Computational analysis of epigenetic information in human DNA sequences

Over the last few years, investigations of human epigenetic profiles have identified key elements of change to be Histone Modifications, stable and heritable DNA methylation and Chromatin remodeling. These factors determine gene expression levels and characterise conditions leading to disease. In order to extract information embedded in long DNA sequences, data mining and pattern recognition tools are widely used, but efforts have been limited to date with respect to analyzing epigenetic changes, and their role as catalysts in disease onset. Useful insight, however, can be gained by investigation of associated dinucleotide distributions. The focus of this paper is to explore specific dinucleotides frequencies across defined regions within the human genome, and to identify new patterns between epigenetic mechanisms and DNA content. Signal processing methods, including Fourier and Wavelet Transformations, are employed and principal results are reported.

Finding within-organisation spatial information on the web

Information available on company websites can help people navigate to the offices of groups and individuals within the company. Automatically retrieving this within-organisation spatial information is a challenging AI problem This paper introduces a novel unsupervised pattern-based method to extract within-organisation spatial information by taking advantage of HTML structure patterns, together with a novel Conditional Random Fields (CRF) based method to identify different categories of within-organisation spatial information. The results show that the proposed method can achieve a high performance in terms of F-Score, indicating that this purely syntactic method based on web search and an analysis of HTML structure is well-suited for retrieving within-organisation spatial information.

Informed learning in the undergraduate classroom: The role of information experiences in shaping outcomes

This research aimed to inform the design of effective information literacy lessons in higher education. Phenomenography, a research approach designed to study human experience, was used to explore the experiences of a teacher and undergraduate students using information to learn about language and gender issues. The findings show that the way learners use information influences content-focused learning outcomes, and reveal an instructional pattern for enabling students to use information while becoming aware of the topic they are investigating. Based on the findings, a design model is offered in which learning outcomes are realized through targeted information literacy activities.

Multi Pattern Dynamic Time Warping For Automatic Speech Recognition

We are addressing the problem of jointly using multiple noisy speech patterns for automatic speech recognition (ASR), given that they come from the same class. If the user utters a word K times, the ASR system should try to use the information content in all the K patterns of the word simultaneously and improve its speech recognition accuracy compared to that of the single pattern based speech recognition. T address this problem, recently we proposed a Multi Pattern Dynamic Time Warping (MPDTW) algorithm to align the K patterns by finding the least distortion path between them. A Constrained Multi Pattern Viterbi algorithm was used on this aligned path for isolated word recognition (IWR). In this paper, we explore the possibility of using only the MPDTW algorithm for IWR. We also study the properties of the MPDTW algorithm. We show that using only 2 noisy test patterns (10 percent burst noise at -5 dB SNR) reduces the noisy speech recognition error rate by 37.66 percent when compared to the single pattern recognition using the Dynamic Time Warping algorithm.

Neurochemical regulation of auditory information processing studied with EEG/MEG: application to schizophrenia

Cognitive impairments of attention, memory and executive functions are a fundamental feature of the pathophysiology of schizophrenia. The neurophysiological and neurochemical changes in the auditory cortex are shown to underlie cognitive impairmentsin schizophrenia patients. Functional state of the neural substrate of auditory information processing could be objectively and non-invasively probed with auditory event-related potentials (ERPs) and event- related fields (ERFs). In the current work, we explored the neurochemical effect on the neural origins of auditory information processing in relation to schizophrenia. By means of ERPs/ERFs we aimed to determine how neural substrates of auditory information processing are modulated by antipsychotic medication in schizophrenia spectrum patients (Studies I, II) and by neuropharmacological challenges in healthy human subjects (Studies III, IV). First, with auditory ERPs we investigated the effects of olanzapine (Study I) and risperidone (Study II) in a group of patients with schizophrenia spectrum disorders. After 2 and 4 weeks of treatment, olanzapine has no significant effects on mismatch negativity(MMN) and P300, which, as it has been suggested, respectively reflect preattentive and attention-dependent information processing. After 2 weeks of treatment, risperidone has no significant effect on P300, however risperidone reduces P200 amplitude. This latter effect of risperidone on neural resources responsible for P200 generation could be partly explained through the action of dopamine. Subsequently, we used simultaneous EEG/MEG to investigate the effects of memantine (Study III) and methylphenidate (Study IV) in healthy subjects. We found that memantine modulates MMN response without changing other ERP components. This could be interpreted as being due to the possible influence of memantine through the NMDA receptors on auditory change- detection mechanism, with processing of auditory stimuli remaining otherwise unchanged. Further, we found that methylphenidate does not modulate the MMN response. This finding could indicate no association between catecholaminergic activities and electrophysiological measures of preattentive auditory discrimination processes reflected in the MMN. However, methylphenidate decreases the P200 amplitudes. This could be interpreted as a modulation of auditory information processing reflected in P200 by dopaminergic and noradrenergic systems. Taken together, our set of studies indicates a complex pattern of neurochemical influences produced by the antipsychotic drugs in the neural substrate of auditory information processing in patients with schizophrenia spectrum disorders and by the pharmacological challenges in healthy subjects studied with ERPs and ERFs.

Spatial and diurnal pattern of protein foraging by Bactrocera tryoni (Froggatt) on a host plant

Background: Queensland fruit fly, Bactrocera tryoni, is the major pest fruit fly in Australia. Protein bait sprays, where insecticides are mixed with spot applications of a protein based food lure, are one of the sustainable pre-harvest fruit fly management strategies used in Australia. Although protein bait sprays do manage fruit fly infestation in the field, there is little science underpinning this technique and so improving its efficacy is difficult. Lacking information includes where and when to apply protein bait in order to best target foraging B. tryoni. As part of new work in this area, we investigated the effect of height of protein on tree and host plant fruiting status on the spatial and temporal protein foraging patterns of B. tryoni. MEthod: The work was conducted in the field using nectarine and guava plants and wild B. tryoni at Redland Bay, Queensland, Australia. Spot sprays of protein bait were applied to the foliage of randomly selected fruiting and non-fruiting trees. Each tree received protein bait spot sprays on the lower and higher foliage at 0530hrs. The number, sex and species of flies that fed on each protein spot were recorded hourly from 0600hrs through to 1800hrs.Results: For nectarines, there was a significant difference in the number of B. tryoni feeding on protein bait placed at different locations within the tree (ANOVA, F = 8.898, p = 0.001). More flies fed on protein placed on higher foliage relative to lower, irrespective of the fruiting status of the nectarine trees. A significant difference was also observed in the diurnal protein feeding pattern of B. tryoni (ANOVA, F = 2.164, p = 0.024), with more flies feeding at 1600hrs. Results for guava are still being collected and will be presented at the meeting.Conclusions: We conclude that B. tryoni effectively forages for protein at heights higher than 1.3m from ground, indicating greater efficacy of protein bait when applied at foliage higher in the canopy. Bactrocera tryoni actively forages for protein throughout the day, with a highest feeding peak at 1600hrs. The lack of significant difference in the spatial protein foraging pattern between fruiting and non-fruiting nectarine trees may be a real result, or may have resulted from the fruiting tree being very close (within 1 – 2 metres) of the non-fruiting tree. This hypothesis is being tested in the guava trial.

Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

The determination of spatial pattern in Dictyostelium discoideum

Free-living amoebae of the cellular slime mould Dictyostelium discoideum aggregate when starved and give rise to a long and thin multicellular structure, the slug. The slug resembles a metazoan embryo, and as with other embryos it is possible to specify a fate map. In the case of Dictyostelium discoideum the map is especially simple: cells in the anterior fifth of the slug die and form a stalk while the majority of those in the posterior differentiate into spores. The genesis of this anterior-posterior distinction is the subject of our review. In particular, we ask: what are the relative roles of individual pre-aggregative predispositions and post-aggregative position in determining cell fate? We review the literature on the subject and conclude that both factors are important. Variations in nutritional status, or in cell cycle phase at starvation, can bias the probability that an amoeba differentiates into a stalk cell or a spore. On the other hand, isolates, or slug fragments, consisting of only prestalk cells or only prespore cells can regulate so as to result in a normal range of both cell types. We identify three levels of control, each being responsible for guiding patterning in normal development: (i) 'coin tossing', whereby a cell autonomously exhibits a preference for developing along either the stalk or the spore pathway with relative probabilities that can be influenced by the environment; (ii) 'chemical kinetics', whereby prestalk and prespore cells originate from undifferentiated amoebae on a probabilistic basis but, having originated, interact (e.g. via positive and negative feedbacks), and the interaction influences the possibility of conversion of one cell type into the other, and (iii) 'positional information', in which the spatial distribution of morphogens in the slug influences the pathway of differentiation. In the case of possibilities (i) and (ii), sorting out of like cell types leads to the final spatial pattern. In the case of possibility (iii), the pattern arises in situ.

The precision of regulation in Dictyostelium discoideum: implications for cell-type proportioning in the absence of spatial pattern

We have made careful counts of the exact number of spore, stalk and basal disc cells in small fruiting bodies of Dictyostelium discoideum (undifferentiated amoebae are found only rarely and on average their fraction is 4.96 x 10(-4)). (i) Within aggregates of a given size, the relative apportioning of amoebae to the main cell types occurs with a remarkable degree of precision. In most cases the coefficient of variation (c.v.) in the mean fraction of cells that form spores is within 4.86%. The contribution of stalk and basal disc cells is highly variable when considered separately (c.v.'s upto 25% and 100%, respectively), but markedly less so when considered together. Calculations based on theoretical models indicate that purely cell-autonomous specification of cell, fate cannot account for die observed accuracy of proportioning. Cell-autonomous determination to a prestalk or prespore condition followed by cell type interconversion, and stabilised by feedbacks, suffices to explain the measured accuracy. (ii) The fraction of amoebae that differentiates into spores increases monotonically with the total number of cells. This fraction rises from an average of 73.6% for total cell numbers below 30 and reaches 86.0% for cell numbers between 170 and 200 (it remains steady thereafter at around 86%). Correspondingly, the fraction of amoebae differentiating into stalk or basal disc decreases viith total size. These trends are in accordance with evolutionary expectations and imply that a mechanism for sensing the overall size of the aggregate also plays an essential role in the determination of cell-type proportions.

Use of climate information for farm-level decision making: rainfed groundnut in southern India

The production of rainfed crops in semi-arid tropics exhibits large variation in response to the variation in seasonal rainfall. There are several farm-level decisions such as the choice of cropping pattern, whether to invest in fertilizers, pesticides etc., the choice of the period for planting, plant population density etc. for which the appropriate choice (associated with maximum production or minimum risk) depends upon the nature of the rainfall variability or the prediction for a specific year. In this paper, we have addressed the problem of identifying the appropriate strategies for cultivation of rainfed groundnut in the Anantapur region in a semi-arid part of the Indian peninsula. The approach developed involves participatory research with active collaboration with farmers, so that the problems with perceived need are addressed with the modern tools and data sets available. Given the large spatial variation of climate and soil, the appropriate strategies are necessarily location specific. With the approach adopted, it is possible to tap the detailed location specific knowledge of the complex rainfed ecosystem and gain an insight into the variety of options of land use and management practices available to each category of stakeholders. We believe such a participatory approach is essential for identifying strategies that have a favourable cost-benefit ratio over the region considered and hence are associated with a high chance of acceptance by the stakeholders. (C) 2002 Elsevier Science Ltd. All rights reserved.

Urban Sprawl Pattern Analysis Using GIS

Urbanisation has evinced interest from a wide section of the society including experts, amateurs, and novices. The multidisciplinary scope of the subject invokes the interest from ecologists, to urban planners and civil engineers, to sociologists, to administrators and policy makers, students and finally the common man. With the development and infrastructure initiatives mostly around the urban centres, the impacts of urbanisation and sprawl would be on the environment and the natural resources. The wisdom lies in how effectively we plan the urban growth without - hampering the environment, excessively harnessing the natural resources and eventually disturbing the natural set-up. The research on these help urban residents and policymakers make informed decisions and take action to restore these resources before they are lost. Ultimately the power to balance the urban ecosystems rests with regional awareness, policies, administration practices, management issues and operational problems. This publication on urban systems is aimed at helping scientists, policy makers, engineers, urban planners and ultimately the common man to visualise how towns and cities grow over a period of time based on investigations in the regions around the highway and cities. Two important highways in Karnataka, South India, viz., Bangalore - Mysore highway and the Mangalore - Udupi highway, in Karnataka and the Tiruchirapalli - Tanjavore - Kumbakonam triangular road network in Tamil Nadu, South India, were considered in this investigation. Geographic Information System and Remote Sensing data were used to analyse the pattern of urbanisation. This was coupled with the spatial and temporal data from the Survey of India toposheets (for 1972), satellite imageries procured from National Remote Sensing Agency (NRSA) (LANDSAT TM for 1987 and IRS LISS III for 1999), demographic details from the Census of India (1971, 1981, 1991 and 2001) and the village maps from the Directorate of Survey Settlements and Land Records, Government of Karnataka. All this enabled in quantifying the increase in the built-up area for nearly three decades. With intent of identifying the potential sprawl zones, this could be modelled and projected for the future decades. Apart from these the study could quantify some of the metrics that could be used in the study of urban sprawl.

Efficient Regular Expression Pattern Matching for Network Intrusion Detection Systems using Modified Word-based Automata

Network Intrusion Detection Systems (NIDS) intercept the traffic at an organization's network periphery to thwart intrusion attempts. Signature-based NIDS compares the intercepted packets against its database of known vulnerabilities and malware signatures to detect such cyber attacks. These signatures are represented using Regular Expressions (REs) and strings. Regular Expressions, because of their higher expressive power, are preferred over simple strings to write these signatures. We present Cascaded Automata Architecture to perform memory efficient Regular Expression pattern matching using existing string matching solutions. The proposed architecture performs two stage Regular Expression pattern matching. We replace the substring and character class components of the Regular Expression with new symbols. We address the challenges involved in this approach. We augment the Word-based Automata, obtained from the re-written Regular Expressions, with counter-based states and length bound transitions to perform Regular Expression pattern matching. We evaluated our architecture on Regular Expressions taken from Snort rulesets. We were able to reduce the number of automata states between 50% to 85%. Additionally, we could reduce the number of transitions by a factor of 3 leading to further reduction in the memory requirements.