Having a linear representation of magnitude across scales is essential in understanding many scientific concepts (Tretter, et al., 2006a) and is predictive of a range of mathematical achievement tests (Siegler & Booth, 2004). Despite the importance of understanding magnitude and scale, people have substantial difficulty comparing magnitudes outside of human perception (e.g., Jones, et al., 2008). The present work aims to examine the way people learn to represent and reason about large magnitudes through the development of two science of learning activities based on hierarchical alignment activity and corrective feedback. The hierarchical alignment activity utilizes several analogical reasoning principles: hierarchical alignment, progressive alignment, structural alignment, and multiple opportunities to make analogies. Study 1 examines the effectiveness of hierarchical alignment by contrasting it with a conventional activity that uses all the analogical reasoning principles described above except for hierarchical alignment. Study 2 examines a corrective feedback activity, based on the same analogical reasoning principles used in study 1, except, using corrective feedback instead of progressive alignment and hierarchical alignment. Thus, study 2 examines the necessity of hierarchical and progressive alignment. That both activities were successful in developing linear representations of geologic time (and for study 1, astronomical distances), suggests that multiple opportunities to make analogies through structural alignment are key components in developing analogies for learning magnitude. There appears to be an additive benefit of including hierarchical alignment (i.e., practice aligning magnitude relations across scales) in analogies for learning about magnitudes. Corrective feedback may also be a useful strategy in learning about scale information. Pedagogical implications are discussed. Both activities were based on the hypothesis that magnitudes at scales outside human perception are represented and reasoned about in the same way as magnitudes at human scales. The Category Adjustment Model (Huttenlocher, et al., 1988) suggests magnitude at human scales is stored as a hierarchical combination of metric and categorical information. People may use category boundaries to help make estimations in lieu of precise metric information. Variation in estimation, therefore, occurs because of imprecision of category boundaries (Shipley & Zacks, 2008; Zacks & Tversky, 2001). The current studies provided salient category boundaries to develop a more linear representation of magnitude. Thus, the effectiveness of the hierarchical alignment activity and the corrective feedback activity supports the hypothesis that people use hierarchically organized categorical information when making estimations across scales and across dimensions; and that providing people with more salient category boundary information improves estimation. Similarities and differences among temporal, spatial, and abstract line estimations are identified. Theoretical implications, including the potential application of the Category Adjustment Model to mental number lines, are discussed. / Psychology

This study is an investigation of (dis)alignment and (dis)affiliation in narrative conversations in English. The analytical focus is on the teller's approaches for eliciting an assessment from the recipient, and the recipient's questioning behaviors to request further information. Conversation analysis (CA) is employed to analyze and interpret data from fourteen naturally occurring, mundane conversations between American and Japanese participants. Three conversations were audio-taped only, and eleven were both audio- and video-taped. All recorded conversations were transcribed using CA conventions. The analysis of the data revealed the teller's approaches for eliciting an assessment from the recipient, with repetitions being most frequently observed. Gazing, nodding, and using gestures, and multiple approaches including elaborating on the story, repeating a point, and emphasizing important words in a louder voice, were also observed. The analysis also revealed that minimal responses from the recipient such as "I see" did not necessarily indicate the recipient's understanding of the story. The recipient's assessments and comments functioned as a barometer of the degree of understanding. Several types of recipient questioning behaviors were identified, including initiating repair, requesting background information, prompting further story, expressing disagreement, and assisting the teller to continue the story. These questions indicated the degree to which the recipient had understood the story, encouraged the teller to proceed with the story, satisfied the recipient's personal curiosity, showed the recipient's interest and involvement in the story, challenged the teller's interpretation of the story, and assisted the teller when in trouble. Whereas questions sometimes caused temporal derailment, they could also contribute to enhancing alignment and affiliation between the participants. Whether or not a particular question was an indication of (dis)alignment or (dis)affiliation depended on which aspect of the story the teller and the recipient focused on. Although the smooth flow of narratives might be preferable, in naturally occurring mundane conversations, the recipient sometimes needs to intervene in the teller's talk. What seems important in communication is to attain shared understanding in the end, even if the intervention delays the development of the narrative. / CITE/Language Arts

Background: Lower limb amputees face many challenges, and most of them prefer to use prosthetics for daily tasks and activities. The prosthesis is usually a combination of connected prosthetic components, and their spatial orientation is called the prosthetic alignment. Proper alignment is essential, as it substantially affects the quality and comfort of a prosthesis.   Objective: The aim of this study was to create a method that could accurately and effectively quantify the alignment of a transtibial and transfemoral prostheses using Vicon optical motion capture system.   Methods: Two experimental series were conducted. The first one was to test the repeatability of the measurement. Three analysts placed retroreflective markers on the prostheses three times, and five measurements were recorded each time. Alignment parameters were calculated in Vicon ProCalc for each measurement, and a standard error of measurement was found for each alignment parameter. The standard error of measurement was calculated from three variance components, between-analyst, within-analyst, and between-trial variability. The second experimental series was conducted to understand the relationship between alignment adjustments and the outcome parameters. The socket height, internal rotation, flexion, adduction, and translation were modified and measured. The socket translation was calculated in three coordinate systems to study how they affect the outcome.   Results: For the first experimental series, the standard error of measurement for every alignment parameter was below 3° and 6 mm. The between-analyst variability was the most prominent, and the parameters calculated in the sagittal plane were more reliable than those calculated in the frontal and transverse plane. In the second experimental series, there was a linear relationship between the modifications and the measured outcome. When a connection between two prosthetic components was changed by turning the screws one round, the average change in angle between them was 2°, and the average translation change was 4.4 mm. Of the three coordinate systems, the translation calculated in ankle coordinates was more reliable than in global coordinates and describe the translation more effectively than in socket coordinates.   Conclusion: The reliability of the measurements was considered good. The standard error of measurement was low, and the main variability resulted from differences in marker placement between the analysts. The results from the measured alignment changes were as expected. All the parameters could be effectively interpreted, and the ankle coordinates were considered advantageous in describing the socket translation.

Real-time face recognition has recently become available for the government and industry due to developments in face recognition algorithms, human head detection algorithms, and faster/low cost computers. Despite these advances, however, there are still some critical issues that affect the performance of real-time face recognition software. This paper addresses the problem of off-centered and out-of-pose faces in pictures, particularly in regard to the eigenface method for face recognition. We first demonstrate how the representation of faces by the eigenface method, and ultimately the performance of the software depend on the location of the eyes in the pictures. The eigenface method for face recognition is described: specifically, the creation of a face basis using the singular value decomposition, the reduction of dimension, and the unique representation of faces in the basis. Two different approaches for aligning the eyes in images are presented. The first considers the rotation of images using the orthogonal Procrustes Problem. The second approach looks at locating features in images using energy-minimizing active contours. We then conclude with a simple and fast algorithm for locating faces in images. Future research is also discussed. / Master of Science

[EN] EHealth plays an essential role in supporting healthcare in today's digital society; it is perceived as crucial for high quality and cost-effective healthcare. However, getting the expected benefits from eHealth has been difficult to demonstrate. There has been a raising interest in adopting eHealth Governance frameworks to obtain re-assurance that investments return the expected results in health care. How IT Governance is implemented within healthcare, the actual impact on strategic alignment and its influence to the information society progress, remains poorly understood. For this purpose we have explored the application of these frameworks within the National Health Service in Scotland and their impact on the following three aspects: eHealth Governance maturity, strategic alignment with healthcare and local progress of digital societies. This research is a longitudinal study (2008-2013), involving an exploratory and explanatory multi-case analysis of three representative organisations across Scotland. A combination of empiric methods has been used: semi-structured interviews with implementers, surveys (Strategic Alignment Model), cross-sectoral/national benchmarking based on a literature review and a qualitative analysis of established eHealth progress indicators. Ninety-two participants have been involved across three case studies. The outcomes of this study have been published over a period of 5 years representing a composite thesis based on relevant publications. Results sustain that EHealth Governance is in its infancy across sectors and countries. 80% of the organisations worldwide are in a transition point between a "committed" and an "established" process. Our results support that the more mature eHealth Governance is, the better the strategic alignment between eHealth and health care organisations (HCOs), hence the better progress of eHealth and the Digital Society. The Strategic alignment is slowly maturing across organisations (15% since 2008), indicating a faster development than the overall Digital Society (Scotland) progress indicators. The National eHealth Strategy shows signs of steady progress and very positive eHealth uptake in society with an overall growth of 12% since 2008, despite the deep economical recession within the period of this research. The conclusions of this study as a longitudinal analysis are limited and more research over the forthcoming years is required. For this purpose, a simplified and adapted method to monitor these trends in future HCOs research has also been provided. / [ES] La eSalud juega un papel esencial en el desarrollo de la asistencia médica en sociedades digitales; se percibe como un elemento crucial en la provisión de servicios médico-sanitarios alta calidad y costo-efectivos. A pesar de ello, hasta ahora ha sido difícil demostrar la materialización de los beneficios esperados de la eSalud, pero hay un interés creciente en la adopción de marcos de referencia basados en buenas prácticas, y estándares profesionales internacionales para la gestión y dirección de la eSalud, con el propósito de asegurar que las inversiones revierten los resultados esperados en el cuidado y servicios de la salud. Hasta ahora se sabe muy poco sobre el fenómeno de cómo la eSalud es integrada en el cuidado y servicios de la salud, y del impacto que esta tiene en la alineación estratégica de la eSalud. Igualmente, sabemos muy poco de la influencia real que estas prácticas tienen en el progreso de sociedades digitales. Este estudio se centra en explorar la aplicación de buenas practicas y estándares internacionales como marco de referencia en el gobierno de la eSalud en el servicio de salud Escocés; también contrastamos y comparamos el fenómeno con otros países y sectores. Esta investigación es un estudio longitudinal (2008-2013) que incorpora un análisis exploratorio y explicativo de casos. Se obtuvieron un total de noventa y dos participantes a lo largo de los tres casos estudiados, con representación de los principales grupos de interés (médicos y no médicos). Los resultados se han divulgado a lo largo del periodo de investigación en un compendio de publicaciones relevantes que conforman la tesis. Los principales hallazgos muestran que el gobierno de la eSalud está en su infancia en los sectores y países analizados: el 80% de las organizaciones a nivel mundial presentan este proceso en un punto de transición entre "comprometido" y "establecido" (Modelo SAM). Los resultados corroboran que cuanto más maduro es el gobierno de la eSalud, mayor alineación estratégica entre la eSalud y la organización, y mayor progreso de la variable eSalud en los indicadores de la sociedad de la información. La alineación estratégica esta madurando lentamente (15% desde 2008), sin embargo este crecimiento es mas rápido que el progreso observado en los indicadores de la sociedad digital (Escocia). La estrategia nacional Escocesa muestra signos de progreso sostenido y de integración (por uso o adopción) de las iniciativas de eSalud en la sociedad (crecimiento del 12% desde 2008), a pesar de la profunda depresión económica durante el periodo de investigación. Las conclusiones de esta investigación, como estudio longitudinal, son limitadas y requieren la captura de más datos y observaciones durante los próximos anos. Con el fin de facilitar este proceso, se ha propuesto un método simplificado y adaptado al sector salud, que permite capturar observaciones, comparar y monitorizar estas tendencias en futuras investigaciones en el sector salud. / [CA] La eSalut juga un paper essencial en el suport a l'assistència sanitària a la societat digital de hui en dia; es percep com crucial per a l'alta qualitat i efectivitat del servicis de salut. No obstant això, ha estat difícil de demostrar la obtenció dels beneficis esperats de la eSalut. Hi ha hagut un interès en augmentar l'adopció de marcs de governança de la eSalut per obtenir re-assegurament que les inversions retornen els resultats esperats en els servicis sanitaris. Com s'implementa la governança de les TIC dins de l'assistència sanitària, l'impacte real en l'alineació estratègica i la seua influència en el progrés de la societat de la informació, continua sent poc conegut. Aquest estudi explora l'aplicació d'aquests estàndards i marcs de referència dins dels Serveis Nacionals de Salut d'Escòcia i el seu impacte en els tres aspectes següents: la maduresa de la governança de la eSalut", l'alineació estratègica amb l'assistència sanitària i, finalment, el progrés local de les societats digitals. Aquesta investigació és un estudi longitudinal (2008-2013), que implica una anàlisi multi cas exploratori i explicatiu de tres organitzacions representatives del servici nacional de salut de Escòcia. S'ha utilitzat una combinació de mètodes empírics: entrevistes semi estructurades, enquestes (Model SAM) comparatives de mercat intersectorial i internacional basat en una revisió bibliogràfica i, finalment, una anàlisi qualitativa dels indicadors de progrés eSalut. Noranta dos participants han informat a través de tres estudis de casos. Els resultats s'han divulgat al llarg del període d'investigació en un compendi de publicacions rellevants que conformen la tesi. Els resultats assenyalen que la governança de la eSalut està en la seua infància en tots els sectors i països. 80% de les organitzacions de tot el món es troben en un punt de transició entre un procés "compromès" i "establint". Els nostres resultats apunten que quan més madur es la governança de la eSalut, millor serà l'alineació estratègica entre la eSalut i les organitzacions d'atenció sanitària (HCOs), per tant el millor progrés de la sanitat electrònica a la Societat Digital. L'alineació estratègica està madurant lentament en les organitzacions (15% des de 2008); aquest desenvolupament és més ràpid que el progrés de la societat digital (Escòcia). L'estratègia Nacional de eSalut mostra signes de progrés constant i l'absorció de la eSalut en la societat es prou positiva, amb un creixement global del 12% des de l'any 2008, tot i la profunda recessió econòmica durant el període de temps d'aquesta investigació. Les conclusions d'aquest estudi com una anàlisi longitudinal són limitades i es requereix més investigació en els propers anys. / Beratarbide Sobrado, ME. (2016). Longitudinal analysis of eHealth Governance within healthcare organizations as a critical factor in the adaptation to the Information Society in Scotland [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/63456

The advent of multi-photon microscopes and highly sensitive protein sensors enables the recording of astrocyte activities on a large population of cells over a long-time period in vivo. Existing tools cannot fully characterize these activities, both within single cells and at the population-level, because of the insufficiency of current region-of-interest-based approaches to describe the activity that is often spatially unfixed, size-varying, and propagative. Here, we present Astrocyte Quantitative Analysis (AQuA), an analytical framework that releases astrocyte biologists from the ROI-based paradigm. The framework takes an event-based perspective to model and accurately quantify the complex activity in astrocyte imaging datasets, with an event defined jointly by its spatial occupancy and temporal dynamics. To model the signal propagation in astrocyte, we developed graphical time warping (GTW) to align curves with graph-structured constraints and integrated it into AQuA. To make AQuA easy to use, we designed a comprehensive software package. The software implements the detection pipeline in an intuitive step by step GUI with visual feedback. The software also supports proof-reading and the incorporation of morphology information. With synthetic data, we showed AQuA performed much better in accuracy compared with existing methods developed for astrocytic data and neuronal data. We applied AQuA to a range of ex vivo and in vivo imaging datasets. Since AQuA is data-driven and based on machine learning principles, it can be applied across model organisms, fluorescent indicators, experimental modes, and imaging resolutions and speeds, enabling researchers to elucidate fundamental astrocyte physiology. / Doctor of Philosophy / Astrocyte is an important type of glial cell in the brain. Unlike neurons, astrocyte cannot be electrically excited. However, the concentrations of many different molecules inside and near astrocytes change over space and time and show complex patterns. Recording, analyzing, and deciphering these activity patterns enables the understanding of various roles astrocyte may play in the nervous system. Many of these important roles, such as sensory-motor integration and brain state modulation, were traditionally considered the territory of neurons, but recently found to be related to astrocytes. These activities can be monitored in the intracellular and extracellular spaces in either brain slices and living animals, thanks to the advancement of microscopes and genetically encoded fluorescent sensors. However, sophisticated analytical tools lag far behind the impressive capability of generating the data. The major reason is that existing tools are all based on the region-of-interest-based (ROI) approach. This approach assumes the field of view can be segmented to many regions, and all pixels in the region should be active together. In neuronal activity analysis, all pixels in an ROI (region of interest) correspond to a neuron and are assumed to share a common activity pattern (curve). This is not true for astrocyte activity data because astrocyte activities are spatially unfixed, size-varying, and propagative. In this dissertation, we developed a framework called AQuA to detect the activities directly. We designed an accurate and flexible detection pipeline that works with different types of astrocyte activity data sets. We designed a machine learning model to characterize the signal propagation for the pipeline. We also implemented a compressive and user-friendly software package. The advantage of AQuA is confirmed in both simulation studies and three different types of real data sets.

Oxide dielectric breakdown is an old problem that has been studied over decades. It causes power dissipations and irreversible damage to the electronic devices. The aggressive downscaling of the device size exponentially increases the leakage current density, which also raises the risk of dielectric breakdown. It has been proposed that point defects, current leakages, impurity diffusions, etc. all contribute to the change of oxide chemical composition and ultimately lead to the dielectric breakdown. However, the conclusive cause and a clear understanding of the entire process of dielectric breakdown are still under debate. In this research, the electronic structure at metal/oxide interfaces is studied using first-principle calculations within the framework of Density Functional Theory (DFT) to investigate any possible key signature that would trigger the dielectric breakdown. A classical band alignment method, the Van de Walle method, is applied to the case study of the Al/crystal-SiO2 (Al/c-SiO2) interface. Point defects, such as oxygen vacancy (VO) and hydrogen impurity (IH), are introduced into the Al/c-SiO2 interface to study the effects on band offset and electronic structure caused by point defects at metal/oxide interfaces. It is shown that the bonding chemistry at metal/oxide interfaces, which is mainly ionic bond, polarizes the interface. It results in many interface effects such as the interface dipole, built-in voltage, band bending, etc. Charge density analysis also indicates that the interface can localize charge due to such ionic bonding. It is also found that VO at the interface traps metal electrons which closes the open -sp3 orbital. The analysis on local potential shows that the metal potential penetrates through a few layers of oxide starting from the interface, which metalizes the interfacial region and induces unoccupied states in the oxide band gap. In addition, it is shown that higher oxygen content at metal/oxide interfaces minimizes such metal potential invasion. In addition, an oxygen vacancy is created at multiple sites through the Al/c-SiO2 and Al/a-SiO2 interface systems, separately. The oxygen local pressure is also calculated before its removal using Quantum Stress Density theory. Correlations among electronic structure, stress density, and vacancy formation energy are found, which provide informative insights into the defect generation controlling and dielectric breakdown analysis. A new band alignment approach based on the projection of plane-waves (PWs) into the space-dependent atomic orbital (LCAO) basis is presented and tested against classical band offset methods -- the Van de Walle method. It is found that the new band alignment approach can provide a quantitative and reliable band alignment and can be applied to the heterojunctions consisting of amorphous materials. The new band alignment approach reveals the real-space dependency of the electronic structure at interfaces. In addition, it includes all interface effects, such as the interface dipole, built-in voltage, virtual oxide thinning, and band deformation, which cannot be derived using classical band offset methods. This new band alignment approach is applied to the case study of both the Al/amorphous-SiO2 (Al/a-SiO2) interface and the Al/c-SiO2. We have found that at extremely low dimensions, the reduction of the insulator character due to the virtual oxide thinning is a pure quantum effect. I highlight that the quantum tunneling current leakage is more critical than the decrease of the potential barrier height on the failure of the devices. / PHD / Metal/oxide interfaces have many applications in electronic devices such as Field Effect Transistors (FETs), resistive/dynamic Random-Access Memory (RAM) devices, Tunnel Junctions (TJs), Metal Oxide Semiconductor (MOS) devices, or Back-End-of-Line (BEOL) on integrate-circuits. The downscaling of devices dimension is still following the Moore’s Law. However, it brings several reliability challenges, such as the electric current leakage that is significant for ultrathin oxide films (< 5 nm). At low dimensionality, the stress induced leakage currents (SILC) caused by quantum effects exponentially increases. These electric conductions harm devices and constantly degrade insulating materials, until the degradation reaches a critical level called dielectric breakdown that ultimately leads to the electronic failure of the materials. The insulating/conducting transition is a complex and irreversible very well-known process. Experimentally, the observation of sudden electric current increase is a typical sign of the breakdown. Many experimental works in past decades suggest that point defects are very important to the initiation of dielectric breakdown, however they cannot be the only cause. Many other factors such as the electric voltage, material imperfection, mechanical stress, humidity, and temperature are also critical to the final breakdown. Therefore, a comprehensive and theoretical study is necessary to better understand the mechanisms behind the dielectric breakdown. It benefits the semiconductor industry for inventing new materials and exploring advanced techniques to prevent the occurrence of dielectric breakdown. In this dissertation, a set of theoretical case studies using the aluminum (Al) and silica (SiO₂) to explore correlations among different electronic, thermodynamic, and mechanical properties have been performed. This study reveals that all these material properties are intrinsically correlated and allow a clear understanding of the dielectric breakdown.

The need for research instruments adaptable to culturally diverse populations has grown with globalization and digital connectivity. Ensuring measurement invariance (MI) is crucial for generating accurate and comparable scores, especially in comparative studies. Traditional approaches like Multi-Group Confirmatory Factor Analysis (MG-CFA) often involve intricate procedures and can become unwieldy when adjustments for partial invariance are needed. The Alignment-within-CFA (AwC) method emerged as a promising alternative, designed to approximate group-specific factors and produce latent variables with uniform metrics. This study rigorously compares the AwC method and traditional MG-CFA across moderate numbers of groups (3, 4, and 5) under various conditions of noninvariance and sample sizes. By employing Monte Carlo simulations, the study controls study variables and explores a wide range of hypothetical scenarios, enhancing the precision and reliability of MI testing. The findings indicate that the AwC method is similar to or superior to the step-wise partial invariance approach, offering accurate and consistent results in varied scenarios. Specifically, the study examines the conditions under which AwC outperforms traditional MG-CFA and investigates the impact of factors such as different types of invariance, number of groups, and sample size on bias and model fit. This research provides deeper insights into the strengths and limitations of each method, guiding researchers in selecting the most appropriate approach for their specific contexts. The results support the use of the AwC method in scenarios where minimizing bias and error in parameter estimates is critical, paving the way for more streamlined and effective research amidst increasing global diversity.

Much research has been directed toward understanding the roles of essential components in the cell, such as proteins, microRNAs, and genes. This dissertation focuses on two interesting problems in bioinformatics research: microRNA-target prediction and the identification of conserved protein complexes across species. We define the two problems and develop novel approaches for solving them. MicroRNAs are short non-coding RNAs that mediate gene expression. The goal is to predict microRNA targets. Existing methods rely on sequence features to predict targets. These features are neither sufficient nor necessary to identify functional target sites and ignore the cellular conditions in which microRNA and mRNA interact. We developed MicroTarget to predict microRNA-mRNA interactions using heterogeneous data sources. MicroTarget uses expression data to learn candidate target set for each microRNA. Then, sequence data is used to provide evidence of direct interactions and ranking the predicted targets. The predicted targets overlap with many of the experimentally validated ones. The results indicate that using expression data helps in predicting microRNA targets accurately. Protein complexes conserved across species specify processes that are core to cell machinery. Methods that have been devised to identify conserved complexes are severely limited by noise in PPI data. Behind PPIs, there are domains interacting physically to perform the necessary functions. Therefore, employing domains and domain interactions gives a better view of the protein interactions and functions. We developed novel strategy for local network alignment, DONA. DONA maps proteins into their domains and uses DDIs to improve the network alignment. We developed novel strategy for constructing an alignment graph and then uses this graph to discover the conserved sub-networks. DONA shows better performance in terms of the overlap with known protein complexes with higher precision and recall rates than existing methods. The result shows better semantic similarity computed with respect to both the biological process and the molecular function of the aligned sub-networks. / Ph. D. / Much research has been directed toward understanding the roles of essential components in the cell, such as proteins, microRNAs, and genes. The processes within the cell include a mixture of small molecules. It is of great interest to utilize different information sources to discover the interactions among these molecules. This dissertation focuses on two interesting problems: microRNA-target prediction and the identification of conserved protein complexes across species. We define the two problems and develop novel approaches for solving them. MicroRNAs are a recently discovered class of non-coding RNAs. They play key roles in the regulation of gene expression of as much as 30% of all mammalian protein encoding genes. MicroRNAs regulation activity has been implicated in a number of diseases including cancer, heart disease and neurological diseases. We developed MicroTarget to predict microRNAgene interactions using heterogeneous data sources. The predicted target genes overlap with many of the experimentally validated ones. Proteins carry out their tasks in the cell by interacting with each other. Protein complexes conserved among species specify the cell core processes. We identify conserved complexes by constructing an alignment graph leveraging on the conservation of PPIs between species through domain conservation and domain-domain interactions (DDI) in addition to PPI networks. Better integration of domain conservation and interactions in our developed conserved protein complexes identification system helps biologists benefit from verified data to predict more reliable similarity relationships among species. All the test data sets and source code for this dissertation are available at: https://bioinformatics.cs.vt.edu/∼htorkey/Software.

Residue coupling in protein families has received much attention as an important indicator toward predicting protein structures and revealing functional insight into proteins. Existing coupling methods identify largely pairwise couplings and express couplings over amino acid combinations, which do not yield a mechanistic explanation. Most of these methods primarily use a multiple protein sequence alignment---most likely a resultant alignment---which better exposes couplings and is obtained through manual tweaking of an alignment constructed by a classical alignment algorithm. Classical alignment algorithms primarily focus on capturing conservations and may not fully unveil couplings in the alignment. In this dissertation, we propose methods for capturing both pairwise and higher-order couplings in protein families. Our methods provide mechanistic explanations for couplings using physicochemical properties of amino acids and discernibility between orders. We also investigate a method for mining frequent episodes---called coupled patterns---in an alignment produced by a classical algorithm for proteins and for exploiting the coupled patterns for improving the alignment quality in terms of exposition of couplings. We demonstrate the effectiveness of our proposed methods on a large collection of sequence datasets for protein families. / Ph. D. / Proteins are biomolecules that comprise amino acid compounds. A chain of amino acid (a.k.a. protein sequence) forms the primary structure of a protein, and the shaping of this chain into various folds gives rise to a more complex 3D structure, a natural state of proteins. It is through structures protein performs various activities. To preserve these activities in proteins, evolution allows only those changes in protein sequences that do not disrupt the overall structures and functions of proteins. Coupling is a evolutionary phenomenon that helps proteins preserve their structures and functions. Two or more amino acid positions are coupled if changes of amino acids at a position is compensated by changes in the other position(s). In this thesis, we propose a set of probabilistic methods for modeling such couplings between two or more positions. Our methods identify the most probable couplings in a set of protein sequences and express them with probabilistic graphical models (a powerful and interpretable framework), which can be used for answering questions related to protein structures, functions, and protein synthesis. Using this notion of coupling, we also develop a method for improving the quality of multiple protein sequence alignment, a widely used tool for protein sequence analyses. We evaluate our methods with a large collection of sequence datasets for protein families, and the results substantiate the efficacy of our methods.