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Articles 1141 - 1170 of 2075
Full-Text Articles in Computer Sciences
Bioinformatics And Biomedical Engineering, Francisco Ortuño, Ignacio Rojas, Kathryn Dempsey Cooper, Sachin Pawaskar, Hesham Ali
Bioinformatics And Biomedical Engineering, Francisco Ortuño, Ignacio Rojas, Kathryn Dempsey Cooper, Sachin Pawaskar, Hesham Ali
Faculty Books and Monographs
Editors: Francisco Ortuño, Ignacio Rojas
Chapter, Identification of Biologically Significant Elements Using Correlation Networks in High Performance Computing Environments, co-authored by Kathryn Dempsey Cooper, Sachin Pawaskar, and Hesham Ali, UNO faculty members.
The two volume set LNCS 9043 and 9044 constitutes the refereed proceedings of the Third International Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2015, held in Granada, Spain in April 2015. The 134 papers presented were carefully reviewed and selected from 268 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases, biomedical engineering, biomedical image analysis, biomedical signal analysis, computational genomics, computational …
Novel Computational Methods For Transcript Reconstruction And Quantification Using Rna-Seq Data, Yan Huang
Novel Computational Methods For Transcript Reconstruction And Quantification Using Rna-Seq Data, Yan Huang
Theses and Dissertations--Computer Science
The advent of RNA-seq technologies provides an unprecedented opportunity to precisely profile the mRNA transcriptome of a specific cell population. It helps reveal the characteristics of the cell under the particular condition such as a disease. It is now possible to discover mRNA transcripts not cataloged in existing database, in addition to assessing the identities and quantities of the known transcripts in a given sample or cell. However, the sequence reads obtained from an RNA-seq experiment is only a short fragment of the original transcript. How to recapitulate the mRNA transcriptome from short RNA-seq reads remains a challenging problem. We …
Using Wild I.D. As A Reliable Source For Mark And Recapture Studies On Northern Pike (Esox Lucius), Martin Evans
Using Wild I.D. As A Reliable Source For Mark And Recapture Studies On Northern Pike (Esox Lucius), Martin Evans
Journal of Earth and Life Science
Mark and recapture studies are a very popular method fisheries biologists use to assess certain fish populations in lakes. This process can be very labor intensive and expensive. Wild I.D. is free software developed by Dartmouth College that uses SIFT program to find unique features in photographs. Initially developed for identification of African land mammals the program gives each photo a score and percent match to other photos. Northern pike were used in this study to determine if the program can recognize simulated recapture events. Photos of sample fish were taken at two separate locations, the photos were then copied …
Reasoning Over Taxonomic Change: Exploring Alignments For The Perelleschus Use Case, Nico M. Franz, Mingmin Chen, Shizhuo Yu, Parisa Kianmajd, Shaun Bowers, Bertram Ludäscher
Reasoning Over Taxonomic Change: Exploring Alignments For The Perelleschus Use Case, Nico M. Franz, Mingmin Chen, Shizhuo Yu, Parisa Kianmajd, Shaun Bowers, Bertram Ludäscher
Computer Science Faculty Scholarship
Classifications and phylogenetic inferences of organismal groups change in light of new insights. Over time these changes can result in an imperfect tracking of taxonomic perspectives through the re-/use of Code-compliant or informal names. To mitigate these limitations, we introduce a novel approach for aligning taxonomies through the interaction of human experts and logic reasoners. We explore the performance of this approach with the Perelleschus use case of Franz & Cardona-Duque (2013). The use case includes six taxonomies published from 1936 to 2013, 54 taxonomic concepts (i.e., circumscriptions of names individuated according to their respective source publications), and 75 expert-asserted …
Evaluation Of The Signature Molecular Descriptor With Blosum62 And An All-Atom Description For Use In Sequence Alignment Of Proteins, Lindsay M. Aichinger
Evaluation Of The Signature Molecular Descriptor With Blosum62 And An All-Atom Description For Use In Sequence Alignment Of Proteins, Lindsay M. Aichinger
Williams Honors College, Honors Research Projects
This Honors Project focused on a few aspects of this topic. The second is comparing the molecular signature kernels to three of the BLOSUM matrices (30, 62, and 90) to test the accuracy of the mathematical model. The kernel matrix was manipulated in order to improve the relationship by focusing on side groups and also by changing how the structure was represented in the matrix by increasing the initial height distance from the central atom (Height 1 and Height 2 included).
There were multiple design constraints for this project. The first was the comparison with the BLOSUM matrices (30, 62, …
On The Origin Of Protein Superfamilies And Superfolds, Abram Magner, Wojciech Szpankowski, Daisuke Kihara
On The Origin Of Protein Superfamilies And Superfolds, Abram Magner, Wojciech Szpankowski, Daisuke Kihara
Department of Biological Sciences Faculty Publications
Distributions of protein families and folds in genomes are highly skewed, having a small number of prevalent superfamiles/superfolds and a large number of families/folds of a small size. Why are the distributions of protein families and folds skewed? Why are there only a limited number of protein families? Here, we employ an information theoretic approach to investigate the protein sequence-structure relationship that leads to the skewed distributions. We consider that protein sequences and folds constitute an information theoretic channel and computed the most efficient distribution of sequences that code all protein folds. The identified distributions of sequences and folds are …
Applications Of Machine Learning In Biology And Medicine, Saied Haidarian Shahri
Applications Of Machine Learning In Biology And Medicine, Saied Haidarian Shahri
Wayne State University Dissertations
Machine learning as a field is defined to be the set of computational algorithms that improve their performance by assimilating data.
As such, the field as a whole has found applications in many diverse disciplines from robotics and communication in engineering to economics and finance, and also biology and medicine.
It should not come as a surprise that many popular methods in use today have completely different origins.
Despite this heterogeneity, different methods can be divided into standard tasks, such as supervised, unsupervised, semi-supervised and reinforcement learning.
Although machine learning as a field can be formalized as methods trying to …
Efficient Synergistic De Novo Co-Assembly Of Bacterial Genomes From Single Cells Using Colored De Bruijn Graph, Narjes Sadat Movahedi Tabrizi
Efficient Synergistic De Novo Co-Assembly Of Bacterial Genomes From Single Cells Using Colored De Bruijn Graph, Narjes Sadat Movahedi Tabrizi
Wayne State University Dissertations
Recent progress in DNA amplification techniques, particularly multiple displacement
amplification (MDA), has made it possible to sequence and assemble bacterial
genomes from a single cell. However, the quality of single cell genome assembly has
not yet reached the quality of normal multi-cell genome assembly due to the coverage
bias (including uneven depth of coverage and region blackout) and errors caused by
MDA. Computational methods try to mitigates the amplification bias. In this document
we introduce a de novo co-assembly method using colored de Bruijn graph,
which can overcome the problem of blackout regions due to amplification bias. The
algorithm is …
Detection And Tracking Of T Cells In Time-Lapse Imaging, Cody Arbuckle, Milton L. Greenberg, Erik J. Linstead
Detection And Tracking Of T Cells In Time-Lapse Imaging, Cody Arbuckle, Milton L. Greenberg, Erik J. Linstead
Mathematics, Physics, and Computer Science Faculty Articles and Research
The effective classification and tracking of cells obtained from modern staining techniques has significant limitations due to the necessity of having to train and utilize a human expert in the field who must manually identify each cell in each slide. Often times these slides are filled with noise cells that are not of particular interest to the researcher. The use of computational methods has the ability to effectively and efficiently enhance image quality, as well as identify and track target cell types over large data sets. Here we present a computational approach to the in vitro tracking of T cells …
Hash-Map-Eradicator: Filtering Non-Target Sequences From Next Generation Sequencing Reads, Jonathon Brenner, Catherine Putonti
Hash-Map-Eradicator: Filtering Non-Target Sequences From Next Generation Sequencing Reads, Jonathon Brenner, Catherine Putonti
Bioinformatics Faculty Publications
Contemporary DNA sequencing technologies are continuously increasing throughput at ever decreasing costs. Moreover, due to recent advances in sequencing technology new platforms are emerging. As such computational challenges persist. The average read length possible has taken a giant leap forward with the PacBio and Nanopore solutions. Regardless of the platform used, impurities within the DNA preparation of the sample - be it from unintentional contaminants or pervasive symbiots - remains an issue. We have developed a new tool, HAsh-MaP-ERadicator (HAMPER), for the detection and removal of non-target, contaminating DNA sequences. Integrating hash-based and mapping-based strategies, HAMPER is both memory and …
A Robust Deep Model For Improved Classification Of Ad/Mci Patients, Feng Li, Loc Tran, Kim-Han Thung, Shuiwang Ji, Dinggang Shen, Jiang Li
A Robust Deep Model For Improved Classification Of Ad/Mci Patients, Feng Li, Loc Tran, Kim-Han Thung, Shuiwang Ji, Dinggang Shen, Jiang Li
Electrical & Computer Engineering Faculty Publications
Accurate classification of Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI), plays a critical role in possibly preventing progression of memory impairment and improving quality of life for AD patients. Among many research tasks, it is of a particular interest to identify noninvasive imaging biomarkers for AD diagnosis. In this paper, we present a robust deep learning system to identify different progression stages of AD patients based on MRI and PET scans. We utilized the dropout technique to improve classical deep learning by preventing its weight coadaptation, which is a typical cause of overfitting in deep learning. …
Learning Emotions: A Software Engine For Simulating Realistic Emotion In Artificial Agents, Douglas Code
Learning Emotions: A Software Engine For Simulating Realistic Emotion In Artificial Agents, Douglas Code
Senior Independent Study Theses
This paper outlines a software framework for the simulation of dynamic emotions in simulated agents. This framework acts as a domain-independent, black-box solution for giving actors in games or simulations realistic emotional reactions to events. The emotion management engine provided by the framework uses a modified Fuzzy Logic Adaptive Model of Emotions (FLAME) model, which lets it manage both appraisal of events in relation to an individual’s emotional state, and learning mechanisms through which an individual’s emotional responses to a particular event or object can change over time. In addition to the FLAME model, the engine draws on the design …
Graph-Based Regularization In Machine Learning: Discovering Driver Modules In Biological Networks, Xi Gao
Graph-Based Regularization In Machine Learning: Discovering Driver Modules In Biological Networks, Xi Gao
Theses and Dissertations
Curiosity of human nature drives us to explore the origins of what makes each of us different. From ancient legends and mythology, Mendel's law, Punnett square to modern genetic research, we carry on this old but eternal question. Thanks to technological revolution, today's scientists try to answer this question using easily measurable gene expression and other profiling data. However, the exploration can easily get lost in the data of growing volume, dimension, noise and complexity. This dissertation is aimed at developing new machine learning methods that take data from different classes as input, augment them with knowledge of feature relationships, …
Saccharomyces Boulardii And Bismuth Subsalicylate As Low-Cost Interventions To Reduce The Duration And Severity Of Cholera, Johnathan Sheele, Jessica Cartowski, Angela Dart, Arjun Poddar, Shikha Gupta, Ajay Gupta
Saccharomyces Boulardii And Bismuth Subsalicylate As Low-Cost Interventions To Reduce The Duration And Severity Of Cholera, Johnathan Sheele, Jessica Cartowski, Angela Dart, Arjun Poddar, Shikha Gupta, Ajay Gupta
Computer Science Faculty Publications
We conducted a randomised single-blinded clinical trial of 100 cholera patients in Port-au-Prince, Haiti to determine if the probiotic Saccharomyces cerevisiae var. boulardii and the anti-diarrhoeal drug bismuth subsalicylate (BS) were able to reduce the duration and severity of cholera. Subjects received either: S. boulardii 250 mg, S. boulardii 250 mg capsule plus BS 524 mg tablet, BS 524 mg, or two placebo capsules every 6 hours alongside standard treatment for cholera. The length of hospitalisation plus the number and volume of emesis, stool and urine were recorded every 6 hours until the study subject was discharged (n=83), left against …
De Novo Protein Structure Modeling And Energy Function Design, Lin Chen
De Novo Protein Structure Modeling And Energy Function Design, Lin Chen
Computer Science Theses & Dissertations
The two major challenges in protein structure prediction problems are (1) the lack of an accurate energy function and (2) the lack of an efficient search algorithm. A protein energy function accurately describing the interaction between residues is able to supervise the optimization of a protein conformation, as well as select native or native-like structures from numerous possible conformations. An efficient search algorithm must be able to reduce a conformational space to a reasonable size without missing the native conformation. My PhD research studies focused on these two directions.
A protein energy function—the distance and orientation dependent energy function of …
Fresh Bytes - Connected Hydroponics For Small-Scale Growing, Jack Bowen
Fresh Bytes - Connected Hydroponics For Small-Scale Growing, Jack Bowen
Liberal Arts and Engineering Studies
Many users are now transitioning to small-scale hydroponics and aquaponics at home. There can be a barrier to entry with these systems as there is a delicate balance of chemicals, pH, etc. that must be maintained. There are sensors for these various components but they are either aimed at commercial production or are un-automated. Fresh Bytes is a microcomputer with sensors to detect all of these unseen components in a hydroponic system. A prototype of this microcomputer is produced along with CAD plans for more professional versions of it. The sensors are verified and future development is contemplated.
Anonymized Video Analysis Methods And Systems, Marjorie Skubic, James M. Keller, Fang Wang, Derek T. Anderson, Erik Stone, Robert H. Luke Iii, Tanvi Banerjee, Marilyn J. Rantz
Anonymized Video Analysis Methods And Systems, Marjorie Skubic, James M. Keller, Fang Wang, Derek T. Anderson, Erik Stone, Robert H. Luke Iii, Tanvi Banerjee, Marilyn J. Rantz
Kno.e.sis Publications
Methods and systems for anonymized video analysis are described. In one embodiment, a first silhouette image of a person in a living unit may be accessed. The first silhouette image may be based on a first video signal recorded by a first video camera. A second silhouette image of the person in the living unit may be accessed. The second silhouette image may be of a different view of the person than the first silhouette image. The second silhouette image may be based on a second video signal recorded by a second video camera. A three-dimensional model of the person …
Protecting Web Servers From Web Robot Traffic, Derek Doran
Protecting Web Servers From Web Robot Traffic, Derek Doran
Kno.e.sis Publications
No abstract provided.
Triad-Based Role Discovery For Large Social Systems, Derek Doran
Triad-Based Role Discovery For Large Social Systems, Derek Doran
Kno.e.sis Publications
The social role of a participant in a social system conceptualizes the circumstances under which she chooses to interact with others, making their discovery and analysis important for theoretical and practical purposes. In this paper, we propose a methodology to detect such roles by utilizing the conditional triad censuses of ego-networks. These censuses are a promising tool for social role extraction because they capture the degree to which basic social forces push upon a user to interact with others in a system. Clusters of triad censuses, inferred from network samples that preserve local structural properties, define the social roles. The …
Gwatch: A Web Platform For Automated Gene Association Discovery Analysis, Anton Svitin, Sergey Malov, Nikolay Cherkasov, Paul Geerts, Mikhail Rotkevich, Pavel Dobrynin, Andrey Shevchenko, Li Guan, Jennifer L. Troyer, Sher L. Hendrickson, Holli Hutcheson Dilks, T. K. Oleksyk, Sharyne Donfield, Edward Gomperts, Douglas A. Jabs, Efe Sezgin, Mark Van Natta, P. Richard Harrigan, Zabrina L. Brumme, Stephen J. O'Brien
Gwatch: A Web Platform For Automated Gene Association Discovery Analysis, Anton Svitin, Sergey Malov, Nikolay Cherkasov, Paul Geerts, Mikhail Rotkevich, Pavel Dobrynin, Andrey Shevchenko, Li Guan, Jennifer L. Troyer, Sher L. Hendrickson, Holli Hutcheson Dilks, T. K. Oleksyk, Sharyne Donfield, Edward Gomperts, Douglas A. Jabs, Efe Sezgin, Mark Van Natta, P. Richard Harrigan, Zabrina L. Brumme, Stephen J. O'Brien
Biology Faculty Articles
Background: As genome-wide sequence analyses for complex human disease determinants are expanding, it is increasingly necessary to develop strategies to promote discovery and validation of potential disease-gene associations.
Findings: Here we present a dynamic web-based platform – GWATCH – that automates and facilitates four steps in genetic epidemiological discovery: 1) Rapid gene association search and discovery analysis of large genome-wide datasets; 2) Expanded visual display of gene associations for genome-wide variants (SNPs, indels, CNVs), including Manhattan plots, 2D and 3D snapshots of any gene region, and a dynamic genome browser illustrating gene association chromosomal regions; 3) Real-time validation/replication …
Design Of Randomized Experiments In Networks, Dylan Walker, Lev Muchnik
Design Of Randomized Experiments In Networks, Dylan Walker, Lev Muchnik
Business Faculty Articles and Research
Over the last decade, the emergence of pervasive online and digitally enabled environments has created a rich source of detailed data on human behavior. Yet, the promise of big data has recently come under fire for its inability to separate correlation from causation-to derive actionable insights and yield effective policies. Fortunately, the same online platforms on which we interact on a day-to-day basis permit experimentation at large scales, ushering in a new movement toward big experiments. Randomized controlled trials are the heart of the scientific method and when designed correctly provide clean causal inferences that are robust and reproducible. However, …
Discovering Perceptions In Online Social Media: A Probabilistic Approach, Derek Doran, Swapna S. Gokhale, Aldo Dagnino
Discovering Perceptions In Online Social Media: A Probabilistic Approach, Derek Doran, Swapna S. Gokhale, Aldo Dagnino
Kno.e.sis Publications
People across the world habitually turn to online social media to share their experiences, thoughts, ideas, and opinions as they go about their daily lives. These posts collectively contain a wealth of insights into how masses perceive their surroundings. Therefore, extracting people’s perceptions from social media posts can provide valuable information about pertinent issues such as public transportation, emergency conditions, and even reactions to political actions or other activities. This paper proposes a novel approach to extract such perceptions from a corpus of social media posts originating from a given broad geographical region. The approach divides the broad region into …
Online Information Searching For Cardiovascular Diseases: An Analysis Of Mayo Clinic Search Query Logs, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak
Online Information Searching For Cardiovascular Diseases: An Analysis Of Mayo Clinic Search Query Logs, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak
Kno.e.sis Publications
Since the early 2000’s, Internet usage for health information searching has increased significantly. Studying search queries can help us to understand users “information need” and how do they formulate search queries (“expression of information need”). Although cardiovascular diseases (CVD) affect a large percentage of the population, few studies have investigated how and what users search for CVD. We address this knowledge gap in the community by analyzing a large corpus of 10 million CVD related search queries from MayoClinic.com. Using UMLS MetaMap and UMLS semantic types/concepts, we developed a rule-based approach to categorize the queries into 14 health categories. We …
An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak
An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak
Kno.e.sis Publications
Increasingly, individuals are taking active participation in learning and managing their health by leveraging online resources. Understanding online health information searching behavior can help us to study what health topics users search for and how search queries are formulated. In this work, we analyzed 10 million cardiovascular diseases (CVD) related search queries from MayoClinic.com. We performed semantic analysis on the queries using UMLS MetaMap and analyzed structural and textual properties as well as linguistic characteristics of the queries.
Improving The Efficacy Of Web-Based Educational Outreach In Ecology, Gregory R. Goldsmith, Andrew D. Fulton, Colin D. Witherill, Javier F. Espeleta
Improving The Efficacy Of Web-Based Educational Outreach In Ecology, Gregory R. Goldsmith, Andrew D. Fulton, Colin D. Witherill, Javier F. Espeleta
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Scientists are increasingly engaging the web to provide formal and informal science education opportunities. Despite the prolific growth of web-based resources, systematic evaluation and assessment of their efficacy remains limited. We used clickstream analytics, a widely available method for tracking website visitors and their behavior, to evaluate 60,000 visits over three years to an educational website focused on ecology. Visits originating from search engine queries were a small proportion of the traffic, suggesting the need to actively promote websites to drive visitation. However, the number of visits referred to the website per social media post varied depending on the social …
Taming The Software Chaos: True To Its Promise, Iftdss Eases The Burden Of Fuels Treatment Planning—And Does A Lot More Besides, Gail Wells
Joint Fire Science Program Digests
A key problem reported by the fuels treatment planning community is the difficulty and inefficiency of evaluating and then applying many planning tools and applications. Fuels specialists have struggled to find, load, and learn all the different fuels and fire planning models, not to mention the interface of running, adjusting, and inputting data specific to each model without the ability to easily share inputs/outputs between models.
The Interagency Fuels Treatment Decision Support System (IFTDSS) was conceived as a way for users to learn one interface, access a variety of data and models all in one place, and pass data (inputs …
Generalized Theoretical Criteria For Annihilation Of Hiv-1 Virions During Haart, Frank Nani, Mingxian Jin
Generalized Theoretical Criteria For Annihilation Of Hiv-1 Virions During Haart, Frank Nani, Mingxian Jin
Math and Computer Science Faculty Working Papers
Aims: This paper is an elaborate and quantitative attempt to construct medically applicable mathematical models and derive criteria for efficacious Highly Active Anti-Retroviral Therapy (HAART) protocol for an AIDS patient. The patho-physiological dynamics of Human Immuno-deficiency Virus type 1 (HIV-1) induced AIDS during HAART is modeled by a system of non-linear deterministic differential equations. The physiologically relevant and clinically plausible equations depict the dynamics of uninfected CD4+ T cells (x1), HIV-1 infected CD4+ T cells (x2), HIV-1 virions in the blood plasma (x3), HIV-1 specific CD8+ T cells (x4), and the concentration of HAART drug molecules (x5). The major objective …
Data Analytics For Power Utility Storm Planning, Lan Lin, Aldo Dagnino, Derek Doran, Swapna S. Gokhale
Data Analytics For Power Utility Storm Planning, Lan Lin, Aldo Dagnino, Derek Doran, Swapna S. Gokhale
Kno.e.sis Publications
As the world population grows, recent climatic changes seem to bring powerful storms to populated areas. The impact of these storms on utility services is devastating. Hurricane Sandy is a recent example of the enormous damages that storms can inflict on infrastructure, society, and the economy. Quick response to these emergencies represents a big challenge to electric power utilities. Traditionally utilities develop preparedness plans for storm emergency situations based on the experience of utility experts and with limited use of historical data. With the advent of the Smart Grid, utilities are incorporating automation and sensing technologies in their grids and …
Discretized Agent-Based Model Of Infectious Disease Spread That Uses Contact Probability, Tyrell L. Gardner
Discretized Agent-Based Model Of Infectious Disease Spread That Uses Contact Probability, Tyrell L. Gardner
Computational Modeling & Simulation Engineering Theses & Dissertations
This study uses contact probability in an agent-based model to simulate the spread of an infectious disease. In order to perform the study, the agent-based model must first be discretized into events. Each agent in the model is given its own infectious disease state machine taken from the Susceptible-Exposed-Infected-Recovered (SEIR) model. The agents move between squares in a grid environment where each square represents a group. Groups have a contact probability as an attribute that is used to predict whether an agent comes in close contact with another agent. The transitions between the states in the SEIR model are easily …
Evaluation Of Microarray-Based Dna Methylation Measurement Using Technical Replicates: The Atherosclerosis Risk In Communities (Aric) Study, Maitreyee Bose, Chong Wu, James S. Pankow, Ellen W. Demerath, Jan Bressler, Myriam Fornage, Megan L. Grove, Thomas H. Mosley, Chindo Hicks, Kari North, Wen Hong Kao, Yu Zhang, Eric Boerwinkle, Weihua Guan
Evaluation Of Microarray-Based Dna Methylation Measurement Using Technical Replicates: The Atherosclerosis Risk In Communities (Aric) Study, Maitreyee Bose, Chong Wu, James S. Pankow, Ellen W. Demerath, Jan Bressler, Myriam Fornage, Megan L. Grove, Thomas H. Mosley, Chindo Hicks, Kari North, Wen Hong Kao, Yu Zhang, Eric Boerwinkle, Weihua Guan
Computer Science Faculty Publications
Background: DNA methylation is a widely studied epigenetic phenomenon; alterations in methylation patterns influence human phenotypes and risk of disease. As part of the Atherosclerosis Risk in Communities (ARIC) study, the Illumina Infinium HumanMethylation450 (HM450) BeadChip was used to measure DNA methylation in peripheral blood obtained from ~3000 African American study participants. Over 480,000 cytosine-guanine (CpG) dinucleotide sites were surveyed on the HM450 BeadChip. To evaluate the impact of technical variation, 265 technical replicates from 130 participants were included in the study.
Results: For each CpG site, we calculated the intraclass correlation coefficient (ICC) to compare variation of methylation levels …