6 resultados para FINGERS

em Aston University Research Archive


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Visual information is becoming increasingly important and tools to manage repositories of media collections are highly sought after. In this paper, we focus on image databases and on how to effectively and efficiently access these. In particular, we present effective image browsing systems that are operated on a large multi-touch environment for truly interactive exploration. Not only do image browsers pose a useful alternative to retrieval-based systems, they also provide a visualisation of the whole image collection and let users explore particular parts of the collection. Our systems are based on the idea that visually similar images are located close to each other in the visualisation, that image thumbnails are arranged on a regular lattice (either a regular grid projected on a sphere or a hexagonal lattice), and that large image datasets can be accessed through a hierarchical tree structure. © 2014 International Information Institute.

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Bacteriophage T7 DNA primase recognizes 5'-GTC-3' in single-stranded DNA. The primase contains a single Cys4 zinc-binding motif that is essential for recognition. Biochemical and mutagenic analyses suggest that the Cys4 motif contacts cytosine of 5'-GTC-3' and may also contribute to thymine recognition. Residues His33 and Asp31 are critical for these interactions. Biochemical analysis also reveals that T7 primase selectively binds CTP in the absence of DNA. We propose that bound CTP selects the remaining base G, of 5'-GTC-3', by base pairing. Our deduced mechanism for recognition of ssDNA by Cys4 motifs bears little resemblance to the recognition of trinucleotides of double-stranded DNA by Cys2His2 zinc fingers.

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It has been recognised for some time that a full code of amino acid-based recognition of DNA sequences would be useful. Several approaches, which utilise small DNA binding motifs called zinc fingers, are presently employed. None of the current approaches successfully combine a combinatorial approach to the elucidation of a code with a single stage high throughput screening assay. The work outlined here describes the development of a model system for the study of DNA protein interactions and the development of a high throughput assay for detection of such interactions. A zinc finger protein was designed which will bind with high affinity and specificity to a known DNA sequence. For future work it is possible to mutate the region of the zinc finger responsible for the specificity of binding, in order to observe the effect on the DNA / protein interactions. The zinc finger protein was initially synthesised as a His tagged product. It was not possible however to develop a high throughput assay using the His tagged zinc finger protein. The gene encoding the zinc finger protein was altered and the protein synthesised as a Glutathione S-Transferase (GST) fusion product. A successful assay was developed using the GST protein and Scintillation Proximity Assay technology (Amersham Pharmacia Biotech). The scintillation proximity assay is a dynamic assay that allows the DNA protein interactions to be studied in "real time". This assay not only provides a high throughput method of screening zinc finger proteins for potential ligands but also allows the effect of addition of reagents or competitor ligands to be monitored.

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Protein-DNA interactions are an essential feature in the genetic activities of life, and the ability to predict and manipulate such interactions has applications in a wide range of fields. This Thesis presents the methods of modelling the properties of protein-DNA interactions. In particular, it investigates the methods of visualising and predicting the specificity of DNA-binding Cys2His2 zinc finger interaction. The Cys2His2 zinc finger proteins interact via their individual fingers to base pair subsites on the target DNA. Four key residue positions on the a- helix of the zinc fingers make non-covalent interactions with the DNA with sequence specificity. Mutating these key residues generates combinatorial possibilities that could potentially bind to any DNA segment of interest. Many attempts have been made to predict the binding interaction using structural and chemical information, but with only limited success. The most important contribution of the thesis is that the developed model allows for the binding properties of a given protein-DNA binding to be visualised in relation to other protein-DNA combinations without having to explicitly physically model the specific protein molecule and specific DNA sequence. To prove this, various databases were generated, including a synthetic database which includes all possible combinations of the DNA-binding Cys2His2 zinc finger interactions. NeuroScale, a topographic visualisation technique, is exploited to represent the geometric structures of the protein-DNA interactions by measuring dissimilarity between the data points. In order to verify the effect of visualisation on understanding the binding properties of the DNA-binding Cys2His2 zinc finger interaction, various prediction models are constructed by using both the high dimensional original data and the represented data in low dimensional feature space. Finally, novel data sets are studied through the selected visualisation models based on the experimental DNA-zinc finger protein database. The result of the NeuroScale projection shows that different dissimilarity representations give distinctive structural groupings, but clustering in biologically-interesting ways. This method can be used to forecast the physiochemical properties of the novel proteins which may be beneficial for therapeutic purposes involving genome targeting in general.

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Background: During last decade the use of ECG recordings in biometric recognition studies has increased. ECG characteristics made it suitable for subject identification: it is unique, present in all living individuals, and hard to forge. However, in spite of the great number of approaches found in literature, no agreement exists on the most appropriate methodology. This study aimed at providing a survey of the techniques used so far in ECG-based human identification. Specifically, a pattern recognition perspective is here proposed providing a unifying framework to appreciate previous studies and, hopefully, guide future research. Methods: We searched for papers on the subject from the earliest available date using relevant electronic databases (Medline, IEEEXplore, Scopus, and Web of Knowledge). The following terms were used in different combinations: electrocardiogram, ECG, human identification, biometric, authentication and individual variability. The electronic sources were last searched on 1st March 2015. In our selection we included published research on peer-reviewed journals, books chapters and conferences proceedings. The search was performed for English language documents. Results: 100 pertinent papers were found. Number of subjects involved in the journal studies ranges from 10 to 502, age from 16 to 86, male and female subjects are generally present. Number of analysed leads varies as well as the recording conditions. Identification performance differs widely as well as verification rate. Many studies refer to publicly available databases (Physionet ECG databases repository) while others rely on proprietary recordings making difficult them to compare. As a measure of overall accuracy we computed a weighted average of the identification rate and equal error rate in authentication scenarios. Identification rate resulted equal to 94.95 % while the equal error rate equal to 0.92 %. Conclusions: Biometric recognition is a mature field of research. Nevertheless, the use of physiological signals features, such as the ECG traits, needs further improvements. ECG features have the potential to be used in daily activities such as access control and patient handling as well as in wearable electronics applications. However, some barriers still limit its growth. Further analysis should be addressed on the use of single lead recordings and the study of features which are not dependent on the recording sites (e.g. fingers, hand palms). Moreover, it is expected that new techniques will be developed using fiducials and non-fiducial based features in order to catch the best of both approaches. ECG recognition in pathological subjects is also worth of additional investigations.

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In traditional electrical sensing applications, multiplexing and interconnecting the different sensing elements is a major challenge. Recently, many optical alternatives have been investigated including optical fiber sensors of which the sensing elements consist of fiber Bragg gratings. Different sensing points can be integrated in one optical fiber solving the interconnection problem and avoiding any electromagnetical interference (EMI). Many new sensing applications also require flexible or stretchable sensing foils which can be attached to or wrapped around irregularly shaped objects such as robot fingers and car bumpers or which can even be applied in biomedical applications where a sensor is fixed on a human body. The use of these optical sensors however always implies the use of a light-source, detectors and electronic circuitry to be coupled and integrated with these sensors. The coupling of these fibers with these light sources and detectors is a critical packaging problem and as it is well-known the costs for packaging, especially with optoelectronic components and fiber alignment issues are huge. The end goal of this embedded sensor is to create a flexible optical sensor integrated with (opto)electronic modules and control circuitry. To obtain this flexibility, one can embed the optical sensors and the driving optoelectronics in a stretchable polymer host material. In this article different embedding techniques for optical fiber sensors are described and characterized. Initial tests based on standard manufacturing processes such as molding and laser structuring are reported as well as a more advanced embedding technique based on soft lithography processing.