In order to fully examine the application of association analysis to medical data for the purpose of deriving medical diagnoses, we survey classical association analysis and approaches, the current challenges faced by medical association analysis and proposed solutions, and finally culminate this knowledge in a proposition for the application of medical association analysis to the identification of food intolerance. The field of classical association analysis has been well studied since its introduction in the seminal paper on market basket research in the 1990's. While the theory itself is relatively simple, the brute force approach is prohibitively expensive and thus, creative approaches utilizing various data structures and strategies must be explored for efficiency. Medical association analysis is a burgeoning field with various focuses, including diagnosis systems and gene analysis. There are a number of challenges faced in the field, primarily stemming from characteristics of analysis of complex, voluminous and high dimensional medical data. We examine the challenges faced in the pre-processing, analysis and post-processing phases, and corresponding solutions. Additionally, we survey proposed measures for ensuring the results of medical association analysis will hold up to medical diagnosis standards. Finally, we explore how medical association analysis can be utilized to identify food intolerances. The proposed analysis system is based upon a current method of diagnosis used by medical professionals, and seeks to eliminate manual analysis, while more efficiently and intelligently identifying interesting, and less obvious patterns between patients' food consumption and symptoms to propose a food intolerance diagnosis.

Abstract Knowledge map, like the ¡§Yellow Pages¡¨ of knowledge, indicates where knowledge is and how to get it, but doesn¡¦t contain knowledge. The principal purpose of a knowledge map is to show domain expert when someone need expertise. The principal purpose of a knowledge map is to enhance the efficiency to find the exact expertise someone need. In this digital age, it is a trend for e-learning learners to search knowledge on the Internet. However, when learners try to explore knowledge, they will confront the two important problems:¡ucognitive disorientation¡v and ¡uinformation overloading¡v. This research bases on the function of search engine on the Internet, extract the keywords on the web document, and then analyze the relationship between the keywords appearing on web page. So, we can develop the process of knowledge mapping to construct integrated Knowledge Map (KM). It can reduce the cost and time that is essential for the traditional method. With guidance of the KM, learners can find specific knowledge or discover knowledge relationships more effectively when exploring on the Internet. The contributions of this survey are as followings: Collecting keywords of knowledge automatically, Constructing knowledge relation graph, Constructing knowledge hierarchy graph, and Constructing knowledge time trend graph.

With the coming of knowledge management era, academic institutions also begin to engage in knowledge management (KM) activities, hoping that researchers can understand the relationship between research topics. However, most of the KM activities focusing on academic papers need research¡¦s effort to code and classify paper¡¦s content, and there is still no measurement of relationship between research topics from prior researches. Therefore, this thesis will propose a methodology to measure the relationship between research topics and grab the data of National Central Library from internet to construct a knowledge relationship system. This system will analyze both dissertation¡¦s and thesis¡¦ content, such as keywords, abstracts, etc., and calculate two measurements that are relation strength and relation similarity to assess the direct and indirect relationship between two research topics. Moreover, this thesis found a phenomenon that there is high diversity of Chinese keyword¡¦s usage and the Chinese translation of English keyword. To overcome this incident, the database for Chinese keywords is built. This database will excerpt the mapping of Chinese keywords usage and its translation from the abstract of thesis. Finally, the trend of research topics in information-related domain using different aspects, such as different years, different schools and different departments are analyzed. The result of analysis includes:

Some local health organizations in Ontario (e.g., Local Health Integration Network or LHINs) have put forward a strategic objective to identify patients with preventable high cost healthcare service usage (e.g., hospitalizations, emergency department [ED] visits). To attain this goal, primary care service providers, who are considered the entry point to the health system, need tools to help diagnose, treat and refer those patients identified as being potential high users of the health care system. The goal of this study was to develop a management and referral tool to identify, manage and refer patients living with multiple comorbidities to specialized care teams such as Health Links. Data used in this analysis were obtained from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) primary care data holdings. The dataset created for this study contained 14,004 patient records. Data analysis techniques included use of both statistical and predictive analytic tools. The base models included four data mining classification algorithms: Decision Tree, Naïve Bayes, Neural Network and Clustering. The predictive modeling approach was complemented by an association analysis. The one-way ANOVA analysis indicated that age and health status (number of conditions, and individual medical conditions) identified statistically significant differences in patient utilization of health services. Results from the predictive analytics showed that patient age and patient medical conditions, as well as number of medical conditions for each patient (5 or more) could be used as criteria to develop tools (e.g. searches, reminders). Specifically, Parkinson disease, dementia and epilepsy were found to be important predictors (i.e. most frequently associated with) the top 4 most prevalent conditions (hypertension, osteoarthritis, depression and diabetes) within the population of the study. The association analysis also revealed that chronic obstructive pulmonary disease (COPD) was closely associated with the top 4 most prevalent conditions. Based on the findings of this study, Parkinson Disease, dementia, epilepsy and COPD can be used to identify patients with complex medical needs who are likely to be high users of the healthcare system and to be considered for early, personalized intervention. / Thesis / Master of Health Sciences (MSc)

Kacang faba (Vicia faba L.) merupakan tanaman alogami yang dapat melakukan pembuahan sendiri maupun pembuahan silang. Pembuahan sendiri terjadi tanpa adanya bantuan polinator maupun rangsangan mekanik eksternal, yang pada kacang faba dikenal dengan istilah autofertilitas. Level autofertilitas bervariasi di antara genotipe. Ketika pembuahan terjadi, baik pembuahan sendiri maupun silang, jumlah dan kualitas biji sangat menentukan. Biji kacang faba kaya akan protein dan mengandung komposisi nutrisi lain yang bernilai tinggi. Namun demikian, kacang faba mengandung senyawa anti nutrisi, seperti vicin dan convicin, yang membatasi pemanfaatannya sebagai pangan dan pakan serta memiliki dampak kesehatan bagi manusia. Tujuan dari penelitian ini pada bab pertama adalah untuk mempelajari secara genetik dan mengukur level dan variasi autofertilitas pada kacang faba winter yang spesifik dan untuk mengidentifikasi QTL untuk autofertilitas dan karakter terkait. Jadi fokus bab pertama adalah pada pembuahan dan asal biji. Fokus bab kedua adalah pada kualitas biji yang dihasilkan. Penelitian bab kedua bertujuan untuk mengembangkan kalibrasi berbasis NIRS untuk kandungan vicin-convicin pada biji kacang faba, mempelajari heritabilitas dan variasi genetik kandungan vicin-convicin, mengidentifikasi QTL yang berperan untuk variasi genotipe kacang faba yang mengandung vicin-convicin (tipe liar) dan memverifikasi apakah alel mutan yang terdapat pada vicin-convicin alelik dengan QTL pada material yang mengadung vicin-convicin. Sejumlah eksperimen dilakukan di lapang dan laboratorium untuk mempelajari secara genetik karakter reproduksi dan kualitas biji kacang faba. Materi genetik utama yang digunakan pada penelitian ini melibatkan 200 galur murni, bernama set-Q, yang terdiri dari 189 galur set-A (galur murni untuk studi asosiasi), tujuh galur kacang faba winter dan empat galur kacang faba spring. Set-A berasal dari Göttingen Winter Bean Population (GWBP). Studi fitur reproduksi dilakukan pada rumah isolasi bebas lebah pada 2013, 2014 dan 2015. Perlakuan “tripped” dan “un-tripped” diterapkan pada bunga faba selama musim berbunga. Studi kualitas biji (kandungan vicin-convicin) dilakukan dengan menggunakan analisa HPLC dan spektrofotometri NIR pada biji yang dihasilkan pada penelitian sebelumnya. Kami mengembangkan kalibarsi NIRS untuk memprediksi kandungan vicin-convicin berbasis NIRS. Analisis asosiasi seluruh genom (GWAS) antara penanda DNA dengan karakter fenotipik dilakukan dengan menggunakan TASSEL version 3.0. Sebanyak 2018 penanda polimorfik digunakan yang terdiri dari 189 SNP (Single Nucleotide Polymorphism) dan 1829 AFLP (Amplified Fragment Length Polymorphism). Untuk menentukan autofertilitas, penelitian difokuskan pada karakter prosentase pembuahan, potensi pengisian polong dan pengisian polong sebenarnya, terutama pada perlakuan ‘un-tripped’. Prosentase pembuahan pada perlakuan ‘un-tripped’ rendah, dengan nilai maksimum 37,14% dan heritabiltasnya tinggi. Tripping secara nyata meningkatkan nilai rata-rata ketiga aspek autofertilitas tersebut. Heritabilitas prosentase pembuahan pada perlakuan ‘tripped’ lebih tinggi daripada ‘un-tripped’ yang mengindikasikan perbedaan reaksi tripping merupakan faktor genetik. Tripping yang intens juga mengkonfirmasi hasil tersebut dan menunjukkan bahwa tidak satupun genotype menghasilkan prosentase pembuahan 100%. Hasil penting dari penelitian ini adalah kacang faba winter memiliki level autofertilitas yang berbeda dan lebih rendah dibandingkan dengan kacang faba spring. Teknologi NIRS dapat diterapkan untuk memprediksi kandungan vicin-convicin pada kacang faba. Diperoleh persamaan kalibrasi yang baik dan dapat diterapkan untuk menganalisa contoh biji kacang faba yang dihasilkan pada pengulangan, perlakuan dan tahun yang berbeda. Diperoleh variasi kandungan vicin-convicin yang lebar dan signifikan dengan nilai heritabilitas yang cukup tinggi. Penelitian ini juga menghasilkan beberapa penanda DNA putatif yang secara signifikan terasosiasi dengan beberapa karakter agronomi dan juga kandungan vicin-convicin. Satu penanda AFLP berasosiasi signifikan terhadap variasi vicin-convicin pada genotype, dan dengan menganalisa lebih jauh tiga peta keterpautan yang berbeda dan hubungan sinteni dengan Medicago truncatula, posisi QTL tersebut sangat mungkin berada pada kromosom 5 Vicia faba. Penemuan ini merupakan langkah awal untuk penelitian dan pemuliaan kacang faba winter Eropa yang tinggi fertilitas dengan kualitas biji yang baik.

O mapeamento genético e a genética funcional de doenças são de grande importância na pesquisa médica e genômica. Para estas finalidades o estudo de associação entre fatores de risco genéticos e doença tem ganhado destaque na literatura. Neste trabalho disserta-se sobre a análise de associação aplicada ao mapeamento genético de doenças, caracterizando diferentes possibilidades de planejamentos experimentais e de utilização de modelos estatísticos de análise de dados. As formalizações estatísticas, como o tipo de delineamento experimental, a inclusão ou não de dados familiares, bem como a escolha do método estatístico de análise, que são decisivos na avaliação do poder dos testes obtidos e na sua aplicabilidade ao mapeamento genético, também são discutidas. Além disso, considera-se a análise de associação por meio de modelos de regressão logística em que, as análises de dados genéticos são abordadas via dados no nível genotípico e cromossômico. Finalmente, os conceitos supracitados são aplicados a conjuntos de dados reais, fornecidos pelo Laboratório de Cardiologia e Genética Molecular do InCor/USP, com o objetivo de ilustrar o problema teórico tratado e motivar a aplicação das metodologias estatísticas envolvidas. / The genetic mapping and functional genetics have great importance in the genomics research. In order to conduct these researches the study of the association between genetic risk factors and disease has been becoming an important role in the literature. In this work we consider the association analyses applied to the genetic diseases mapping, charactering different possibilities of experimental designs and the use of statistical models to analyze data sets. The statistical concepts, as the kind of experimental design, the inclusion of familiar records or not, as well as the choice of the statistical analyze method, which are very important to the evaluation of the power of the tests obtained and to their applicability in the genetic mapping, are also discussed. Furthermore, we consider the association analysis at person level and chromosome data set. Finally, the latter concepts are applied to a real data set, provided by the Molecular Genetic and Cardiology Laboratory of InCor/USP, in order to illustrate the theoretical problem treated in this work and to motive the use of the involved statistical methodologies.

O mapeamento genético e a genética funcional de doenças são de grande importância na pesquisa médica e genômica. Para estas finalidades o estudo de associação entre fatores de risco genéticos e doença tem ganhado destaque na literatura. Neste trabalho disserta-se sobre a análise de associação aplicada ao mapeamento genético de doenças, caracterizando diferentes possibilidades de planejamentos experimentais e de utilização de modelos estatísticos de análise de dados. As formalizações estatísticas, como o tipo de delineamento experimental, a inclusão ou não de dados familiares, bem como a escolha do método estatístico de análise, que são decisivos na avaliação do poder dos testes obtidos e na sua aplicabilidade ao mapeamento genético, também são discutidas. Além disso, considera-se a análise de associação por meio de modelos de regressão logística em que, as análises de dados genéticos são abordadas via dados no nível genotípico e cromossômico. Finalmente, os conceitos supracitados são aplicados a conjuntos de dados reais, fornecidos pelo Laboratório de Cardiologia e Genética Molecular do InCor/USP, com o objetivo de ilustrar o problema teórico tratado e motivar a aplicação das metodologias estatísticas envolvidas. / The genetic mapping and functional genetics have great importance in the genomics research. In order to conduct these researches the study of the association between genetic risk factors and disease has been becoming an important role in the literature. In this work we consider the association analyses applied to the genetic diseases mapping, charactering different possibilities of experimental designs and the use of statistical models to analyze data sets. The statistical concepts, as the kind of experimental design, the inclusion of familiar records or not, as well as the choice of the statistical analyze method, which are very important to the evaluation of the power of the tests obtained and to their applicability in the genetic mapping, are also discussed. Furthermore, we consider the association analysis at person level and chromosome data set. Finally, the latter concepts are applied to a real data set, provided by the Molecular Genetic and Cardiology Laboratory of InCor/USP, in order to illustrate the theoretical problem treated in this work and to motive the use of the involved statistical methodologies.

<p>The aim with this thesis has been to identify genes involved in the pathogenesis of Systemic Lupus Erythematosus (SLE). SLE is a systemic autoimmune disorder, most likely caused by both several genetic and environmental factors. </p><p>In order to identify susceptibility loci for the disease we performed linkage analyses on data from 70 families of various ethnic origins. Significant linkage was found in two regions. One region (chromosome 17p12-q11) was linked to SLE in a set of Argentine families. Since the same region had been previously identified in several linkage studies on Multiple Sclerosis patients, we propose that this locus may contain a genetic variant that affects not only SLE, but also autoimmunity in general. The second locus is located on chromosome 4p14-13 and has only been identified in a set of Icelandic families. We suggest that this locus contains a mutation that has been enriched in the Icelandic population due to its population history.</p><p>The <i>BCL2 </i>gene has been suggested as a candidate gene for SLE. Three markers in this gene were investigated for association with the disease in two different populations. However, no association could be found with any of the markers or when these markers were analysed together as a haplotype. We conclude that the <i>BCL2</i> gene is not associated with SLE in our material. This result contradicts previously published results of an association between <i>BCL2</i> and SLE. </p><p>We suggest that the PD-1 pathway (involved in inhibition of T- and B-cell responses) is an important component in SLE pathogenesis. A regulatory variant in the <i>PD-1</i> gene had previously been associated with SLE and here we show strong association (p<0.0001) to a haplotype containing SNPs in both <i>PD-L1</i> and <i>PD-L2</i>. </p><p>Our results indicate that SLE is a disease caused by several genetic variations that differ between families and populations.</p>

The aim with this thesis has been to identify genes involved in the pathogenesis of Systemic Lupus Erythematosus (SLE). SLE is a systemic autoimmune disorder, most likely caused by both several genetic and environmental factors. In order to identify susceptibility loci for the disease we performed linkage analyses on data from 70 families of various ethnic origins. Significant linkage was found in two regions. One region (chromosome 17p12-q11) was linked to SLE in a set of Argentine families. Since the same region had been previously identified in several linkage studies on Multiple Sclerosis patients, we propose that this locus may contain a genetic variant that affects not only SLE, but also autoimmunity in general. The second locus is located on chromosome 4p14-13 and has only been identified in a set of Icelandic families. We suggest that this locus contains a mutation that has been enriched in the Icelandic population due to its population history. The BCL2 gene has been suggested as a candidate gene for SLE. Three markers in this gene were investigated for association with the disease in two different populations. However, no association could be found with any of the markers or when these markers were analysed together as a haplotype. We conclude that the BCL2 gene is not associated with SLE in our material. This result contradicts previously published results of an association between BCL2 and SLE. We suggest that the PD-1 pathway (involved in inhibition of T- and B-cell responses) is an important component in SLE pathogenesis. A regulatory variant in the PD-1 gene had previously been associated with SLE and here we show strong association (p&lt;0.0001) to a haplotype containing SNPs in both PD-L1 and PD-L2. Our results indicate that SLE is a disease caused by several genetic variations that differ between families and populations.

During the last two decades, genotyping technology has advanced rapidly, which enabled the tremendous success of genome-wide association studies (GWAS) in the search of disease susceptibility loci (DSLs). However, only a small fraction of the overall predicted heritability can be explained by the DSLs discovered. One possible explanation for this ”missing heritability” phenomenon is that many causal variants are rare. The recent development of high-throughput next-generation sequencing (NGS) technology provides the instrument to look closely at these rare variants with precision and efficiency. However, new approaches for both the storage and analysis of sequencing data are in imminent needs. In this thesis, we introduce three methods that could be utilized in the management and analysis of sequencing data. In Chapter 1, we propose a novel and simple algorithm for compressing sequencing data that leverages on the scarcity of rare variant data, which enables the storage and analysis of sequencing data efficiently in current hardware environment. We also provide a C++ implementation that supports direct and parallel loading of the compressed format without requiring extra time for decompression. Chapter 2 and 3 focus on the association analysis of sequencing data in population-based design. In Chapter 2, we present a statistical methodology that allows the identification of genetic outliers to obtain a genetically homogeneous subpopulation, which reduces the false positives due to population substructure. Our approach is computationally efficient that can be applied to all the genetic loci in the data and does not require pruning of variants in linkage disequilibrium (LD). In Chapter 3, we propose a general analysis framework in which thousands of genetic loci can be tested simultaneously for association with complex phenotypes. The approach is built on spatial-clustering methodology, assuming that genetic loci that are associated with the target phenotype cluster in certain genomic regions. In contrast to standard methodology for multi-loci analysis, which has focused on the dimension reduction of data, the proposed approach profits from the availability of large numbers of genetic loci. Thus it will be especially relevant for whole-genome sequencing studies which commonly record several thousand loci per gene.