Dissertations / Theses on the topic 'Sequence Feature'
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Smith, Stephen Mark. "Feature based image sequence understanding." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.316951.
Full textSung, Raymond Chun Wai. "Automatic assembly feature recognition and disassembly sequence generation." Thesis, Heriot-Watt University, 2001. http://hdl.handle.net/10399/478.
Full textLai, Man Lok Michael. "Image sequence coding using intensity-based feature separation." Thesis, University of Cambridge, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284145.
Full textTangirala, Karthik. "Unsupervised feature construction approaches for biological sequence classification." Diss., Kansas State University, 2015. http://hdl.handle.net/2097/19123.
Full textDepartment of Computing and Information Sciences
Doina Caragea
Recent advancements in biological sciences have resulted in the availability of large amounts of sequence data (DNA and protein sequences). Biological sequence data can be annotated using machine learning techniques, but most learning algorithms require data to be represented by a vector of features. In the absence of biologically informative features, k-mers generated using a sliding window-based approach are commonly used to represent biological sequences. A larger k value typically results in better features; however, the number of k-mer features is exponential in k, and many k-mers are not informative. Feature selection is widely used to reduce the dimensionality of the input feature space. Most feature selection techniques use feature-class dependency scores to rank the features. However, when the amount of available labeled data is small, feature selection techniques may not accurately capture feature-class dependency scores. Therefore, instead of working with all k-mers, this dissertation proposes the construction of a reduced set of informative k-mers that can be used to represent biological sequences. This work resulted in three novel unsupervised approaches to construct features: 1. Burrows Wheeler Transform-based approach, that uses the sorted permutations of a given sequence to construct sequential features (subsequences) that occur multiple times in a given sequence. 2. Community detection-based approach, that uses a community detection algorithm to group similar subsequences into communities and refines the communities to form motifs (group of similar subsequences). Motifs obtained using the community detection-based approach satisfy the ZOMOPS constraint (Zero, One or Multiple Occurrences of a Motif Per Sequence). All possible unique subsequences of the obtained motifs are then used as features to represent the sequences. 3. Hybrid-based approach, that combines the Burrows Wheeler Transform-based approach and the community detection-based approach to allow certain mismatches to the features constructed using the Burrows Wheeler Transform-based approach. To evaluate the predictive power of the features constructed using the proposed approaches, experiments were conducted in three learning scenarios: supervised, semi-supervised, and domain adaptation for both nucleotide and protein sequence classification problems. The performance of classifiers learned using features generated with the proposed approaches was compared with the performance of the classifiers learned using k-mers (with feature selection) and feature hashing (another unsupervised dimensionality reduction technique). Experimental results from the three learning scenarios showed that features constructed with the proposed approaches were typically more informative than k-mers and feature hashing.
Nilsson, Daniel. "Genomic feature identification in trypanosomatid parasites /." Stockholm, 2006. http://diss.kib.ki.se/2006/91-7140-789-8/.
Full textBozkurt, Burcin. "Prediction Of Protein Subcellular Localization Using Global Protein Sequence Feature." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/3/1135292/index.pdf.
Full textand self-organizing maps (SOM)"
are used. For classication purposes, support vector machines (SVM)"
, a method of statistical learning theory recently introduced to bioinformatics is used. The aim of the combination of feature extraction, clustering and classification methods is to design an acccurate system that predicts the subcellular localization of proteins presented into the system. Our scheme for combining several methods is cascading or serial combination according to its architecture. In the cascading architecture, the output of a method serves as the input of the other model used.
Islamaj, Rezarta. "Feature generation and analysis applied to sequence classification for splice-site prediction." College Park, Md.: University of Maryland, 2007. http://hdl.handle.net/1903/7745.
Full textThesis research directed by: Dept. of Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Lakshmanan, Arun. "Practice makes imperfect? sequence learning and the discontinuous acquisition of feature use skills /." [Bloomington, Ind.] : Indiana University, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3331241.
Full textTitle from PDF t.p. (viewed on Jul 23, 2009). Source: Dissertation Abstracts International, Volume: 69-11, Section: A, page: 4418. Adviser: Shanker Krishnan.
Ali, Isse. "Analysing and predicting differences between methylated and unmethylated DNA sequence features." Thesis, De Montfort University, 2015. http://hdl.handle.net/2086/12616.
Full textAbril, Ferrando Josep Francesc. "Comparative analysis of eukaryotic gene sequence features." Doctoral thesis, Universitat Pompeu Fabra, 2005. http://hdl.handle.net/10803/7108.
Full textl'increment del nombre de tècniques experimentals de les que es disposa,
permetrà obtenir el catàleg complet de les funcions cel.lulars de
diferents organismes, incloent-hi la nostra espècie. Aquest catàleg
definirà els fonaments sobre els que es podrà entendre millor com els
organismes funcionen a nivell molecular. Al mateix temps es tindran més
pistes sobre els canvis que estan associats amb les malalties. Per tant,
la seqüència en brut, tal i com s'obté dels projectes de seqüenciació de
genomes, no té cap valor sense les anàlisis i la subsegüent anotació de
les característiques que defineixen aquestes funcions. Aquesta tesi
presenta la nostra contribució en tres aspectes relacionats de
l'anotació dels gens en genomes eucariotes.
Primer, la comparació a nivell de seqüència entre els genomes humà i de
ratolí es va dur a terme mitjançant un protocol semi-automàtic. El
programa de predicció de gens SGP2 es va desenvolupar a partir
d'elements d'aquest protocol. El concepte al darrera de l'SGP2 és que
les regions de similaritat obtingudes amb el programa TBLASTX, es fan
servir per augmentar la puntuació dels exons predits pel programa
geneid, amb el que s obtenen conjunts d'anotacions més acurats
d'estructures gèniques. SGP2 té una especificitat que és prou gran com
per que es puguin validar experimentalment via RT-PCR. La validació de
llocs d'splicing emprant la tècnica de la RT-PCR és un bon exemple de
com la combinació d'aproximacions computacionals i experimentals
produeix millors resultats que per separat.
S'ha dut a terme l'anàlisi descriptiva a nivell de seqüència dels llocs
d'splicing obtinguts sobre un conjunt fiable de gens ortòlegs per humà,
ratolí, rata i pollastre. S'han explorat les diferències a nivell de
nucleòtid entre llocs U2 i U12, pel conjunt d'introns ortòlegs que se'n
deriva d'aquests gens. S'ha trobat que els senyals d'splicing ortòlegs
entre humà i rossegadors, així com entre rossegadors, estan més
conservats que els llocs no relacionats. Aquesta conservació addicional
pot ser explicada però a nivell de conservació basal dels introns.
D'altra banda, s'ha detectat més conservació de l'esperada entre llocs
d'splicing ortòlegs entre mamífers i pollastre. Els resultats obtinguts
també indiquen que les classes intròniques U2 i U12 han evolucionat
independentment des de l'ancestre comú dels mamífers i les aus. Tampoc
s'ha trobat cap cas convincent d'interconversió entre aquestes dues
classes en el conjunt d'introns ortòlegs generat, ni cap cas de
substitució entre els subtipus AT-AC i GT-AG d'introns U12. Al contrari,
el pas de GT-AG a GC-AG, i viceversa, en introns U2 no sembla ser inusual.
Finalment, s'han implementat una sèrie d'eines de visualització per
integrar anotacions obtingudes pels programes de predicció de gens i per
les anàlisis comparatives sobre genomes. Una d'aquestes eines, el
gff2ps, s'ha emprat en la cartografia dels genomes humà, de la mosca del
vinagre i del mosquit de la malària, entre d'altres. El programa
gff2aplot i els filtres associats, han facilitat la tasca d'integrar
anotacions de seqüència amb els resultats d'eines per la cerca
d'homologia, com ara el BLAST. S'ha adaptat també el concepte de
pictograma a l'anàlisi comparativa de llocs d splicing ortòlegs, amb el
desenvolupament del programa compi.
El aumento incesante del número de secuencias genómicas, junto con el
incremento del número de técnicas experimentales de las que se dispone,
permitirá la obtención del catálogo completo de las funciones celulares
de los diferentes organismos, incluida nuestra especie. Este catálogo
definirá las bases sobre las que se pueda entender mejor el
funcionamiento de los organismos a nivel molecular. Al mismo tiempo, se
obtendrán más pistas sobre los cambios asociados a enfermedades. Por
tanto, la secuencia en bruto, tal y como se obtiene en los proyectos de
secuenciación masiva, no tiene ningún valor sin los análisis y la
posterior anotación de las características que definen estas funciones.
Esta tesis presenta nuestra contribución a tres aspectos relacionados de
la anotación de los genes en genomas eucariotas.
Primero, la comparación a nivel de secuencia entre el genoma humano y el
de ratón se llevó a cabo mediante un protocolo semi-automático. El
programa de predicción de genes SGP2 se desarrolló a partir de elementos
de dicho protocolo. El concepto sobre el que se fundamenta el SGP2 es
que las regiones de similaridad obtenidas con el programa TBLASTX, se
utilizan para aumentar la puntuación de los exones predichos por el
programa geneid, con lo que se obtienen conjuntos más precisos de
anotaciones de estructuras génicas. SGP2 tiene una especificidad
suficiente como para validar esas anotaciones experimentalmente vía
RT-PCR. La validación de los sitios de splicing mediante el uso de la
técnica de la RT-PCR es un buen ejemplo de cómo la combinación de
aproximaciones computacionales y experimentales produce mejores
resultados que por separado.
Se ha llevado a cabo el análisis descriptivo a nivel de secuencia de los
sitios de splicing obtenidos sobre un conjunto fiable de genes ortólogos
para humano, ratón, rata y pollo. Se han explorado las diferencias a
nivel de nucleótido entre sitios U2 y U12 para el conjunto de intrones
ortólogos derivado de esos genes. Se ha visto que las señales de
splicing ortólogas entre humanos y roedores, así como entre roedores,
están más conservadas que las no ortólogas. Esta conservación puede ser
explicada en parte a nivel de conservación basal de los intrones. Por
otro lado, se ha detectado mayor conservación de la esperada entre
sitios de splicing ortólogos entre mamíferos y pollo. Los resultados
obtenidos indican también que las clases intrónicas U2 y U12 han
evolucionado independientemente desde el ancestro común de mamíferos y
aves. Tampoco se ha hallado ningún caso convincente de interconversión
entre estas dos clases en el conjunto de intrones ortólogos generado, ni
ningún caso de substitución entre los subtipos AT-AC y GT-AG en intrones
U12. Por el contrario, el paso de GT-AG a GC-AG, y viceversa, en
intrones U2 no parece ser inusual.
Finalmente, se han implementado una serie de herramientas de
visualización para integrar anotaciones obtenidas por los programas de
predicción de genes y por los análisis comparativos sobre genomas. Una
de estas herramientas, gff2ps, se ha utilizado para cartografiar los
genomas humano, de la mosca del vinagre y del mosquito de la malaria. El
programa gff2aplot y los filtros asociados, han facilitado la tarea de
integrar anotaciones a nivel de secuencia con los resultados obtenidos
por herramientas de búsqueda de homología, como BLAST. Se ha adaptado
también el concepto de pictograma al análisis comparativo de los sitios
de splicing ortólogos, con el desarrollo del programa compi.
The constantly increasing amount of available genome sequences, along
with an increasing number of experimental techniques, will help to
produce the complete catalog of cellular functions for different
organisms, including humans. Such a catalog will define the base from
which we will better understand how organisms work at the molecular
level. At the same time it will shed light on which changes are
associated with disease. Therefore, the raw sequence from genome
sequencing projects is worthless without the complete analysis and
further annotation of the genomic features that define those functions.
This dissertation presents our contribution to three related aspects of
gene annotation on eukaryotic genomes.
First, a comparison at sequence level of human and mouse genomes was
performed by developing a semi-automatic analysis pipeline. The SGP2
gene-finding tool was developed from procedures used in this pipeline.
The concept behind SGP2 is that similarity regions obtained by TBLASTX
are used to increase the score of exons predicted by geneid, in order to
produce a more accurate set of gene structures. SGP2 provides a
specificity that is high enough for its predictions to be experimentally
verified by RT-PCR. The RT-PCR validation of predicted splice junctions
also serves as example of how combined computational and experimental
approaches will yield the best results.
Then, we performed a descriptive analysis at sequence level of the
splice site signals from a reliable set of orthologous genes for human,
mouse, rat and chicken. We have explored the differences at nucleotide
sequence level between U2 and U12 for the set of orthologous introns
derived from those genes. We found that orthologous splice signals
between human and rodents and within rodents are more conserved than
unrelated splice sites. However, additional conservation can be
explained mostly by background intron conservation. Additional
conservation over background is detectable in orthologous mammalian and
chicken splice sites. Our results also indicate that the U2 and U12
intron classes have evolved independently since the split of mammals and
birds. We found neither convincing case of interconversion between these
two classes in our sets of orthologous introns, nor any single case of
switching between AT-AC and GT-AG subtypes within U12 introns. In
contrast, switching between GT-AG and GC-AG U2 subtypes does not appear
to be unusual.
Finally, we implemented visualization tools to integrate annotation
features for gene- finding and comparative analyses. One of those tools,
gff2ps, was used to draw the whole genome maps for human, fruitfly and
mosquito. gff2aplot and the accompanying parsers facilitate the task of
integrating sequence annotations with the output of homologybased tools,
like BLAST.We have also adapted the concept of pictograms to the
comparative analysis of orthologous splice sites, by developing compi.
Ozturk, Ozgur. "Feature extraction and similarity-based analysis for proteome and genome databases." The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1190138805.
Full textLyons, James Geoffrey. "Enhanced Feature Extraction from Evolutionary Profiles for Protein Fold Recognition." Thesis, Griffith University, 2016. http://hdl.handle.net/10072/365732.
Full textThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Griffith School of Engineering
Science, Environment, Engineering and Technology
Full Text
Kabir, Mitra. "Prediction of mammalian essential genes based on sequence and functional features." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/prediction-of-mammalian-essential-genes-based-on-sequence-and-functional-features(cf8eeed5-c2b3-47c3-9a8f-2cc290c90d56).html.
Full textZhang, Nan. "Feature selection based segmentation of multi-source images : application to brain tumor segmentation in multi-sequence MRI." Phd thesis, INSA de Lyon, 2011. http://tel.archives-ouvertes.fr/tel-00701545.
Full textTaha, May. "Probing sequence-level instructions for gene expression." Thesis, Montpellier, 2018. http://www.theses.fr/2018MONTT096/document.
Full textGene regulation is tightly controlled to ensure a wide variety of cell types and functions. These controls take place at different levels and are associated with different genomic regulatory regions. An actual challenge is to understand how the gene regulation machinery works in each cell type and to identify the most important regulators. Several studies attempt to understand the regulatory mechanisms by modeling gene expression using epigenetic marks. Nonetheless, these approaches rely on experimental data which are limited to some samples, costly and time-consuming. Besides, the important component of gene regulation based at the sequence level cannot be captured by these approaches. The main objective of this thesis is to explain mRNA expression based only on DNA sequences features. In a first work, we use Lasso penalized linear regression to predict gene expression using DNA features such as transcription factor binding site (motifs) and nucleotide compositions. We measured the accuracy of our approach on several data from the TCGA database and find similar performance as that of models fitted with experimental data. In addition, we show that nucleotide compositions of different regulatory regions have a major impact on gene expression. Furthermore, we rank the influence of each regulatory regions and show a strong effect of the gene body, especially introns.In a second part, we try to increase the performances of the model. We first consider adding interactions between nucleotide compositions and applying non-linear transformations on predictive variables. This induces a slight increase in model performances.To go one step further, we then learn deep neuronal networks. We consider two types of neural networks: multilayer perceptrons and convolution networks. Hyperparameters of each network are optimized. The performances of both types of networks appear slightly higher than those of a Lasso penalized linear model. In this thesis, we were able to (i) demonstrate the existence of sequence-level instructions for gene expression and (ii) provide different frameworks based on complementary approaches. Additional work is ongoing, in particular with the last direction based on deep learning, with the aim of detecting additional information present in the sequence
Eberhardt, Katharina [Verfasser], Hilde [Akademischer Betreuer] Haider, and Iring [Akademischer Betreuer] Koch. "What are the basic modules of implicit sequence learning? A feature-based account / Katharina Eberhardt. Gutachter: Hilde Haider ; Iring Koch." Köln : Universitäts- und Stadtbibliothek Köln, 2016. http://d-nb.info/1098427408/34.
Full textEberhardt, Katharina [Verfasser], Hilde Akademischer Betreuer] Haider, and Iring [Akademischer Betreuer] [Koch. "What are the basic modules of implicit sequence learning? A feature-based account / Katharina Eberhardt. Gutachter: Hilde Haider ; Iring Koch." Köln : Universitäts- und Stadtbibliothek Köln, 2016. http://nbn-resolving.de/urn:nbn:de:hbz:38-67021.
Full textLi, Xiaomeng. "Human Promoter Recognition Based on Principal Component Analysis." Thesis, The University of Sydney, 2008. http://hdl.handle.net/2123/3656.
Full textLi, Xiaomeng. "Human Promoter Recognition Based on Principal Component Analysis." University of Sydney, 2008. http://hdl.handle.net/2123/3656.
Full textThis thesis presents an innovative human promoter recognition model HPR-PCA. Principal component analysis (PCA) is applied on context feature selection DNA sequences and the prediction network is built with the artificial neural network (ANN). A thorough literature review of all the relevant topics in the promoter prediction field is also provided. As the main technique of HPR-PCA, the application of PCA on feature selection is firstly developed. In order to find informative and discriminative features for effective classification, PCA is applied on the different n-mer promoter and exon combined frequency matrices, and principal components (PCs) of each matrix are generated to construct the new feature space. ANN built classifiers are used to test the discriminability of each feature space. Finally, the 3 and 5-mer feature matrix is selected as the context feature in this model. Two proposed schemes of HPR-PCA model are discussed and the implementations of sub-modules in each scheme are introduced. The context features selected by PCA are III used to build three promoter and non-promoter classifiers. CpG-island modules are embedded into models in different ways. In the comparison, Scheme I obtains better prediction results on two test sets so it is adopted as the model for HPR-PCA for further evaluation. Three existing promoter prediction systems are used to compare to HPR-PCA on three test sets including the chromosome 22 sequence. The performance of HPR-PCA is outstanding compared to the other four systems.
Xi, Min. "Image sequence guidance for mobile robot navigation." Thesis, Queensland University of Technology, 1998. https://eprints.qut.edu.au/36082/1/36082_Xi_1998.pdf.
Full textPanahandeh, Ghazaleh, Nasser Mohammadiha, and Magnus Jansson. "Ground Plane Feature Detection in Mobile Vision-Aided Inertial Navigation." KTH, Signalbehandling, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-99448.
Full textQC 20121107
Yin, Pei. "Segmental discriminative analysis for American Sign Language recognition and verification." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33939.
Full textTucker, Dominic M. "Mapping and Characterization of Phytophthora sojae and Soybean Mosaic Virus Resistance in Soybean." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/79598.
Full textPh. D.
Elbita, Abdulhakim Mehemed. "Efficient processing of corneal confocal microscopy images : development of a computer system for the pre-processing, feature extraction, classification, enhancement and registration of a sequence of corneal images." Thesis, University of Bradford, 2013. http://hdl.handle.net/10454/6463.
Full textElbita, Abdulhakim M. "Efficient Processing of Corneal Confocal Microscopy Images. Development of a computer system for the pre-processing, feature extraction, classification, enhancement and registration of a sequence of corneal images." Thesis, University of Bradford, 2013. http://hdl.handle.net/10454/6463.
Full textThe data and image files accompanying this thesis are not available online.
Hauser, Václav. "Rozpoznávání obličejů v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219434.
Full textCosta, Gabriella Castro Barbosa. "Uma abordagem para linha de produtos de software científico baseada em ontologia e workflow." Universidade Federal de Juiz de Fora (UFJF), 2013. https://repositorio.ufjf.br/jspui/handle/ufjf/4787.
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CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Uma forma de aprimorar a reutilização e a manutenção de uma família de produtos de software é através da utilização de uma abordagem de Linha de Produtos de Software (LPS). Em algumas situações, tais como aplicações científicas para uma determinada área, é vantajoso desenvolver uma coleção de produtos de software relacionados, utilizando uma abordagem de LPS. Linhas de Produtos de Software Científico (LPSC) diferem-se de Li nhas de Produtos de Software pelo fato de que LPSC fazem uso de um modelo abstrato de workflow científico. Esse modelo abstrato de workflow é definido de acordo com o domínio científico e, através deste workflow, os produtos da LPSC serão instanciados. Analisando as dificuldades em especificar experimentos científicos e considerando a necessidade de composição de aplicações científicas para a sua implementação, constata-se a necessidade de um suporte semântico mais adequado para a fase de análise de domínio. Para tanto, este trabalho propõe uma abordagem baseada na associação de modelo de features e onto logias, denominada PL-Science, para apoiar a especificação e a condução de experimentos científicos. A abordagem PL-Science, que considera o contexto de LPSC, visa auxiliar os cientistas através de um workflow que engloba as aplicações científicas de um dado experimento. Usando os conceitos de LPS, os cientistas podem reutilizar modelos que especificam a LPSC e tomar decisões de acordo com suas necessidades. Este trabalho enfatiza o uso de ontologias para facilitar o processo de aplicação de LPS em domínios científicos. Através do uso de ontologia como um modelo de domínio consegue-se fornecer informações adicionais, bem como adicionar mais semântica ao contexto de LPSC.
A way to improve reusability and maintainability of a family of software products is through the Software Product Line (SPL) approach. In some situations, such as scientific applications for a given area, it is advantageous to develop a collection of related software products, using an SPL approach. Scientific Software Product Lines (SSPL) differs from the Software Product Lines due to the fact that SSPL uses an abstract scientific workflow model. This workflow is defined according to the scientific domain and, using this abstract workflow model, the products will be instantiated. Analyzing the difficulties to specify scientific experiments, and considering the need for scientific applications composition for its implementation, an appropriated semantic support for the domain analysis phase is necessary. Therefore, this work proposes an approach based on the combination of feature models and ontologies, named PL-Science, to support the specification and conduction of scientific experiments. The PL-Science approach, which considers the context of SPL and aims to assist scientists to define a scientific experiment, specifying a workflow that encompasses scientific applications of a given experiment, is presented during this disser tation. Using SPL concepts, scientists can reuse models that specify the scientific product line and carefully make decisions according to their needs. This work also focuses on the use of ontologies to facilitate the process of applying Software Product Line to scientific domains. Through the use of ontology as a domain model, we can provide additional information as well as add more semantics in the context of Scientific Software Product Lines.
Li, Ming. "Sequence and text classification : features and classifiers." Thesis, University of East Anglia, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.426966.
Full textSutanto, Kevin. "RNA Sequence Classification Using Secondary Structure Fingerprints, Sequence-Based Features, and Deep Learning." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/41876.
Full textPiroddi, R. "Multiple-feature object-based segmentation of video sequences." Thesis, University of Surrey, 2004. http://epubs.surrey.ac.uk/842727/.
Full textWang, Caixia. "Using Linear Features for Aerial Image Sequence Mosaiking." Fogler Library, University of Maine, 2004. http://www.library.umaine.edu/theses/pdf/WangC2004.pdf.
Full textMulet, Parada Miguel. "Intensity independent feature extraction and tracking in echocardiographic sequences." Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343557.
Full textNg, Siu-Kin. "Lineage specific genomics features and insights into evolutionary pathways /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?BIEN%202007%20NG.
Full textSchaidnagel, Michael. "Automated feature construction for classification of complex, temporal data sequences." Thesis, University of the West of Scotland, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.692834.
Full textLawver, Jordan D. "Robust Feature Tracking in Image Sequences Using View Geometric Constraints." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1365611706.
Full textYao, Xiaoquan. "Sequence features affecting translation initiation in eukaryotes: A bioinformatic approach." Thesis, University of Ottawa (Canada), 2008. http://hdl.handle.net/10393/27658.
Full textClark, Angus Alistair. "Region classification for the interpretation of video sequences." Thesis, University of Bristol, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302167.
Full textPerera, Weliwaththage Thilini. "Elucidating the Sequence and Structural Features of Human Bence-Jones Proteins." University of Toledo / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1526078353370352.
Full textPerkins, David Neil. "Computer methods for identifying significant features in protein sequences." Thesis, University of Leeds, 1994. http://etheses.whiterose.ac.uk/6772/.
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