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Modeling Multivariate Biomedical Data

Thesis Info

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External Link

Author

Nawaz, Uzma

Program

PhD

Institute

Bahauddin Zakariya University

City

Multan

Province

KPK

Country

Pakistan

Thesis Completing Year

2013

Thesis Completion Status

Completed

Subject

Mathemaics

Language

English

Link

http://prr.hec.gov.pk/jspui/handle/123456789/1546

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676726657146

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The study addresses the significance of biomedical data to be analyzed by Statistical Community in collaboration with the expertise of personnel in the biomedical field. The data has its own particular constraints and difficulties being privacy-sensitive, heterogeneous and voluminous data. The mathematical understanding of patterns and structures and estimation procedures may be fundamentally different from those of data collected in other fields. For the purpose complicated genomic data of leukemia cancer type of Golub et al (1999) is selected for the study. This dataset comes from a study of gene expression in two types of acute leukemia’s, acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). The training data set consisted of 38 bone marrow samples, 27 of which were taken from ALL patients (19 B-ALL and 8 T-ALL) and 11 of which were taken from AML patients. Each gene expression is the quantitative level of messenger RNA found in the cells. Understanding the genetic underpinnings of disease is important for screening, treatment, drug development, and basic biological insight. Thus exploring genomic data has drawn on mathematical, statistical, and computational methods to discover meaningful genetic relationships from large-scale measurements of genes. Since this is a continuously growing area and is constantly being seeded with new approaches and interpretations. Most of this new material is easily accessible given a familiarity with basic genetics and multivariate statistics. The application of multivariate techniques need a thorough study of the data in hand and the primary objective in the study has been to “let the data speak for itself”. For the proper interpretation of these data, experimental and computational genomics need to have a firm grasp of statistical methodology. An aspect of prime importance, keenly taken into consideration in the 1study. For the multivariate genomic data of leukemia cancer type an initial exploratory data analysis has been performed in the study with the graphical tools of Histograms and Box plots in conjunction with one another. This has exposed that such a data set has a thorough fit for the extreme value distributions, which apart for the study undertaken has not been found in literature for the data type. The fitting of extreme value distributions has opened many new avenues for the data type for the new researchers to work on. Another output of the exploratory data analysis is the application of an appropriate transformation (the classical Box Cox transformation) to deal with the sharp skewness the data, and not relying only on the traditionally used logarithmic transformation. The appropriate data transformation has been another high point in the application of PCA for visualizing clusters present in the data set. Previously PCA and other complicated techniques like SOM and SVM has been applied and new adaptations are continuously being tried on these apart from the traditional clustering methodologies. Here the focus has not been just on the application of multivariate techniques to locate the clusters as predefined by the biological knowledge, rather it is on the methodologically simple yet most appropriate technique to be applied after a thorough look into the interior of the data set. Thus the data set revealed a patterned correlation matrix which in itself explained the number and configuration of clusters. This provided a groundwork for the application of PCA on box cox transformed data using the patterned correlation matrix as the interrelationship matrix. Indeed a comparison has been made with other interrelationship matrices as well. The clear cluster structure presented was, with no any misclassification in the configuration of clusters and exactly coincided with the prior biological knowledge. Therefore as per our hopes this introduction to prototypical methods for 2studying the data and interpreting in the context of biological genomic knowledge has been successful to get started. Addressing the next immediate issue in the study of the biomedical genomic data was finding genes that may be specific for one leukemia type or the cluster. The initial exploratory data analysis exposed certain data values that were of prime biological significance and played statistically significant role in the specification of genes for each cluster defined or the leukemia type. Resultantly a criterion developed from the data set, classifying each gene into its specific single cluster, or two of the three clusters or in all of the three clusters (the common genes).Thus a classified data set of the most variant genes across all the samples was taken as a training data set. Based on the classified grouping a linear discriminant analysis was successfully performed to find the discriminating genes for the specific leukemia type with 99.97% probability of correct classification. The collections of the discriminating genes from the three clusters formed were then needed to be checked for the previously found externally valid cluster structure. PCA was then applied in a new dimension as a check for the discriminating genes. For the discriminating genes the cluster formed for the sample expression profiles were expected to be distinctively clear for the genes to term as a leukemia type specific or cluster specific. Thus the clusters formed were very clearly distinguishable from one and other in contrast to the clusters of the sample expression profiles comprising of the common genes in all. These presented no any distinctive cluster rather a big bulk of a cluster that did not showed any difference in the biologically different leukemia types. The two major issues of the biomedical genomic data have been addressed successfully with an appropriate proposed model for the data type. Thus the study has been based on methodologically simple yet appropriate statistical techniques for such a data type filling 3the inevitable space left in for a statistical community the Pakistani statistical community for the very first time for such a internationally important field, the genomic biomedical field. With the results being unequivocal: Simplest is best! Can cluster genes, cell samples, or both. Yet the study has explored many new dimensions that need to be explored to establish relationship between an experiment based leukemia class and its subclass and a clinical out come. Since the data has many dimensions and concentrating on few precisely has been a difficult task yet accomplished.
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مشتاق احمد انبیٹھوی

مشتاق احمد انبیٹھوی
اس موقع پرہمیں اپنی جماعت کے ایک اوربزرگ عالم مولانا مشتاق احمد صاحب انبیٹھویکی وفات حسرت آیات کابھی ماتم کرناہے، مولانا مرحوم ایک درویش گوشہ نشین اورعالم خلوت پسند تھے۔ انبیٹھ ضلع سہارنپور وطن تھا۔ وہاں کے مشہور خاندان شیوخ سے تعلق رکھتے تھے۔ درس نظامی کی تعلیم دہلی اور سہارنپور میں پائی تھی۔ آخر میں حدیث کادرس مولانا احمد علی صاحب محدث سہارنپوری سے لیا۔مطالعۂ کتب اور تصنیف وتالیف کاخاصا ذوق تھا۔ خود اپنا بڑا کتب خانہ رکھتے تھے۔مرحوم کی تصنیفات کی تعداد اکیاسی (۸۱)ہے۔اس فہرست میں ان کی مطبوعہ اورغیر مطبوعہ سب کتابیں اوررسالے شامل ہیں۔یہ تصنیفات اکثروبیشتر مذہبی مسائل،تاریخ و تذکرہ اورتصوف ومعرفت سے متعلق ہیں اورعربی، فارسی اور اردو تینوں زبانوں میں ہیں۔علم ظاہر کے ساتھ صاحب باطن اور صاحب سلوک و طریقت بھی تھے۔ معاشی اعتبار سے مرفہ الحال ہونے کے باوجود ورع واحتیاط ان کی زندگی کا طغراء امتیاز تھا۔کیسے ہی سخت بیمار ہوں جب تک انگریزی دواکے متعلق ان کو الکحل سے بالکل پاک وصاف ہونے کا یقین نہیں ہوتاتھا نہیں پیتے تھے۔پبلک زندگی سے ان کونفرت تھی۔ ایک گوشۂ تنہائی میں بیٹھے ہوئے تصنیف وتالیف،مطالعۂ کتب، ارشاد و ہدایت باطنی اور افتاء کی خدمت انجام دیتے رہتے تھے۔آج کل پرانی وضع قطع کے پابند جو بزرگ نظرآتے ہیں ان کو غنیمت جانناچاہیے۔کچھ عرصے بعدآنکھیں اس وضع کو دیکھنے کے لیے ترسا ہی کریں گی۔ افسوس کہ آں مرحوم نے ۱۴/فروری ۱۹۴۲ء کو شام کے چاربجے ۹۴ سال کی عمر میں وفات پائی۔حق تعالیٰ مرحوم کوغریق بحرِ رحمت کرے اور مراتب اخروی بڑھائے۔آمین [اپریل۱۹۴۲ء]

Impact of Holy Quran Recitation on Psychological Wellbeing Among Muslim Youth

The present study is aimed to examine the relation of Holy Qur’ān recitation and psychological wellbeing among the Muslim Youth. People find no time for offering prayers and reciting Holy Qur’ān because they are very busy in their daily routines and if they do so, they do it for short period of time when they are in some trouble. The objectives include firstly the exploration of the relationship of Holy Qur’ān recitation and psychological wellbeing. Second objective of the study is to explore the correlation of the Holy Qur’ān recitation with depression, anxiety and stress among young Muslims. Study sample comprises of 100 young Muslims (43 males and 57 females) falling between 17 and 25 years from Rawalpindi and Islamabad. Instruments used for data collection include psychological wellbeing scale by Kamman and Flett (1983) and DASS (depression anxiety stress scale) by Lovibond and Lovibond (1995) and a demographic sheet. Results of the study showed that significant positive relationship exists between Holy Qur’ān recitation and psychological wellbeing among young Muslims and Holy Qur’ān recitation negatively relates with depression, anxiety and stress. The present study findings support that those young Muslims who had more rate of Holy Qur’ān recitation were psychologically more stable as compared to non-frequent reciters. In the light of findings of current study, it can be declared as a quintessence that Holy Qur’ān Recitation can serve as an influential element in ensuring the positive mental health of youth. Educators and Policy makers can play a crucial role in promotion of Holy Qur’ān familiarity which will make certain the psychological and mental health of youth and of the society at large.

An Analysis of Institutional Investors, Information Asymmetry and Stock Market Liquidity A Sector Wise Analysis in Pakistan Stock Exchange

The study was conducted by checking the effect of institutional investors (Ins.Invs) on information asymmetry (Inf.Asym) and stock market liquidity (ML) in Pakistan stock exchange (PSX). The aim of the study was to analyze the Ins.Invs, Inf.Asym, and ML on the basis of most populated non-financial sectors among the other sectors listed at PSX. The purposive sampling is base for the study and has selected four sectors, that is, textile, food, chemical and pharmaceutical and mineral plus cement sector as the sample of the study. The sample comprises of 280 sample firms which constitute 70 percent of the total population. The information of the sample firms has been gathered through reliable sources like annual reports of the sample firms, business recorder, yahoo finance and the official web sites of State Bank of Pakistan and PSX. The panel firm information regression was recommended for the firm information analysis. According to the results of this model; in textile sector, institutional shareholdings (IS) and growth shows insignificant effect on market liquidity while firm size and leverage have significantly affect the ML. Further, IS, growth and leverage have insignificant while size of the firm has significantly affect the information asymmetry. In food sector, institutional shareholdings and growth shows insignificant effect on market liquidity while firm size and leverage shows noteworthy effect on market liquidity. IS, growth and leverage have insignificant effect while firm size has significant effect on information asymmetry. In chemical sector, institutional shareholdings, leverage and growth shows insignificant effect on market liquidity while firm size shows noteworthy effect on ML. Furthermore, IS and growth have unimportant effect while firm size and growth has major effect on information asymmetry. In cement sector, institutional shareholdings, firm size and growth have notably affected the ML as well as the leverage has also considerably affected the ML that shows the significance of the variables of this study. Similarly, IS, growth and leverage have momentous effect while firm size has unimportant effect on information asymmetry.