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Full-Text Articles in Bioinformatics

Functional Data Analysis Methods For Predicting Disease Status., Sarah Kendrick Dec 2017

Functional Data Analysis Methods For Predicting Disease Status., Sarah Kendrick

Electronic Theses and Dissertations

Introduction: Differential scanning calorimetry (DSC) is used to determine thermally-induced conformational changes of biomolecules within a blood plasma sample. Recent research has indicated that DSC curves (or thermograms) may have different characteristics based on disease status and, thus, may be useful as a monitoring and diagnostic tool for some diseases. Since thermograms are curves measured over a range of temperature values, they are often considered as functional data. In this dissertation we propose and apply functional data analysis (FDA) techniques to analyze DSC data from the Lupus Family Registry and Repository (LFRR). The aim is to develop FDA methods to …


Using Data To Improve Services For Infants With Hearing Loss: Linking Newborn Hearing Screening Records With Early Intervention Records, Maria Gonzalez, Lori Iarossi, Yan Wu, Ying Huang, Kirsten Siegenthaler Nov 2017

Using Data To Improve Services For Infants With Hearing Loss: Linking Newborn Hearing Screening Records With Early Intervention Records, Maria Gonzalez, Lori Iarossi, Yan Wu, Ying Huang, Kirsten Siegenthaler

Journal of Early Hearing Detection and Intervention

The purpose of this study was to match records of infants with permanent hearing loss from the New York Early Hearing Detection and Intervention Information System (NYEHDI-IS) to records of infants with permanent hearing loss receiving early intervention services from the New York State Early Intervention Program (NYSEIP) to identify areas in the state where hearing screening, diagnostic evaluations and referrals to the NYSEIP were not being made or documented in a timely manner. Data from 2014-2016 NYEHDI-IS and NYEIS information systems were matched using The Link King. There were 274 infants documented in NYEIS Information System as receiving early …


Multiple Testing Correction With Repeated Correlated Outcomes: Applications To Epigenetics, Katie Leap Oct 2017

Multiple Testing Correction With Repeated Correlated Outcomes: Applications To Epigenetics, Katie Leap

Masters Theses

Epigenetic changes (specifically DNA methylation) have been associated with adverse health outcomes; however, unlike genetic markers that are fixed over the lifetime of an individual, methylation can change. Given that there are a large number of methylation sites, measuring them repeatedly introduces multiple testing problems beyond those that exist in a static genetic context. Using simulations of epigenetic data, we considered different methods of controlling the false discovery rate. We considered several underlying associations between an exposure and methylation over time.

We found that testing each site with a linear mixed effects model and then controlling the false discovery rate …


Testing The Independence Hypothesis Of Accepted Mutations For Pairs Of Adjacent Amino Acids In Protein Sequences, Jyotsna Ramanan, Peter Revesz Jul 2017

Testing The Independence Hypothesis Of Accepted Mutations For Pairs Of Adjacent Amino Acids In Protein Sequences, Jyotsna Ramanan, Peter Revesz

School of Computing: Faculty Publications

Evolutionary studies usually assume that the genetic mutations are independent of each other. However, that does not imply that the observed mutations are independent of each other because it is possible that when a nucleotide is mutated, then it may be biologically beneficial if an adjacent nucleotide mutates too. With a number of decoded genes currently available in various genome libraries and online databases, it is now possible to have a large-scale computer-based study to test whether the independence assumption holds for pairs of adjacent amino acids. Hence the independence question also arises for pairs of adjacent amino acids within …


Can Cone Signals In The Wild Be Predicted From The Past?, David H. Foster, Iván Marín-Franch May 2017

Can Cone Signals In The Wild Be Predicted From The Past?, David H. Foster, Iván Marín-Franch

MODVIS Workshop

In the natural world, the past is usually a good guide to the future. If light from the sun and sky is blue earlier in the day and yellow now, then it is likely to be more yellow later, as the sun's elevation decreases. But is the light reflected from a scene into the eye as predictable as the light incident upon the scene, especially when lighting changes are not just spectral but include changes in local shadows and mutual reflections? The aim of this work was to test the predictability of cone photoreceptor signals in the wild over the …


Statistical Methods For Two Problems In Cancer Research: Analysis Of Rna-Seq Data From Archival Samples And Characterization Of Onset Of Multiple Primary Cancers, Jialu Li May 2017

Statistical Methods For Two Problems In Cancer Research: Analysis Of Rna-Seq Data From Archival Samples And Characterization Of Onset Of Multiple Primary Cancers, Jialu Li

Dissertations & Theses (Open Access)

My dissertation is focused on quantitative methodology development and application for two important topics in translational and clinical cancer research.

The first topic was motivated by the challenge of applying transcriptome sequencing (RNA-seq) to formalin-fixation and paraffin-embedding (FFPE) tumor samples for reliable diagnostic development. We designed a biospecimen study to directly compare gene expression results from different protocols to prepare libraries for RNA-seq from human breast cancer tissues, with randomization to fresh-frozen (FF) or FFPE conditions. To comprehensively evaluate the FFPE RNA-seq data quality for expression profiling, we developed multiple computational methods for assessment, such as the uniformity and continuity …


Novel Statistical Approaches For Missing Values In Truncated High-Dimensional Metabolomics Data With A Detection Threshold., Jasmit Sureshkumar Shah May 2017

Novel Statistical Approaches For Missing Values In Truncated High-Dimensional Metabolomics Data With A Detection Threshold., Jasmit Sureshkumar Shah

Electronic Theses and Dissertations

Despite considerable advances in high throughput technology over the last decade, new challenges have emerged related to the analysis, interpretation, and integration of high-dimensional data. The arrival of omics datasets has contributed to the rapid improvement of systems biology, which seeks the understanding of complex biological systems. Metabolomics is an emerging omics field, where mass spectrometry technologies generate high dimensional datasets. As advances in this area are progressing, the need for better analysis methods to provide correct and adequate results are required. While in other omics sectors such as genomics or proteomics there has and continues to be critical understanding …


Network Exploration Of Correlated Multivariate Protein Data For Alzheimer's Disease Association, Matthew J. Lane Apr 2017

Network Exploration Of Correlated Multivariate Protein Data For Alzheimer's Disease Association, Matthew J. Lane

Theses

Alzheimer Disease (AD) is difficult to diagnose by using genetic testing or other traditional methods. Unlike diseases with simple genetic risk components, there exists no single marker determining as to whether someone will develop AD. Furthermore, AD is highly heterogeneous and different subgroups of individuals develop the disease due to differing factors. Traditional diagnostic methods using perceivable cognitive deficiencies are often too little too late due to the brain having suffered damage from decades of disease progression. In order to observe AD at early stages prior to the observation of cognitive deficiencies, biomarkers with greater accuracy are required. By using …


A Functional Data Analytic Approach For Region Level Differential Dna Methylation Detection, Mohamed Salem F. Milad Jan 2017

A Functional Data Analytic Approach For Region Level Differential Dna Methylation Detection, Mohamed Salem F. Milad

Doctoral Dissertations

"DNA methylation is an epigenetic modification that can alter gene expression without a DNA sequence change. The role of DNA methylation in biological processes and human health is important to understand, with many studies identifying associations between specific methylation patterns and diseases such as cancer. In mammals, DNA methylation almost always occurs when a methyl group attaches to a cytosine followed by a guanine (i.e. CpG dinucleotides) on the DNA sequence. Many statistical methods have been developed to test for a difference in DNA methylation levels between groups (e.g. healthy vs disease) at individual cytosines. Site level testing is often …


Statistical Contributions To Bioinformatics: Design, Modeling, Structure Learning, And Integration, Jeffrey S. Morris, Veera Baladandayuthapani Dec 2016

Statistical Contributions To Bioinformatics: Design, Modeling, Structure Learning, And Integration, Jeffrey S. Morris, Veera Baladandayuthapani

Jeffrey S. Morris

The advent of high-throughput multi-platform genomics technologies providing whole-genome molecular summaries of biological samples has revolutionalized biomedical research. These technologies yield highly structured big data, whose analysis poses significant quantitative challenges. The field of Bioinformatics has emerged to deal with these challenges, and is comprised of many quantitative and biological scientists working together to eectively process these data and extract the treasure trove of information they contain. Statisticians, with their deep understanding of variability and uncertainty quantification, play a key role in these efforts. In this article, we attempt to summarize some of the key contributions of statisticians to bioinformatics, …