the need to be able to address problems of varying kinds and complexity can be met by different information processing systems. We also discuss different ways in which relevant information can be obtained, and how different kinds of information can be processed and used, by both biological organisms and artificial agents. We analyse several constraints and design features, and show how they relate both to biological organisms, and to lessons that can be learned from building artificial systems. Our standpoint overlaps with Karmiloff-Smith (1992) in that we assume that a collection of mechanisms geared to learning and developing in biological environments are available in forms that constrain, but do not determine, what can or will be learnt by individuals.     

A digital signal processing system for EEG frequency analysis

This paper describes the digital signal processing work of a research project for studying children's cognitive processes by analyzing EEG signals during school-related tasks. The EEG being analyzed involves two homologous channels (left and right parietal area), and is recorded on magnetic tapes. The objective of the analysis is to determine if, by examining the alpha band of the ongoing EEG, different school tasks and correct vs incorrect responses can be detected. Analysis of alpha-band calls for the determination of signal power in the 7-12 Hz frequency band (adjusted for the age of the subjects) for each channel as well as correlation between the channels. A digital signal processing scheme implemented on an Apple II microcomputer was developed for such an analysis. The results obtained are discussed.     

SSK-DDoS: distributed stream processing framework based classification system for DDoS attacks

Cluster Computing - Distributed denial of service (DDoS) is an immense threat for Internet based-applications and their resources. It immediately floods the victim system by transmitting a large...     

Peach: a simple Perl-based system for distributed computation and its application to cryo-EM data processing

A simple distributed processing system named "Peach" was developed to meet the rising computational demands of modern structural biology (and other) laboratories without additional expense by using existing hardware resources more efficiently. A central server distributes jobs to idle workstations in such a way that each computer is used maximally, but without disturbing intermittent interactive users. As compared to other distributed systems, Peach is simple, easy to install, easy to administer, easy to use, scalable, and robust. While it was designed to queue and distribute large numbers of small tasks to participating computers, it can also be used to send single jobs automatically to the fastest currently available computer and/or survey the activity of an entire laboratory's computers. Tests of robustness and scalability are reported, as are three specific electron cryomicroscopy applications where Peach enabled projects that would not otherwise have been feasible without an expensive, dedicated cluster.     

The hypocretin neuron system: an arousal system in the human brain

Hypocretins are recently discovered neuropeptides produced by a small group of posterior hypothalamic neurons which project widely over the neuroaxis. In this study, we note that hypocretin neuron perikarya in the human brain are localized to the perifornical region of the posterior hypothalamus, extending into the lateral hypothalamus. These neurons lightly innervate all areas of cerebral cortex studied in a variable pattern with denser innervation of association cortex than primary motor or sensory cortex. There is a dense innervation of hypothalamus, locus coeruleus, raphe nuclei, midline thalamus and nucleus of the diagonal band-nucleus basalis complex of the forebrain. This pattern of projections from the hypocretin neurons is compatible with an important role in arousal and the maintenance of the waking state.     

miRAS: a data processing system for miRNA expression profiling study

Background  

The study of microRNAs (miRNAs) is attracting great considerations. Recent studies revealed that miRNAs play as important regulators of gene expression and some even as cancer players or inhibitors. Many studies try to discover new miRNAs and reveal the miRNA expression profile in cancer using a SAGE-based total RNA clone method. However, the data processing of this method is labor-intensive with several different biological databases and more than ten data processing steps involved.     

The Drosophila neural lineages: a model system to study brain development and circuitry

In Drosophila, neurons of the central nervous system are grouped into units called lineages. Each lineage contains cells derived from a single neuroblast. Due to its clonal nature, the Drosophila brain is a valuable model system to study neuron development and circuit formation. To better understand the mechanisms underlying brain development, genetic manipulation tools can be utilized within lineages to visualize, knock down, or over-express proteins. Here, we will introduce the formation and development of lineages, discuss how one can utilize this model system, offer a comprehensive list of known lineages and their respective markers, and then briefly review studies that have utilized Drosophila neural lineages with a look at how this model system can benefit future endeavors.     

The EEG, spike activity and the brain processor: an attempt at paradigm analysis]

A notion is introduced about the brain processor as a natural mechanism of brain activity, which is close to the neurocomputer technology. In contrast to the common computer metaphor, this notion can be used as a real basis for explanation of many brain phenomena.     

The brain as a geometer

The fragmentary cues we have on the geometric aptitudes of the brain (e.g., in evaluating shapes or appreciating depth) do not lead to a unified model of perceptual geometry. In parallel with physiological studies, aimed at explaining how perception works, I suggest developing the study of the geometrical capabilities of the brain, in order to learn precisely what is accomplished.