Dissertations / Theses: 'Biology Classification'

1

Lantz, Henrik. "Phylogeny and classification of the tribe Vanguerieae (Rubiaceae)." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.bibl. [distributör], 2003. http://publications.uu.se/theses/91-554-5529-8/.

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Martin, Traykovski Linda V. (Linda Victoria) 1966. "Acoustic classification of zooplankton." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/49620.

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Wang, Min-Hui. "Classification using phylogenetic trees /." The Ohio State University, 1999. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488190595939375.

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Currie, Sheila. "Data classification for choropleth mapping." Thesis, University of Ottawa (Canada), 1989. http://hdl.handle.net/10393/5725.

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Sanassy, Daven. "Meta-stochastic simulation for systems and synthetic biology using classification." Thesis, University of Newcastle upon Tyne, 2015. http://hdl.handle.net/10443/2993.

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To comprehend the immense complexity that drives biological systems, it is necessary to generate hypotheses of system behaviour. This is because one can observe the results of a biological process and have knowledge of the molecular/genetic components, but not directly witness biochemical interaction mechanisms. Hypotheses can be tested in silico which is considerably cheaper and faster than “wet” lab trialand- error experimentation. Bio-systems are traditionally modelled using ordinary differential equations (ODEs). ODEs are generally suitable for the approximation of a (test tube sized) in vitro system trajectory, but cannot account for inherent system noise or discrete event behaviour. Most in vivo biochemical interactions occur within small spatially compartmentalised units commonly known as cells, which are prone to stochastic noise due to relatively low intracellular molecular populations. Stochastic simulation algorithms (SSAs) provide an exact mechanistic account of the temporal evolution of a bio-system, and can account for noise and discrete cellular transcription and signalling behaviour. Whilst this reaction-by-reaction account of system trajectory elucidates biological mechanisms more comprehensively than ODE execution, it comes at increased computational expense. Scaling to the demands of modern biology requires ever larger and more detailed models to be executed. Scientists evaluating and engineering tissue-scale and bacterial colony sized biosystems can be limited by the tractability of their computational hypothesis testing techniques. This thesis evaluates a hypothesised relationship between SSA computational performance and biochemical model characteristics. This relationship leads to the possibility of predicting the fastest SSA for an arbitrary model - a method that can provide computational headroom for more complex models to be executed. The research output of this thesis is realised as a software package for meta-stochastic simulation called ssapredict. Ssapredict uses statistical classification to predict SSA performance, and also provides high performance stochastic simulation implementations to the wider community.

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Qiao, Mu. "Morphological, Physiological and Molecular Classification of Mouse Retinal Ganglion Cells." Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:26718723.

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Visual information is conveyed from the retina to the brain through axons of retinal ganglion cells (RGCs). There are >20 different subtypes of RGCs, each of which detects specific features. Classification of RGC subtypes is thus essential for us to understand how visual information is processed and delivered to the brain. Here I reported my efforts in classifying different subtypes of RGCs, using morphological, physiological and molecular criteria. A combination of these criteria allowed me to successfully identify subtypes from alpha RGCs, Foxp2-positive RGCs (F-RGCs) and RGCs labeled in a transgenic mouse line W3. First, I presented studies of classifying subtypes of alpha RGCs. Cell attached recording followed by morphology reconstruction revealed four subtypes of alpha-like RGCs: Off-sustained, Off-transient, On-sustained, On-transient subtypes, each of which has distinct morphological properties. In addition, we found osteopontin (OPN) as a molecular marker for all alpha RGCs. Following this discovery, we studied the role of OPN in alpha RGCs, Analysis showed that alpha RGCs preferentially survive and regenerate compared with other RGCs, leading us to test whether OPN can promote axon regeneration. Indeed, by combining OPN with growth factors, we were able to promote axon regenerations of RGCs. Second, I presented work in classifying subtypes of F-RGCs, which are recognized by expressing a transcription factor, Foxp2. Combinatory expression of Foxp2 with other transcriptional factors divides F-RGCs into four subtypes, which form two pairs differing in their dendritic field sizes. Cell attached recording showed that one pair, F-minion and F-minioff RGCs, are direction-selective, while the other pair, F-midion and F-midioff RGCs, are not. Thus, we identified four new subtypes of RGCs labeled by transcriptional factor Foxp2. Third, I described initial efforts in classifying subtypes of RGCs labeled in the transgenic mouse line W3. W3 RGCs can be separated into two group based on their expression levels of fluorescent proteins, with the dimly labeled RGCs (W3D) remained uncharacterized. Initial analysis showed W3D RGCs include at least five subtypes of RGCs, which are different in their structures and physiological properties. Lastly, I described my work in developing a molecular tool for mapping electrical synaptic connections from genetically defined neurons or neuronal subtypes, making use of a dipeptide transporter, Pept2. Cells expressing Pept2 (in a Cre-dependent way) take up a gap junction permeable fluorescent dipeptide, which then diffuses and labels the coupled cells. We tested this method in cultured cells and validated it in mouse retina using AAV carrying Cre-dependent Pept2. I applied this method to one subtype of RGCs, J-RGCs, to label their coupling partners.
Biology, Molecular and Cellular

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Liang, Jiarong. "Federated Learning for Bioimage Classification." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-420615.

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Graham, Martin. "Visualising multiple overlapping classification hierarchies." Thesis, Edinburgh Napier University, 2001. http://researchrepository.napier.ac.uk/Output/2430.

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The revision or reorganisation of hierarchical data sets can result in many possible hierarchical classifications composed of the same or overlapping data sets existing in parallel with each other. These data sets are difficult for people to handle and conceptualise, as they try to reconcile the different perspectives and structures that such data represents. One area where this situation occurs is the study of botanical taxonomy, essentially the classification and naming of plants. Revisions, new discoveries and new dimensions for classifying plants lead to a proliferation of classifications over the same set of plant data. Taxonomists would like a method of exploring these multiple overlapping hierarchies for interesting information, correlations, or anomalies. The application and extension of Information Visualisation (IV) techniques, the graphical display of abstract information, is put forward as a solution to this problem. Displaying the multiple classification hierarchies in a visually appealing manner along with powerful interaction mechanisms for examination and exploration of the data allows taxonomists to unearth previously hidden information. This visualisation gives detail that previous visualisations and statistical overviews cannot offer. This thesis work has extended previous IV work in several respects to achieve this goal. Compact, yet full and unambiguous, hierarchy visualisations have been developed. Linking and brushing techniques have been extended to work on a higher class of structure, namely overlapping trees and hierarchies. Focus and context techniques have been pushed to achieve new effects across the visually distinct representations of these multiple hierarchies. Other data types, such as multidimensional data and large cluster hierarchies have also been displayed using the final version of the visualisation.

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9

Civallero, Edgardo. "UDC Biology Revision Project: First Stage: Class 59 Vertebrates." UDC Consortium, 2010. http://hdl.handle.net/10150/200632.

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The paper presents and describes the work on the revision of the zoology of vertebrates, which is published in E&C 32 and introduced in UDC MRF 2010. This is the first stage of a larger project of revision, correction and update affecting all tables related to systematics (zoology, botany, microbiology and virology) to be undertaken from 2011-2013. The first part of the paper briefly introduces the current systems of classification of living and extinct beings, and explains how different perspectives with respect to the arrangement of biological entities have been reflected (or not) in the UDC schedules. The second part gives an overview of problems detected in UDC prior to this revision and explains solutions that were implemented in UDC MRF 2010 indicating tools and methods used in this work.

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Xiong, Kuangnan. "Roughened Random Forests for Binary Classification." Thesis, State University of New York at Albany, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3624962.

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Binary classification plays an important role in many decision-making processes. Random forests can build a strong ensemble classifier by combining weaker classification trees that are de-correlated. The strength and correlation among individual classification trees are the key factors that contribute to the ensemble performance of random forests. We propose roughened random forests, a new set of tools which show further improvement over random forests in binary classification. Roughened random forests modify the original dataset for each classification tree and further reduce the correlation among individual classification trees. This data modification process is composed of artificially imposing missing data that are missing completely at random and subsequent missing data imputation.

Through this dissertation we aim to answer a few important questions in building roughened random forests: (1) What is the ideal rate of missing data to impose on the original dataset? (2) Should we impose missing data on both the training and testing datasets, or only on the training dataset? (3) What are the best missing data imputation methods to use in roughened random forests? (4) Do roughened random forests share the same ideal number of covariates selected at each tree node as the original random forests? (5) Can roughened random forests be used in medium- to high- dimensional datasets?

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Civallero, Edgardo. "UDC Biology Revision Project: Second Stage: Class 58 Botany." UDC Consortium, 2011. http://hdl.handle.net/10150/236491.

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This text is a brief update on the progress of the revision of biological systematics in UDC that has not had an overall revision for many decades. The first stage of the project, in 2010, included the revision of the taxonomy of vertebrates, and this was completed and published in Extensions and Corrections to the UDC - E&C, 32 (2010). The next stage, completed in 2011, was class 582 Systematic botany, published as the revised table in this issue - E&C, 33 (2011). In this paper, the author of the revised tables provides a brief overview of content organization and presentation in the new schedules and specific information about the revision of Botany.

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Poulter, Graham L. "Rapid statistical classification on the Medline database of biomedical literature." Master's thesis, University of Cape Town, 2008. http://hdl.handle.net/11427/4322.

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Anctil, Benoit. "Signal classification issues in motor unit number estimation." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=31043.

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In the electrophysiological evaluation of neuromuscular disorders, the number of active motor units in a muscle is considered one of the most important indicators of the physiological state of peripheral nerve/muscle systems. Electrophysiological techniques have been designed to estimate this number but, despite considerable effort, they only provide an approximation of the exact number. To assist further development in this field, the specific problem of the classification of stimulus-evoked potentials was investigated. Over 1300 series of signals were recorded from four subjects over a five-week period. From these data sets, those having clearly separable unique responses were selected and unsupervised learning methods were employed to identify the different response classes. The lowest misclassification error rate obtained under these conditions was 25%. A subsequent evaluation of an interactive graph-theoretic clustering technique presented interesting results with an error rate of 8%. The findings hold promise for developing better methods to estimate the number of motor units.

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Fong, Ruth Catherine. "Leveraging Human Brain Activity to Improve Object Classification." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:14398538.

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Today, most object detection algorithms differ drastically from how humans tackle visual problems. In this thesis, I present a new paradigm for improving machine vision algorithms by designing them to better mimic how humans approach these tasks. Specifically, I demonstrate how human brain activity from functional magnetic resonance imaging (fMRI) can be leveraged to improve object classification. Inspired by the graduated manner in which humans learn, I present a novel algorithm that simulates learning in a similar fashion by more aggressively penalizing the misclassification of certain training datum. I propose a method to learn annotations that capture the difficulty of detecting an object in an image from auxilliary brain activity data. I then demonstrate how to leverage these annotations by using a modified definition of Support Vector Machines (SVMs) that uses these annotations to weight training data in an object classification task. An experimental comparison between my procedure and a parallel control shows that my techniques provide significant improvements in object classification. In particular, my protocol empirically halved the gap in classification accuracy between SVM classifiers that used state-of-the-art, yet computationally intensive convolutional neural net (CNN) features and those that used out-of-the box, efficient histogram of oriented gradients (HOG) descriptors. Further analysis demonstrates that my experimental results support findings in neuroimaging literature about the roles different cortical regions play in object recognition.

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Abdel-Hady, Mohamed Helmy Abdel-Rahman. "Molecular genetic profiling of low grade gliomas : towards a molecular genetic classification /." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1486402957195399.

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Lumpkin, Robert. "Parameter Classification and Analysis of Neuronal Systems with Astrocytic Modulation of Behaviour." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1563206513875333.

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Marshall, Jeremy H. "Natural classification and the reality of higher taxa." Thesis, University of Oxford, 1989. http://ora.ox.ac.uk/objects/uuid:240dd5d5-41f2-4378-a6d0-4c11c1e5351a.

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Having outlined the present situation as regards rival taxonomic philosophies, and some of its historical background, the thesis examines this attempt to recategorize taxa as individual-like entities, and finds it wanting. The properties of species which render them regardable as individuals do not readily extend to more inclusive levels, or, if they do, are not readily restricted solely to cladistic taxa. Cladistic systematization, in moving away from the notion of a taxon as a class of similar entities, may cease to convey the information expected of a classification system. The practice of biology requires a more flexible and more stable taxonomy than can be provided by strict adherence to cladistic rules, and taxa are-better regarded as 'historical classes', delineated neither by pure unanalysed similarity nor by logical transformation of hypotheses of phylogenetic relationship, but by a considered pragmatic synthesis of the two, employing the notion of convexity as a criterion of acceptability.

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Torii, Manabu. "Investigation of term classification with applications to sortal anaphora resolution in the biology domain." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file 0.57 Mb., 115 p, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:3200527.

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Cooper, J. Andrew. "Monophyly and intrarelationships of the family Pleuronectidae (Pleuronectiformes), with a revised classification." Thesis, University of Ottawa (Canada), 1996. http://hdl.handle.net/10393/10047.

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A cladistic analysis of interrelationships for 53 (of 58) pleuronectid (Order Pleuronectiformes) species was performed using 106 morphologial and osteological characters. The analysis resulted in a 50% majority-rule consensus tree of 128 equally parsimonious cladograms (heuristic search, 403 steps, ci = 0.33, ri = 0.79). Only five of 47 resolved nodes were observed in less than 100% of the cladograms. These five nodes are restricted to interrelationships within one subfamily. The Pleuronectidae (sensu Chapleau and Keast, 1988) are monophyletic based on ten synapomorphies. In addition, five subfamilies were defined Hippoglossinae, Eopsettinae, Lyonsettinae, Hippoglossoidinae and Pleuronectinae. The largest subfamily, the Pleuronectinae, was further subdivided into four tribes. Psettichyini, Isopsettini, Microstomini and Pleuronectini. The interrelationships established within Pleuronectidae provide a strong foundation for a simplified yet phylogenetically informative taxonomic nomenclature. The genera Atherestes and Reinhardtius; Embassichthys, Errex, Glyptocephalus, Tanakius and Microstomus; Hypsopsetta and Pleuronichthys are regrouped in Reinhardtus; Microstomus and Pleuronichthys, respectively. To preserve the monophyletic status of Eopsetta, E. exilis was reassigned to the genus Lyopsetta (Lyopsettinae). The genus Pleuronectes (as defined by Sakamoto, 1984a) is polyphyletic. It now includes only five species: Pleuronectes glacialis, P. pinnifasciatus, P. platessa, P. putnami and P. quadrituberculatus. Other Pleuronectes species are reclassified in Isopsetta, Limanda, Parophrys, Platichthys, Psettichys, and Pseudopleuronectes. The monophyletic status of the genus Limanda (six species) is uncertain based on unresolved relationships between these species and other taxa in the tribe Pleuronectini.

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Weerasooriya, Aruna Dharmapriya. "Systematics, phylogeny and reproductive biology of Mitrephora (Annonaceae)." Thesis, Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B23316895.

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Shah, Rohan Shiloh. "Support vector machines for classification and regression." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=100247.

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In the last decade Support Vector Machines (SVMs) have emerged as an important learning technique for solving classification and regression problems in various fields, most notably in computational biology, finance and text categorization. This is due in part to built-in mechanisms to ensure good generalization which leads to accurate prediction, the use of kernel functions to model non-linear distributions, the ability to train relatively quickly on large data sets using novel mathematical optimization techniques and most significantly the possibility of theoretical analysis using computational learning theory. In this thesis, we discuss the theoretical basis and computational approaches to Support Vector Machines.

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Tcheimegni, Elie. "Kernel Based Relevance Vector Machine for Classification of Diseases." Thesis, Bowie State University, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3558597.

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Motivated by improvements of diseases and cancers depiction that will be facilitated by an ability to predict the related syndrome occurrence; this work employs a data-driven approach to developing cancer classification/prediction models using Relevance Vector Machine (RVM), a probabilistic kernel-based learning machine.

Drawing from the work of Bertrand Luvision, Chao Dong, and the outcome result classification of electrocardiogram signals by S. Karpagachelvi ,which show the superiority of the RVM approach as compared to traditional classifiers, the problem addressed in this research is to design a program of piping components together in a graphic workflows which could help improve the accuracy classification/regression of two models structure methods (Support vector machines and kernel based Relevance Vector machines) for better prediction performance of related diseases and then make a comparison among both methods using clinical data.

Would the application of relevance vector machine on these data classification improve their coverage. We developed a hierarchical Bayesian model for binary and bivariate data classification using the RBF, sigmoid kernel, with different parameterization and varied threshold. The parameters of the kernel function are considered as model parameters. The finding results allow us to conclude that RVM is almost equal to SVM on training efficiency and classification accuracy, but RVM performs better on sparse property, generalization ability, and decision speed.

Meanwhile, the use of RVM raise some issues due to the fact that it used less support vectors but it trains much faster for non-linear kernel than SVM-light. Finally, we test those approaches on a corpus of public release phenotype data. Further research to improve the accuracy prediction with more patients' data is needed. Appendices provide the SVM and RVM derivation in detail. One important area of focus is the development of models for predicting cancers.

Keywords: Support Vector Machines, Relevance Vector Machine, Rapidminer, Tanagra, Accuracy's values.

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Huang, Lunde. "Identification and classification of JIGR1, a novel MADF-containing gene essential for Drosophila development." Thesis, University of Ottawa (Canada), 2008. http://hdl.handle.net/10393/27694.

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The Drosophila melanogaster model system is capable of providing valuable insight to neurodegenerative disease research. The Drosophila jing zinc finger transcription factor plays an essential role in CNS and tracheal cell differentiation. It is important to identify and characterize jing interactors to better understand its molecular mechanism. The JIGR1 gene was previously identified as a genetic modifier of jing and contains a MADF DNA-binding domain. The MADF domain is found in a large and diverse family with weak sequence homology. JIGR1 was found to genetically interact with other jing-interactors to maintain photoreceptor survival. JIGR1 is predominantly localized to the nuclei and is ubiquitously present throughout all stages of embryogenesis, particularly in the CNS and PNS, suggesting a role in fundamental cellular processes. Proper regulation of JIGR1 dosage is important, as its over-expression is associated with defects in the CNS and tracheal development. By characterizing JIGR1 and having a better concept of jing, with a homolog found in vertebrates, a better understanding of the complex vertebrate developmental pathways is gained.

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Wang, Chen. "Novel software tool for microsatellite instability classification and landscape of microsatellite instability in osteosarcoma." Miami University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=miami1554829925088174.

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25

Luna, Ruiz Jose de Jesus 1959. "The crown system of barley: I. Temperature, seeding depth and genotypic effects II. Classification and description." Thesis, The University of Arizona, 1992. http://hdl.handle.net/10150/291560.

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Little is known about the crown system and its association with plant growth and development in spring cereals. This study investigated temperature, seeding depth and genotypic effects on crown development of barley; relationships between crown and seminal root systems; and classification and description of crown systems under deep seeding. Two greenhouse experiments were performed using PVC tubes. Low temperature and deep seeding reduced percentage and rate of emergence but increased crown number, crown depth, and crown weight in most genotypes. Crown number, crown depth and crown weight showed increased associations with seminal root, whole root, and shoot weight at low temperature and deep seeding in most genotypes. Deep plantings showed that crown systems of barley can be classified as unicrown, bicrown and multicrown types with some variants. One line produced plants with no subcrown internode under 12.5 cm planting. Our results suggested that the crown is a potential source of crown roots and tillers.

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Pastor, Ashutosh. "Structure-function relation and chaperone assisted folding of maltodextrin glucosidase: a structural biology and protein engineering approach." Thesis, IIT Delhi, 2016. http://localhost:8080/xmlui/handle/12345678/7107.

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Simoni, Giulia. "Modeling Startegies for Computational Systems Biology." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/254361.

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Mathematical models and their associated computer simulations are nowadays widely used in several research fields, such as natural sciences, engineering, as well as social sciences. In the context of systems biology, they provide a rigorous way to investigate how complex regulatory pathways are connected and how the disruption of these processes may contribute to the develop- ment of a disease, ultimately investigating the suitability of specific molecules as novel therapeutic targets. In the last decade, the launching of the precision medicine initiative has motivated the necessity to define innovative computational techniques that could be used for customizing therapies. In this context, the combination of mathematical models and computer strategies is an essential tool for biologists, which can analyze complex system pathways, as well as for the pharmaceutical industry, which is involved in promoting programs for drug discovery. In this dissertation, we explore different modeling techniques that are used for the simulation and the analysis of complex biological systems. We analyze the state of the art for simulation algorithms both in the stochastic and in the deterministic frameworks. The same dichotomy has been studied in the context of sensitivity analysis, identifying the main pros and cons of the two approaches. Moreover, we studied the quantitative system pharmacology (QSP) modeling approach that elucidates the mechanism of action of a drug on the biological processes underlying a disease. Specifically, we present the definition, calibration and validation of a QSP model describing Gaucher disease type 1 (GD1), one of the most common lysosome storage rare disorders. All of these techniques are finally combined to define a novel computational pipeline for patient stratification. Our approach uses modeling techniques, such as model simulations, sensitivity analysis and QSP modeling, in combination with experimental data to identify the key mechanisms responsible for the stratification. The pipeline has been applied to three test cases in different biological contexts: a whole-body model of dyslipidemia, the QSP model of GD1 and a QSP model of cardiac electrophysiology. In these test cases, the pipeline proved to be accurate and robust, allowing the interpretation of the mechanistic differences underlying the phenotype classification.

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Simoni, Giulia. "Modeling Startegies for Computational Systems Biology." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/254361.

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Mathematical models and their associated computer simulations are nowadays widely used in several research fields, such as natural sciences, engineering, as well as social sciences. In the context of systems biology, they provide a rigorous way to investigate how complex regulatory pathways are connected and how the disruption of these processes may contribute to the develop- ment of a disease, ultimately investigating the suitability of specific molecules as novel therapeutic targets. In the last decade, the launching of the precision medicine initiative has motivated the necessity to define innovative computational techniques that could be used for customizing therapies. In this context, the combination of mathematical models and computer strategies is an essential tool for biologists, which can analyze complex system pathways, as well as for the pharmaceutical industry, which is involved in promoting programs for drug discovery. In this dissertation, we explore different modeling techniques that are used for the simulation and the analysis of complex biological systems. We analyze the state of the art for simulation algorithms both in the stochastic and in the deterministic frameworks. The same dichotomy has been studied in the context of sensitivity analysis, identifying the main pros and cons of the two approaches. Moreover, we studied the quantitative system pharmacology (QSP) modeling approach that elucidates the mechanism of action of a drug on the biological processes underlying a disease. Specifically, we present the definition, calibration and validation of a QSP model describing Gaucher disease type 1 (GD1), one of the most common lysosome storage rare disorders. All of these techniques are finally combined to define a novel computational pipeline for patient stratification. Our approach uses modeling techniques, such as model simulations, sensitivity analysis and QSP modeling, in combination with experimental data to identify the key mechanisms responsible for the stratification. The pipeline has been applied to three test cases in different biological contexts: a whole-body model of dyslipidemia, the QSP model of GD1 and a QSP model of cardiac electrophysiology. In these test cases, the pipeline proved to be accurate and robust, allowing the interpretation of the mechanistic differences underlying the phenotype classification.

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Gatti, Stefano. "Object Detection for Cell Classification." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/22034/.

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The human body is an incredibly complex system with deeply interconnected functions. To understand this behaviour requires the knowledge of the genes expressed by every cell in a region of the tissue. As a direct consequence of the complexity of biological tissues the analysis of such images is extremely complex. The objective of this work is to use techniques of object detection and instance segmentation to help with the analysis of the image, by identifying both the location and shapes of the cells and their content. In addition to the work’s original objective, a methodology is outlined for dividing the cells in the image, rather than just identifying their positions, based on the application of Voronoi diagrams.

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Ngwira, Patricia. "Nucleotide sequence diversity in maize and grass-infecting streak geminiviruses: A basis for nucleotide sequence classification and identification /." The Ohio State University, 1997. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487945015618607.

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Sarrazin, François. "Méthodes comparées d'analyse aérienne pour la classification de la végétation en toundra arbustive, territoire du Yukon." Thesis, University of Ottawa (Canada), 1987. http://hdl.handle.net/10393/5375.

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Davies, Robert William. "On the Generation of a Classification Algorithm from DNA Based Microarray Studies." Thesis, University of Ottawa (Canada), 2010. http://hdl.handle.net/10393/28583.

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The purpose of this thesis is to build a classification algorithm using a Genome Wide Association (GWA) study. Briefly, a GWA is a case-control study using genotypes derived from DNA microarrays for thousands of people. These microarrays are able to acquire the genotypes of hundreds of thousands of Single Nucleotide Polymorphisms (SNPs) for a person at a time. In this thesis, we first describe the processes necessary to prepare the data for analysis. Next, we introduce the Naive Bayes classification algorithm and a modification so that effects of a SNP on the disease of interest are weighted by a Bayesian posterior probability of association. This thesis then uses the data from three coronary artery disease GWAs, one as a training set and two as test sets, to build and test the classifier. Finally, this thesis discusses the relevance of the results and the generalizability of this method to future studies.

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Spooner, David Michael. "The systematics of Simsia (Compositae : Heliantheae) /." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487335992903456.

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Miya, Tshoanelo Portia. "Molecular systematics and antifreeze biology of sub-Antarctic notothenioid fishes." Thesis, Rhodes University, 2014. http://hdl.handle.net/10962/d1020938.

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Fishes of the perciform suborder Notothenioidei are found in Antarctic and sub-Antarctic waters that are separated by the Antarctic Polar Front (APF), with some species being distributed on both sides of this front. In this wide latitudinal range, these fishes are exposed to different temperatures ranging from -2 °C in the High Antarctic regions to 12 °C in the sub-Antarctic regions. To survive in icy Antarctic waters, the Antarctic notothenioid species have evolved antifreeze glycoproteins (AFGPs) that prevent their body fluids from freezing. The findings of past research on the AFGP attributes of several notothenioid species inhabiting ice-free sub-Antarctic environments have presented a complex picture. Furthermore, previous taxonomic studies split widely distributed notothenioids into different species and/or subspecies, with other studies disagreeing with these splits. To understand the response of the sub-Antarctic notothenioids to warmer, ice-free environments, it is necessary to have a good understanding of their antifreeze biology and systematics. Therefore, this study aimed to determine the association, if any, between the antifreeze attributes of sub-Antarctic notothenioid fishes and their taxonomic status. And more...

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Miller, John. "The classification and mapping of the Casuarina pauper woodlands of the Scotia 1:100 000 map." Thesis, Federation University Australia, 1998. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/164873.

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Hinneburg, Detlef, and Nicole Mölders. "A mesoscale atmospheric model combining meteorology, chemistry, biology, and heterogeneity." Wissenschaftliche Mitteilungen des Leipziger Instituts für Meteorologie ; 12 = Meteorologische Arbeiten aus Leipzig ; 4 (1999), S. 44-58, 1999. https://ul.qucosa.de/id/qucosa%3A15094.

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A mesoscale non-hydrostatic atmospheric model was extended by including both a chemical transport module (CTM) for the chemical triade NO, N02, and 0 3, and an explicit surface-subgrid module (ESSM) for a subscale resolution of the topographical surface. CTEM: The simulated time-dependent concentration fields result from the following processes involved: anthropogenic emission at different heights, biogenic emission, dry deposition on the receptive surface, chemical reactions, turbulent diffusion, and passive transport according to the model dynamics. The calculations in the lowest model layer, usually treated as a constant-flux layer, are now performed on a vertical subgrid that was inserted to better resolve the often observed high concentration gradients within the surface layer. ESSM: Moreover, an equidistant horizontal-subgrid is introduced for finer resolving the topography. The surface fluxes of momentum, sensible and latent heat, long-wave radiation, soil heat flux and wetness as well as the surf ace-energy balance are calculated in the usual approximations, however, employing the individual surface and soil properties of the subgrid cells. The averaged subgrid quantities serve as boundary values required for the model-grid calculations. Within the CTM the ESSM method leads to an intersection of the horizontal ESSM subgrid and the vertical CTM subgrid. Preliminary results representing an interim realization state of the ESSM demonstrate partially strong changes of the dry deposition rates caused by subgrid-resolved surface properties.
Ein mesoskaliges nicht-hydrostatisches Atmosphärenmodell ist um ein Chemie-TransportModul (CTM) zur Berücksichtigung der Triaden-Komponenten NO, N02 und 03 sowie um ein Verfahren zur verfeinerten Auflösung der topographischen Unterlage (explicit surface-subgrid modul ESSM) erweitert worden. CTM: Die simulierten zeitabhängigen Konzentrationsfelder sind das Resultat folgender modellierter Prozesse: Anthropogene Emission in verschiedenen Höhenschichten, biogene Emission, trockene Deposition (Rezeption), die speziellen chemischen Umwandlungen, turbulente Diffusion und passiver Transport. Da der Schwerpunkt der Prozesse und die höchsten Konzentrationsgradienten innerhalb der bodennahen ersten Modellschicht vorliegen, werden die Berechnungen in dieser Schicht auf einem verfeinerten vertikalen Untergitter durchgeführt. ESSM: Unabhängig von den Eigenheiten des CTM wird für alle untergrundbezogenen meteorologischen Größen ein regelmäßiges horizontales Untergitter zwecks Berücksichtigung des subskalig aufgelösten topographischen Untergrundes eingeführt. Auf diesem Untergitter werden in den bisherigen Näherungen alle Oberflächenflüsse für Impuls, fühlbare und latente Wärme, langwellige Strahlung, der Bodenwärmefluß, die Bodenfeuchte sowie die Energiebilanz am Boden berechnet. Die über die Untergitterzellen gemittelten Werte dienen den weiteren Berechnungen im normalen Modellgitter als die erforderlichen Randwerte. Innerhalb des CTM führt die ESSM-Methode zu einer Überlagerung des vertikalen CTM-Untergitters mit dem horizontalen Untergitter des ESSM. Erste Simulationsergebnisse, die dem derzeitigen Stand in der Realisierung des ESSM entsprechen, erbringen teilweise stark veränderte Depositionsraten infolge der Berücksichtigung der horizontal feiner aufgelösten Topographie.

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Attanayake, Mudiyanselage Achala Subhashinee Attanayake. "Systematics of Uvaria (Annonaceae) in Borneo and the reproductive biology of a Sri Lankan endemic, Uvaria semecarpifolia." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B45532047.

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Romagnoli, Dario. "Identification and development of epigenetic tumor biomarkers through computational biology approaches." Doctoral thesis, Università di Siena, 2023. https://hdl.handle.net/11365/1227695.

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DNA-methylation alterations are common in cancer and display unique characteristics that make them ideal markers for tumor quantification and classification. In this study, we discuss the development and testing of a computational framework exploiting minimal DNA-methylation signatures composed by a few dozen informative DNA-methylation sites to quantify and classify tumor signals in tissue and cell-free DNA samples. Extensive analyses of multiple independent and heterogenous datasets including >7,200 samples demonstrate the capability of the framework to provide precise estimations of tumor content and to enable accurate classification of tumor type and molecular subtype. To evaluate its applicability in the clinical context, we designed an informed assay incorporating the minimal signatures for breast cancer. Using both artificial samples and clinical serial cell-free DNA samples from patients with metastatic breast cancer, we show that our approach provides accurate estimations of tumor content, sensitive detection of tumor signal and the ability to capture clinically relevant molecular subtype in patients’ circulation. This study provides evidence that an extremely parsimonious approach can be used to develop cost-effective and highly-scalable DNA-methylation assays that could support and facilitate the implementation of precision oncology in clinical practice.

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Herber, Scott A. "Classification of Acropora cervicornis in Nearshore Waters of Fort Lauderdale, Florida." NSUWorks, 2001. http://nsuworks.nova.edu/occ_stuetd/305.

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Coastal waters in the Fort Lauderdale area of Florida host a series of relatively small colonial formations of the hermatypic coral Acropora cervicornis. Until recently, the extent and distribution of these colonies in nearshore marine waters was largely unknown. This study identified a number of occurrences of this scleractinian coral located between Hillsboro Inlet and Port Everglades Inlet, no further than 1.5 miles offshore. A diver was towed to locate the corals. A series of surveys were conducted and the results were used to classify the occurrences into different growth forms; thicket formations, isolated occurrences, and remnant colonies. Thicket formations were subsequently sub-divided into three groupings; small, medium, and large. The classification system is species and site specific for this study area. This system allows rapid assessment of colonies and provides a basis for long term monitoring of the progression and regression of A. cervicornis in the study area.

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Daoudi, Yannick. "An artificial neural network based prediction system for the classification of Golgi resident proteins /." Thesis, McGill University, 2003. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=78345.

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The Golgi apparatus of the cell is responsible for crucial mechanisms such as the intracellular transport of molecules, and the glycosylation process. It is linked to several serious and deadly diseases, including cancer. Understanding which proteins make up this organelle, and their associated functions, is essential to provide scientists with more insight into these related processes. The localization of Golgi resident proteins is a complex and not yet fully understood process. It has kept biologists using slow, manual, "wet lab" methods. Artificial neural networks have the capability of learning complex relationships from training data, and generalizing beyond these examples. Here, we present a neural network prediction system based on evolutionary information, which we extracted from the amino acid sequences in our data set. Our predictor proved to correctly classify, with a 90% success rate, whether a candidate sequence was coding for a protein located in the Golgi apparatus.

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Leroux, Nicole. "What are biological species? : the impact of the current debate in taxonomy on the species problem." Thesis, McGill University, 1993. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=69538.

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For the past twenty years, taxonomy has been in a state of turmoil. This confusion brings along with it four distinct schools of thought, each of which offers a different concept of biological species. The thesis will show that these concepts are purely operational and have only a weak theoretical force. In turn, it will be argued that a sound definition of species uses the notion of natural kinds, which is itself defined in term of non-causal nomological regularities.

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Fontaine, Jean-Fred. "Caractérisation et classification moléculaire des pathologies thyroïdiennes par approche transcriptomique." Phd thesis, Université d'Angers, 2007. http://tel.archives-ouvertes.fr/tel-00346443.

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L'accident de Tchernobyl, en 1986, a mis en lumière le cancer de la thyroïde. Ce cancer, assez rare, est pourtant en forte augmentation, et cela avant même 1986. Le diagnostic des tumeurs folliculaires thyroïdiennes par analyses anatomopathologiques est parfois difficile. Ce travail s'intéresse à la classification moléculaire de ces tumeurs ainsi qu'à la recherche de marqueurs spécifiques à chaque pathologie. En regroupant et en analysant le transcriptome de plus de 90% des types de lésions folliculaires de la thyroïde, nous avons établi une classification moléculaire globale de ces lésions, nous avons défini des marqueurs spécifiques faisant l'objet d'un brevet, et nous avons permis de préciser le diagnostic de la majorité des tumeurs de malignité incertaine. L'étude bioinformatique des données issues de biopuces apporte des précisions à la classification internationale des tumeurs, particulièrement pour les tumeurs oncocytaires, microfolliculaires et de malignité incertaine.

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Slocum, Kevin R. "Coastal zone landscape classification using remote sensing and model development." W&M ScholarWorks, 2002. https://scholarworks.wm.edu/etd/1539616857.

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Coastal zone landscape characterization and empirical model development were evaluated using multi-spectral airborne imagery. Collectively, four projects are described that address monitoring and classification issues common to the resource management community. Chapter 1 discusses opportunities for remote sensing. Chapter 2 examines spectral and spatial image resolution requirements, as well as training sample selection methods required for accurate landscape classification. Classification accuracy derived from 25nm imagery with 4m pixel sizes outperformed 70nm imagery with 1m pixel sizes. Eight natural and five cultural landscape features were tested for classification accuracy. Chapter 3 investigated the ability to characterize 1m multispectral imagery into rank-ordered categorical biomass index classes of Phragmites australis. Statistical clustering and sample membership was based upon normalized field-measurements. The red imagery channel showed highly significant correlation with field measurements (p = 0.00) and explained much of its variability (r2 = 0.79). Addition of near-infra red, green, and blue image channels in a forward stepwise regression improved the coefficient of determination (r2 = 0.98). In Chapter 4, a landscape cover map was revised by incorporating expert knowledge into a simple spatial model. Examples are provided for a barrier island environment to illustrate this post-classification methodology. A prototype selection of expert rules was sufficient to change more than 20 per cent of the originally classified landscape pixels. Chapter 5 discusses the development of an empirical model that uses vegetation community classes to estimate: (a) soil type, (b) soil compaction rate, and (c) elevation. Vegetation class proved itself a reliable surrogate for estimating these variables based upon field-based statistical measures of association and significance tests. Vegetation was highly associated with four soil types (Cramer's V = 0.98) and soil compaction rates values at depths of 30 and 46cm (Cramer's V > 0.85), and was able to accurately estimate three decimeter-level elevation zones (r2 = 0.86, p = 0.00). A preliminary model to estimate transverse dune crest heights and locations under forest canopy was presented. Lastly, Chapter 6 offers a summary and concluding statements advocating continued use of remote sensing as an application tool for resource management needs.

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Moon, Mike. "Hydroacoustic Substrate Classification Accuracy and Faunal Assemblage Variation Between Artificial and Natural Rock Regions: Bear Lake, Utah/Idaho." DigitalCommons@USU, 2007. https://digitalcommons.usu.edu/etd/7682.

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Research designed to elucidate artificial reef efficacy in attraction and production is lacking. Delineation of the rock reef habitat, coupled with faunal patterns of substrate use within artificial and natural reef regions, will allow elucidation of the potential of artificial reefs to attract sport fishes, and function as surrogate natural habitat for the conservation of endemic fish species. We compared faunal assemblages and habitat complexity between artificial and natural reefs to access the efficacy of artificial reefs in conservation of the native community, and attraction of sport fishes. We used hydroacoustics to map artificial and natural rock reefs within Bear Lake. We compared the accuracy of Visual Bottom Typer (VBT, BioSonics, Seattle, WA) software to observed substrate in three regions of varying slope and rock complexity within Bear Lake. VBT demonstrated an ability to distinguish substrates regardless of rock complexity and slope, although inaccuracies were present. VBT biased classification towards predominant substrate in the survey regions. We compared benthic invertebrate and fish catch in natural and artificial reef regions to assess the utility of artificial reefs in fisheries management. We assessed the potential of artificial reefs to function as foraging habitat for endemic fishes within Bear Lake. We compared benthic invertebrate taxa abundances and diversity between one region of artificial reefs, and two natural reefs in spring and summer. The artificial reefs hosted prey consumed by endemic Bonneville whitefish and Bear Lake sculpin. We assessed the potential of artificial reefs to function in attraction of sport fishes, and conservation of endemic fishes. We compared differences in fish catch per unit effort (CPUE) and diversity on rock and soft substrate between one artificial and two natural reef regions. Sport fishes attraction to the artificial reefs was minimal. Winter cisco and whitefish used the artificial reefs similarly to natural reefs. Fall lake trout, crayfish, and yellow perch used artificial and natural reefs dissimilarly.

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Doolittle, Daniel Foster. "Automated Fish Species Classification using Artificial Neural Networks and Autonomous Underwater Vehicles." W&M ScholarWorks, 2003. https://scholarworks.wm.edu/etd/1539617813.

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Hatem, Iyad. "Hybrid multivariate classification technique and its application in tissue image analysis /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3091929.

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Liu, Xinan. "NOVEL COMPUTATIONAL METHODS FOR SEQUENCING DATA ANALYSIS: MAPPING, QUERY, AND CLASSIFICATION." UKnowledge, 2018. https://uknowledge.uky.edu/cs_etds/63.

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Over the past decade, the evolution of next-generation sequencing technology has considerably advanced the genomics research. As a consequence, fast and accurate computational methods are needed for analyzing the large data in different applications. The research presented in this dissertation focuses on three areas: RNA-seq read mapping, large-scale data query, and metagenomics sequence classification. A critical step of RNA-seq data analysis is to map the RNA-seq reads onto a reference genome. This dissertation presents a novel splice alignment tool, MapSplice3. It achieves high read alignment and base mapping yields and is able to detect splice junctions, gene fusions, and circular RNAs comprehensively at the same time. Based on MapSplice3, we further extend a novel lightweight approach called iMapSplice that enables personalized mRNA transcriptional profiling. As huge amount of RNA-seq has been shared through public datasets, it provides invaluable resources for researchers to test hypotheses by reusing existing datasets. To meet the needs of efficiently querying large-scale sequencing data, a novel method, called SeqOthello, has been developed. It is able to efficiently query sequence k-mers against large-scale datasets and finally determines the existence of the given sequence. Metagenomics studies often generate tens of millions of reads to capture the presence of microbial organisms. Thus efficient and accurate algorithms are in high demand. In this dissertation, we introduce MetaOthello, a probabilistic hashing classifier for metagenomic sequences. It supports efficient query of a taxon using its k-mer signatures.

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Clark, Shawn Meredith. "A revision of the section Scelidites in the Western Hemisphere (Coleoptera: Chrysomelidae) /." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487584612163441.

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Rödder, Silke. "A molecular biology based approach for the classification and characterization of human renal allograft pathologies based on Metzincin deregulation." [S.l.] : [s.n.], 2009. http://www.zb.unibe.ch/download/eldiss/09roedder_s.pdf.

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Mayor, Charlie. "The classification of gene products in the molecular biology domain : realism, objectivity, and the limitations of the Gene Ontology." Thesis, City University London, 2012. http://openaccess.city.ac.uk/3006/.

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Background: Controlled vocabularies in the molecular biology domain exist to facilitate data integration across database resources. One such tool is the Gene Ontology (GO), a classification designed to act as a universal index for gene products from any species. The Gene Ontology is used extensively in annotating gene products and analysing gene expression data, yet very little research exists from a library and information science perspective exploring the design principles, philosophy and social role of ontologies in biology. Aim: To explore how molecular biologists, in creating the Gene Ontology, devised guidelines and rules for determining which scientific concepts are included in the ontology, and the criteria for how these concepts are represented. Methods: A domain analysis approach was used to devise a mixed methodology to study the design of the Gene Ontology. Concept analysis of a GO term and a critical discourse analysis of GO developer mailing list texts were used to test whether ontological realism is a tenable basis for constructing objective ontologies. A comparison of the current GO vocabulary construction guidelines and a study of the reasons why GO terms are removed from the ontology further explored the justifications for the design of the Gene Ontology. Finally, a content analysis of published GO papers examined how authors use and cite GO data and terminology. Results: Gene Ontology terms can be presented according to different epistemologies for concepts, indicating that ontological realism is not the only way objective ontologies can be designed. Social roles and the exercise of power were found to play an important role in determining ontology content, and poor synonym control, a lack of clear warrant for deciding terminology and arbitrary decisions to delete and invent new terms undermine the objectivity and universal applicability of the Gene Ontology. Authors exhibited poor compliance with GO data citation policies, and in re-wording and misquoting GO terminology, risk exacerbating the semantic problems this controlled vocabulary was designed to solve. Conclusions: The failure of the Gene Ontology to define what is meant by a molecular function, the exercise of power by GO developers in clearing contentious concepts from the ontology, and the strict adherence to ontological realism, which marginalises social and subjective ways of classifying scientific concepts, limits the utility of the ontology as a tool to unify the molecular biology domain. These limitations to the Gene Ontology design could be overcome with the development of lighter, pluralistic, user-controlled ‘open ontologies’ for gene products that can work alongside more traditional, ‘top-down’ developed vocabularies.

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Dissertations / Theses on the topic 'Biology Classification'

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