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Articles 91 - 120 of 156

Full-Text Articles in Computational Biology

Pathway-Extended Gene Expression Signatures Integrate Novel Biomarkers That Improve Predictions Of Patient Responses To Kinase Inhibitors, Ashis Jem Bagchee-Clark, Eliseos J. Mucaki, Tyson Whitehead, Peter Rogan Nov 2020

Pathway-Extended Gene Expression Signatures Integrate Novel Biomarkers That Improve Predictions Of Patient Responses To Kinase Inhibitors, Ashis Jem Bagchee-Clark, Eliseos J. Mucaki, Tyson Whitehead, Peter Rogan

Biochemistry Publications

No abstract provided.


Statistical Methods For Resolving Intratumor Heterogeneity With Single-Cell Dna Sequencing, Alexander Davis Aug 2020

Statistical Methods For Resolving Intratumor Heterogeneity With Single-Cell Dna Sequencing, Alexander Davis

Dissertations and Theses (Open Access)

Tumor cells have heterogeneous genotypes, which drives progression and treatment resistance. Such genetic intratumor heterogeneity plays a role in the process of clonal evolution that underlies tumor progression and treatment resistance. Single-cell DNA sequencing is a promising experimental method for studying intratumor heterogeneity, but brings unique statistical challenges in interpreting the resulting data. Researchers lack methods to determine whether sufficiently many cells have been sampled from a tumor. In addition, there are no proven computational methods for determining the ploidy of a cell, a necessary step in the determination of copy number. In this work, software for calculating probabilities from …


Machine Learning Prediction Of Glioblastoma Patient One-Year Survival, Andrew Du '20, Warren Mcgee, Jane Y. Wu Jan 2020

Machine Learning Prediction Of Glioblastoma Patient One-Year Survival, Andrew Du '20, Warren Mcgee, Jane Y. Wu

Student Publications & Research

Glioblastoma (GBM) is a grade IV astrocytoma formed primarily from cancerous astrocytes and sustained by intense angiogenesis. GBM often causes non-specific symptoms, creating difficulty for diagnosis. This study aimed to utilize machine learning techniques to provide an accurate one-year survival prognosis for GBM patients using clinical and genomic data from the Chinese Glioma Genome Atlas. Logistic regression (LR), support vector machines (SVM), random forest (RF), and ensemble models were used to identify and select predictors for GBM survival and to classify patients into those with an overall survival (OS) of less than one year and one year or greater. With …


Effective Statistical Energy Function Based Protein Un/Structure Prediction, Avdesh Mishra Aug 2019

Effective Statistical Energy Function Based Protein Un/Structure Prediction, Avdesh Mishra

LSU New Orleans Theses and Dissertations

Proteins are an important component of living organisms, composed of one or more polypeptide chains, each containing hundreds or even thousands of amino acids of 20 standard types. The structure of a protein from the sequence determines crucial functions of proteins such as initiating metabolic reactions, DNA replication, cell signaling, and transporting molecules. In the past, proteins were considered to always have a well-defined stable shape (structured proteins), however, it has recently been shown that there exist intrinsically disordered proteins (IDPs), which lack a fixed or ordered 3D structure, have dynamic characteristics and therefore, exist in multiple states. Based on …


Molecular Consequences Of High Taz Expression In Gliomas, Visweswaran Ravikumar Aug 2019

Molecular Consequences Of High Taz Expression In Gliomas, Visweswaran Ravikumar

Dissertations and Theses (Open Access)

Diffuse high grade gliomas are complex and lethal neoplasms of the adult central nervous system that are driven by a range of genetic and epigenetic alterations. Molecular classification of these tumors has identified different transcriptional subtypes, the most notable being Proneural (PN) and Mesenchymal (MES) classes. The most aggressive forms of the disease have a Mesenchymal expression signature, with reported PN-to-MES transition occurring with tumor progression. Master regulatory analysis has identified the transcriptional co-activator TAZ (WWTR1) as a major driver of the MES transition. Overexpression of this single protein in glioma stem cells has been shown to drive a transition …


Association Of Copy Number Variations With Chronic Hepatitis B In Chinese Population, Fang Niu Aug 2019

Association Of Copy Number Variations With Chronic Hepatitis B In Chinese Population, Fang Niu

Capstone Experience: Master of Public Health

With one third of the Hepatitis B virus (HBV) infection population of the world, chronic Hepatitis B (CHB) has become a top burden in China. CHB is a lifelong infection with HBV which can cause serious health problems, like cirrhosis, liver cancer or even death. HBV infection is known to result in various clinical conditions, including asymptomatic HBV carriers to chronic hepatitis and primary hepatocellular carcinoma. Several studies have shown that host genetic susceptibility could be an important factor that determines these various outcomes of HBV infection. Many Single Nucleotide Polymorphisms (SNPs) and Copy Number Variations (CNVs) have been associated …


Computational Genomic Models For Spatio-Temporal Investigation Of Early Lung Cancer Pathology, Smruthy Sivakumar May 2019

Computational Genomic Models For Spatio-Temporal Investigation Of Early Lung Cancer Pathology, Smruthy Sivakumar

Dissertations and Theses (Open Access)

Lung cancer, of which non-small cell lung cancer (NSCLC) is the most common form, is the second most prevalent cancer and the leading cause of cancer-related deaths. NSCLCs primarily comprise adenocarcinomas (LUAD) and squamous cell carcinomas (LUSC). Advances in early detection and prevention have been limited by the lack of early-stage biomarkers and targets. A comprehensive molecular characterization of premalignant lesions and tumor-adjacent normal tissue can aid in better understanding NSCLC pathogenesis. However, these investigations are further challenged by limited tissue availability and low cellular fractions of detectable somatic mutations.

Therefore, there is a dearth of knowledge about the pathogenesis …


Incorporating Pathway Information Into Feature Selection Towards Better Performed Gene Signatures, Suyan Tian, Chi Wang, Bing Wang Apr 2019

Incorporating Pathway Information Into Feature Selection Towards Better Performed Gene Signatures, Suyan Tian, Chi Wang, Bing Wang

Biostatistics Faculty Publications

To analyze gene expression data with sophisticated grouping structures and to extract hidden patterns from such data, feature selection is of critical importance. It is well known that genes do not function in isolation but rather work together within various metabolic, regulatory, and signaling pathways. If the biological knowledge contained within these pathways is taken into account, the resulting method is a pathway-based algorithm. Studies have demonstrated that a pathway-based method usually outperforms its gene-based counterpart in which no biological knowledge is considered. In this article, a pathway-based feature selection is firstly divided into three major categories, namely, pathway-level selection, …


Supervised Dimension Reduction For Large-Scale "Omics" Data With Censored Survival Outcomes Under Possible Non-Proportional Hazards, Lauren Spirko-Burns, Karthik Devarajan Mar 2019

Supervised Dimension Reduction For Large-Scale "Omics" Data With Censored Survival Outcomes Under Possible Non-Proportional Hazards, Lauren Spirko-Burns, Karthik Devarajan

COBRA Preprint Series

The past two decades have witnessed significant advances in high-throughput ``omics" technologies such as genomics, proteomics, metabolomics, transcriptomics and radiomics. These technologies have enabled simultaneous measurement of the expression levels of tens of thousands of features from individual patient samples and have generated enormous amounts of data that require analysis and interpretation. One specific area of interest has been in studying the relationship between these features and patient outcomes, such as overall and recurrence-free survival, with the goal of developing a predictive ``omics" profile. Large-scale studies often suffer from the presence of a large fraction of censored observations and potential …


Exploring The Ipf Lung Through The Lens Of Single Cell Rna Sequencing, Taylor Adams, Jonas Schupp Jan 2019

Exploring The Ipf Lung Through The Lens Of Single Cell Rna Sequencing, Taylor Adams, Jonas Schupp

Yale Day of Data

This poster illustrates the differences between the IPF disease-specific variety of lung macrophages and the two varieties of macrophages known to reside in the normal human lung.


Cyclin C: The Story Of A Non-Cycling Cyclin, Jan Jezek, Daniel G J Smethurst, David C Stieg, Z A C Kiss, Sara E Hanley, Vidyaramanan Ganesan, Kai-Ti Chang, Katrina F Cooper, Randy Strich Jan 2019

Cyclin C: The Story Of A Non-Cycling Cyclin, Jan Jezek, Daniel G J Smethurst, David C Stieg, Z A C Kiss, Sara E Hanley, Vidyaramanan Ganesan, Kai-Ti Chang, Katrina F Cooper, Randy Strich

Rowan-Virtua School of Osteopathic Medicine Departmental Research

The class I cyclin family is a well-studied group of structurally conserved proteins that interact with their associated cyclin-dependent kinases (Cdks) to regulate different stages of cell cycle progression depending on their oscillating expression levels. However, the role of class II cyclins, which primarily act as transcription factors and whose expression remains constant throughout the cell cycle, is less well understood. As a classic example of a transcriptional cyclin, cyclin C forms a regulatory sub-complex with its partner kinase Cdk8 and two accessory subunits Med12 and Med13 called the Cdk8-dependent kinase module (CKM). The CKM reversibly associates with the multi-subunit …


Overview Of Direct Thrombin Inhibitors For Use In Staphylococcus Aereus Infections, Joseph C. Risler Jan 2019

Overview Of Direct Thrombin Inhibitors For Use In Staphylococcus Aereus Infections, Joseph C. Risler

Honors Undergraduate Theses

The pathogenicity and intractable nature of the microorganism Staphylococcus aureus (SA) has been long documented and highlighted by many health care agencies, with emphasis on its ability to exploit the human coagulation system to deadly effect. Two drugs from a class of inhibitors known as Direct Thrombin Inhibitors (DTI) have been shown to have a substantial effect on the enzyme secreted by SA known as Staphylocoagulase (SC), but up until now the application of this potential treatment has been limited. This paper strives to supply an overview of these clinical studies and propose a novel protocol for testing DTI's on …


Genome-Wide Systems Genetics Of Alcohol Consumption And Dependence, Kristin Mignogna Jan 2019

Genome-Wide Systems Genetics Of Alcohol Consumption And Dependence, Kristin Mignogna

Theses and Dissertations

Widely effective treatment for alcohol use disorder is not yet available, because the exact biological mechanisms that underlie this disorder are not completely understood. One way to gain a better understanding of these mechanisms is to examine the genetic frameworks that contribute to the risk for developing this disorder. This dissertation examines genetic association data in combination with gene expression networks in the brain to identify functional groups of genes associated with alcohol consumption and dependence.

The first study took advantage of the behavioral complexity of human samples, and experimental capabilities provided by mouse models, by co-analyzing gene expression networks …


Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor Aug 2018

Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor

Electronic Theses and Dissertations

Metabolomics, the study of small molecules in biological systems, has enjoyed great success in enabling researchers to examine disease-associated metabolic dysregulation and has been utilized for the discovery biomarkers of disease and phenotypic states. In spite of recent technological advances in the analytical platforms utilized in metabolomics and the proliferation of tools for the analysis of metabolomics data, significant challenges in metabolomics data analyses remain. In this dissertation, we present three of these challenges and Bayesian methodological solutions for each. In the first part we develop a new methodology to serve a basis for making higher order inferences in metabolomics, …


Transcriptional Profiling Reveals Extraordinary Diversity Among Skeletal Muscle Tissues, Erin E. Terry, Xiping Zhang, Christy Hoffmann, Laura D. Hughes, Scott A. Lewis, Jiajia Li, Matthew J. Wallace, Lance A. Riley, Collin M. Douglas, Miguel A. Gutierrez-Monreal, Nicholas F. Lahens, Ming C. Gong, Francisco H. Andrade, Karyn A. Esser, Michael E. Hughes May 2018

Transcriptional Profiling Reveals Extraordinary Diversity Among Skeletal Muscle Tissues, Erin E. Terry, Xiping Zhang, Christy Hoffmann, Laura D. Hughes, Scott A. Lewis, Jiajia Li, Matthew J. Wallace, Lance A. Riley, Collin M. Douglas, Miguel A. Gutierrez-Monreal, Nicholas F. Lahens, Ming C. Gong, Francisco H. Andrade, Karyn A. Esser, Michael E. Hughes

Physiology Faculty Publications

Skeletal muscle comprises a family of diverse tissues with highly specialized functions. Many acquired diseases, including HIV and COPD, affect specific muscles while sparing others. Even monogenic muscular dystrophies selectively affect certain muscle groups. These observations suggest that factors intrinsic to muscle tissues influence their resistance to disease. Nevertheless, most studies have not addressed transcriptional diversity among skeletal muscles. Here we use RNAseq to profile mRNA expression in skeletal, smooth, and cardiac muscle tissues from mice and rats. Our data set, MuscleDB, reveals extensive transcriptional diversity, with greater than 50% of transcripts differentially expressed among skeletal muscle tissues. We detect …


Modeling And Analyzing An Optogenetic System For Photoactivatable Protein Dissociation, Anvin Thomas, James Schaff May 2018

Modeling And Analyzing An Optogenetic System For Photoactivatable Protein Dissociation, Anvin Thomas, James Schaff

Honors Scholar Theses

Computational modeling of cell-cell interactions can grant clues and can answer questions about an experiment, especially for observations about binding interactions and kinetics. This approach was used to investigate an interaction between a light-oxygen-voltage (LOV) domain and an engineered protein called Zdark (Zdk). The LOV domain is membrane-bound while Zdk is cytosolic. The LOV domain and Zdk bind strongly in dark (Kd 26.2 nM), and weakly upon exposure to blue light (Kd > 4 μM). Total internal reflection fluorescence (TIRF) images are acquired of Zdk, the fluorescent species bound to a mCherry tag, and the loss of fluorescence is …


Understanding Huntington's Disease Using Machine Learning Approaches, Sonali Lokhande Dec 2017

Understanding Huntington's Disease Using Machine Learning Approaches, Sonali Lokhande

KGI Theses and Dissertations

Huntington’s disease (HD) is a debilitating neurodegenerative disorder with a complex pathophysiology. Despite extensive studies to study the disease, the sequence of events through which mutant Huntingtin (mHtt) protein executes its action still remains elusive. The phenotype of HD is an outcome of numerous processes initiated by the mHtt protein along with other proteins that act as either suppressors or enhancers of the effects of mHtt protein and PolyQ aggregates. Utilizing an integrative systems biology approach, I construct and analyze a Huntington’s disease integrome using human orthologs of protein interactors of wild type and mHtt protein. Analysis of this integrome …


The Ability Of Different Imputation Methods To Preserve The Significant Genes And Pathways In Cancer, Rosa Aghdam, Taban Baghfalaki, Pegah Khosravi, Elnaz Saberi Ansari Dec 2017

The Ability Of Different Imputation Methods To Preserve The Significant Genes And Pathways In Cancer, Rosa Aghdam, Taban Baghfalaki, Pegah Khosravi, Elnaz Saberi Ansari

Publications and Research

Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM) method was applied to detect the significant genes in rectal and lung cancers to showcase …


Bayesian Prediction Intervals For Assessing P-Value Variability In Prospective Replication Studies, Olga A. Vsevolozhskaya, Gabriel Ruiz, Dmitri Zaykin Dec 2017

Bayesian Prediction Intervals For Assessing P-Value Variability In Prospective Replication Studies, Olga A. Vsevolozhskaya, Gabriel Ruiz, Dmitri Zaykin

Biostatistics Faculty Publications

Increased availability of data and accessibility of computational tools in recent years have created an unprecedented upsurge of scientific studies driven by statistical analysis. Limitations inherent to statistics impose constraints on the reliability of conclusions drawn from data, so misuse of statistical methods is a growing concern. Hypothesis and significance testing, and the accompanying P-values are being scrutinized as representing the most widely applied and abused practices. One line of critique is that P-values are inherently unfit to fulfill their ostensible role as measures of credibility for scientific hypotheses. It has also been suggested that while P-values …


In Silico Study Of Newly Synthesized Opioid Analgesics Bound To Three Opioid Receptors, Abdullah Allaoa, Mai Zahran Dec 2017

In Silico Study Of Newly Synthesized Opioid Analgesics Bound To Three Opioid Receptors, Abdullah Allaoa, Mai Zahran

Publications and Research

Opioids are the most widely used drugs for the treatment of moderate to severe, chronic pain. They achieve antinociception by activation of mu (MOR-1), kappa (KOR-1), and delta (DOR-1) opioid receptors. Natural products found in kratom plant, Mitragyna speciosa, represent diverse chemical groups with opioid activity, providing opportunities to better understand opioid pharmacology. Pharmacology studies show that Mitragynine pseudoindoxyl is a mu agonist/delta antagonist opioid with a signaling bias for G-protein-mediated signaling pathways in vitro and which produced potent antinociception in vivo. Respiratory depression assays along with other behavioral testing also showed that some of the major problems …


Integrative Cancer Immunogenomic Analysis Of Serial Melanoma Biopsies Reveals Correlates Of Response And Resistance To Sequential Ctla-4 And Pd-1 Blockade Treatment, Whijae Roh Dec 2017

Integrative Cancer Immunogenomic Analysis Of Serial Melanoma Biopsies Reveals Correlates Of Response And Resistance To Sequential Ctla-4 And Pd-1 Blockade Treatment, Whijae Roh

Dissertations and Theses (Open Access)

Melanoma is the most malignant form of skin cancer. The five-year survival rate for metastatic melanoma is 19.9%. Although targeted therapy of BRAF and MEK inhibitors were developed for melanoma, resistance to therapy is inevitable. Immune checkpoint blockade, which reverses the suppression of the immune system, on the other hand, has shown a durable response in 20-30% of patients with metastatic melanoma. However, more predictive and robust biomarkers of response to this therapy are still needed, and resistance mechanisms remain incompletely understood. To address this, we examined a cohort of metastatic melanoma patients treated with sequential checkpoint blockade against cytotoxic …


Exploring Biological Heterogeneity And Its Consequences At Tissue And Cellular Scales Through Mathematical And Computational Modeling, Romica Kerketta Sep 2017

Exploring Biological Heterogeneity And Its Consequences At Tissue And Cellular Scales Through Mathematical And Computational Modeling, Romica Kerketta

Biomedical Sciences ETDs

This dissertation explores the effects of heterogeneity across different biological scales in cancer as well as normal cells. At the tissue scale, we investigated the variability present in the tumor microenvironment and its effect on patient chemotherapeutic outcomes using a mathematical model of drug transport. We found that parameters such as tumor blood perfusion and radius of blood vessel had an impact on the tumor cytotoxicity. This indicated that the physical microenvironment of the tumor is an important regulator of the tumor response to chemotherapy. At the cellular scale, we investigated the heterogeneity present on the membrane landscape of ErbB2 …


Using Mathematical Models Of Biological Processes In Genome-Wide Association Studies Of Psychiatric Disorders, Amy Cochran May 2017

Using Mathematical Models Of Biological Processes In Genome-Wide Association Studies Of Psychiatric Disorders, Amy Cochran

Biology and Medicine Through Mathematics Conference

No abstract provided.


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 and 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 …


Penetrance Estimates For Incidental Genomic Findings In Acmg-59, James A. Diao Jan 2017

Penetrance Estimates For Incidental Genomic Findings In Acmg-59, James A. Diao

Yale Day of Data

The dropping costs and rising popularity of next-generation sequencing has introduced the possibility of personalizing medical treatments and screening for genetic diseases. Still, the clinical community’s understanding remains incomplete, with limited consensus on the proper interpretation for many genetic variants. Thus, the standard procedure when returning sequencing results has been to report findings only in genes related to the diagnostic indication, and not incidental findings in other genes. To balance the threat of false positives with the medical benefits of true findings, the American College on Medical Genetics and Genomics (ACMG) recommends an exception: that clinical sequencing laboratories seek and …


Optimization Of A Genomic Editing System Using Crispr/Cas9-Induced Site-Specific Gene Integration, Jillian L. Mccool Ms., Nick Hum, Gabriela G. Loots Aug 2016

Optimization Of A Genomic Editing System Using Crispr/Cas9-Induced Site-Specific Gene Integration, Jillian L. Mccool Ms., Nick Hum, Gabriela G. Loots

STAR Program Research Presentations

The CRISPR-Cas system is an adaptive immune system found in bacteria which helps protect against the invasion of other microorganisms. This system induces double stranded breaks at precise genomic loci (1) in which repairs are initiated and insertions of a target are completed in the process. This mechanism can be used in eukaryotic cells in combination with sgRNAs (1) as a tool for genome editing. By using this CRISPR-Cas system, in addition to the “safe harbor locus,” ROSAβ26, the incorporation of a target gene into a site that is not susceptible to gene silencing effects can be achieved through few …


Development Of An In Silico Kir Genotyping Algorithm And Its Application To Population And Cancer Immunogenetic Analyses, Howard Rosoff Aug 2016

Development Of An In Silico Kir Genotyping Algorithm And Its Application To Population And Cancer Immunogenetic Analyses, Howard Rosoff

Dissertations and Theses (Open Access)

Gene content determination and variant calling in the complex KIR genomic region are useful for immune system function analysis, pathogenesis and disease risk factor elucidation, immunotherapy development, evolutionary investigations, and human migration modeling. Sequence-specific oligonucleotide and sequence-specific primer PCR methods are the de facto standards for KIR presence/absence identification, but the current platforms are unsuitable for SNP calling, impractical for KIR typing large cohorts of DNA samples, and inapplicable for typing repositories in which sequence data, but not cells or cell analytes, are available. Alternative typing methods, such as in silico sequence-based typing, can address the problems associated with amplicon-based …


Phylogenetic Analysis Of Human Cytomegalovirus Pus27 And Pus28: Ascertaining An Independent Or Linked Evolutionary History, Jessica A. Scarborough May 2016

Phylogenetic Analysis Of Human Cytomegalovirus Pus27 And Pus28: Ascertaining An Independent Or Linked Evolutionary History, Jessica A. Scarborough

Undergraduate Honors Theses

Human cytomegalovirus (HCMV) is a widespread pathogen that is particularly skilled at evading immune detection and defense mechanisms, largely due to extensive co-evolution with its host’s immune system. One aspect of this co-evolution involves the acquisition of four virally encoded GPCR chemokine receptor homologs, products of the US27, US28, UL33 and UL78 genes. G protein-coupled receptors (GPCR) are the largest family of cell surface proteins, found in organisms from yeast to humans. In this research, phylogenetic analysis was used to investigate the origins of the US27 and US28 genes, which are adjacent in the viral genome. The results indicate that …


Accurate Mutation Annotation And Functional Prediction Enhance The Applicability Of -Omics Data In Precision Medicine, Tenghui Chen May 2016

Accurate Mutation Annotation And Functional Prediction Enhance The Applicability Of -Omics Data In Precision Medicine, Tenghui Chen

Dissertations and Theses (Open Access)

Clinical sequencing has been recognized as an effective approach for enhancing the accuracy and efficiency of cancer patient management and therefore achieve the goals of personalized therapy. However, the accuracy of large scale sequencing data in clinics has been constrained by many different aspects, such as clinical detection, annotation and interpretation of the variants that are observed in clinical sequencing data. In my Ph.D thesis work, I mainly investigated how to comprehensively and efficiently apply high dimensional -omics data to enhance the capability of precision cancer medicine. Following this motivation, my dissertation has been focused on two important topics in …


Detecting Gene-Gene Interactions Using A Permutation-Based Random Forest Method, Jing Li, James D. Malley, Angeline S. Andrew, Margaret R. Karagas, Jason H. Moore Apr 2016

Detecting Gene-Gene Interactions Using A Permutation-Based Random Forest Method, Jing Li, James D. Malley, Angeline S. Andrew, Margaret R. Karagas, Jason H. Moore

Dartmouth Scholarship

Identifying gene-gene interactions is essential to understand disease susceptibility and to detect genetic architectures underlying complex diseases. Here, we aimed at developing a permutation-based methodology relying on a machine learning method, random forest (RF), to detect gene-gene interactions. Our approach called permuted random forest (pRF) which identified the top interacting single nucleotide polymorphism (SNP) pairs by estimating how much the power of a random forest classification model is influenced by removing pairwise interactions.