Computer Sciences Commons^™

Graph Mining For Next Generation Sequencing: Leveraging The Assembly Graph For Biological Insights, Julia Warnke-Sommer, Hesham Ali

Computer Science Faculty Publications

Background: The assembly of Next Generation Sequencing (NGS) reads remains a challenging task. This is especially true for the assembly of metagenomics data that originate from environmental samples potentially containing hundreds to thousands of unique species. The principle objective of current assembly tools is to assemble NGS reads into contiguous stretches of sequence called contigs while maximizing for both accuracy and contig length. The end goal of this process is to produce longer contigs with the major focus being on assembly only. Sequence read assembly is an aggregative process, during which read overlap relationship information is lost as reads are …

A Support Vector Machine Base Model For Predicting Heparin-Binding Proteins Using Biological Metrics And Xb Patterns As Features, Joseph W. Sirrianni

Computer Science and Computer Engineering Undergraduate Honors Theses

Heparin is a highly sulphated and negatively charged polysaccharides belonging to the glycosamino- glycans(GAGs) family. It is widely used in medical treatments as an injectable anticoagulant. Although many heparin-binding proteins have been identified through experimental studies, there are still many proteins needing to be classified as heparin-binding or not. Many studies have been aimed at prediction of heparin binding patterns or motifs in the primary structure of proteins. For example XBBXBX and XBBBXXBX are two well-known patterns or motifs. In spite of intensive studies, still no good model has emerged which reasonably predicts proteins in the protein database as heparin-binding …

Chipathlon: A Competitive Assessment For Gene Regulation Tools, Avi Knecht, Adam Caprez, Istvan Ladunga

UCARE: Research Products

When gene regulation of the cell cycle malfunctions, it frequently causes cancer.

Adult, differentiated cells can be reprogrammed to induced pluripotent stem cell; which can then be reprogrammed to heart muscle, skin, etc, to repair damaged tissue (to limited extent in clinical practice).

ChIPathlon: Evaluate the performance of all transcription factor mapping (peak calling) methods. To this end, we will develop a scalable and easy to use super computing pipeline to stage data, compare many different peak calling and differential binding site tools, and store all results into a single database.

Scalable Parallelization Of A Markov Coalescent Genealogy Sampler, Philip E. Davis

Masters Theses

Coalescent genealogy samplers are effective tools for the study of population genetics. They are used to estimate the historical parameters of a population based upon the sampling of present-day genetic information. A popular approach employs Markov chain Monte Carlo (MCMC) methods. While effective, these methods are very computationally intensive, often taking weeks to run. Although attempts have been made to leverage parallelism in an effort to reduce runtimes, they have not resulted in scalable solutions. Due to the inherently sequential nature of MCMC methods, their performance has suffered diminishing returns when applied to large-scale computing clusters. In the interests of …

Volume 08, Meghan Enzinna, Casey Dawn Gailey, Raven Collins, Chiara Enriquez, Amelia Mcconnell, Alexander Morton, Emma Beckett, Leah G. Parr, Briana Adhikusuma, Taylor Embrey, Rowan Davis, Danielle Sisson, Bianca Cherry, Melissa Cacho, Chloe Woodward, Catherine Rollins, Carson Reeher, Landon Cooper, Haley Vasquez, Marlisha Stewart, Eric Whitehead, Sabrina Walker, James Bates

Incite: The Journal of Undergraduate Scholarship

Introduction from Interim Dean Dr. Jennifer Apperson

Indigenous Peoples and the Modern Era by Meghan Enzinna

"Who Says": How Selena Gomez and the Scene Attempt to Subvert the Popular Standards of Beauty by Casey Dawn Gailey

Art by Raven Collins

Meltdown on Social Media: Amy's Baking Company Meets Kitchen Nightmares by Nathena Haddrill

Art by Chiara Enriquez

Design by Amelia Mcconnell

Worth More Than a Thousand Words: A Visual Rhetorical Discussion of Virtual Reality by Examining "Clouds Over Sidra" by Alexander Morton

Design by Emma Beckett

The Sonata: An Analysis of Piano Sonata No. 14 in C Minor, K. …

Bottom-Up Ggm Algorithm For Constructing Multilayered Hierarchical Gene Regulatory Networks That Govern Biological Pathways Or Processes, Sapna Kupari, Wenping Deng, Chathura J. Gunasekara, Vincent Chiang, Huann-Sheng Chen, Hairong Wei, Et. Al.

Michigan Tech Publications, Part 1

Background: Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways.

Results: A bottom-up graphic Gaussian model (GGM) algorithm was developed for constructing ML-hGRN operating above a biological pathway using small- to medium-sized microarray or RNA-seq data sets. The algorithm first placed genes of a pathway at the bottom layer and began to construct an ML-hGRN by evaluating all combined triple genes: two pathway genes and one regulatory gene. The algorithm retained all triple genes where a regulatory …

A Mitochondrial Dna-Based Computational Model Of The Spread Of Human Populations, Peter Revesz

School of Computing: Faculty Publications

This paper presents a mitochondrial DNA-based computational model of the spread of human populations. The computation model is based on a new measure of the relatedness of two populations that may be both heterogeneous in terms of their set of mtDNA haplogroups. The measure gives an exponentially increasing weight for the similarity of two haplogroups with the number of levels shared in the mtDNA classification tree. In an experiment, the computational model is applied to the study of the relatedness of seven human populations ranging from the Neolithic through the Bronze Age to the present. The human populations included in …

Developing Probability Maps For Locating And Scouting Unprotected Areas Of Gravel Hill Prairies On Rodman Soils Along The Wabash River Valley Near Lafayette, Indiana, Ryan W.R. Schroeder

Engagement & Service-Learning Summit

No abstract provided.

Data Publication With The Structural Biology Data Grid Supports Live Analysis, Peter A. Meyer, Stephanie Socias, Jason Key, Elizabeth Ransey, Emily C. Tjon, Alejandro Buschiazzo, Ming Lei, Chris Botka, James Withrow, David Neau, Kanagalaghatta Rajashankar, Karen S. Anderson, Chung-I Chang, Walter J. Chazin, Kevin D. Corbett, Michael S. Cosgrove, Sean Crosson, Sirano Dhe-Paganon, Enrico Di Cera, Catherine L. Drennan, Michael J. Eck, Brandt F. Eichman, Qing R. Fan, Adrian R. Ferre-D’Amare, J. Christopher Fromme, K. Christopher Garcia, Rachelle Gaudet, Peng Gong, Stephen C. Harrison, Ekaterina E. Heldwein, Zongchao Jia, Robert J. Keenan, Andrew C. Kruse, Marc Kvansaku, Jason S. Mclellan

Dartmouth Scholarship

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the …

Semantic, Cognitive, And Perceptual Computing: Paradigms That Shape Human Experience, Amit P. Sheth, Pramod Anantharam, Cory Henson

Kno.e.sis Publications

Unlike machine-centric computing, in which efficient data processing takes precedence over contextual tailoring, human-centric computation provides a personalized data interpretation that most users find highly relevant to their needs. The authors show how semantic, cognitive, and perceptual computing paradigms work together to produce actionable information.

A Systems Approach To Animal Communication, Eileen A. Hebets, Andrew B. Barron, Christopher N. Balakrishnan, Mark E. Hauber, Paul H. Mason, Kim L. Hoke

Eileen Hebets Publications

Why animal communication displays are so complex and how they have evolved are active foci of research with a long and rich history. Progress towards an evolutionary analysis of signal complexity, however, has been constrained by a lack of hypotheses to explain similarities and/or differences in signalling systems across taxa. To address this, we advocate incorporating a systems approach into studies of animal communication—an approach that includes comprehensive experimental designs and data collection in combination with the implementation of systems concepts and tools. A systems approach evaluates overall display architecture, including how components interact to alter function, and how function …

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …

A Polyglot Approach To Bioinformatics Data Integration: A Phylogenetic Analysis Of Hiv-1, Steven Reisman, Thomas Hatzopoulous, Konstantin Läufer, George K. Thiruvathukal, Catherine Putonti

Computer Science: Faculty Publications and Other Works

As sequencing technologies continue to drop in price and increase in throughput, new challenges emerge for the management and accessibility of genomic sequence data. We have developed a pipeline for facilitating the storage, retrieval, and subsequent analysis of molecular data, integrating both sequence and metadata. Taking a polyglot approach involving multiple languages, libraries, and persistence mechanisms, sequence data can be aggregated from publicly available and local repositories. Data are exposed in the form of a RESTful web service, formatted for easy querying, and retrieved for downstream analyses. As a proof of concept, we have developed a resource for annotated HIV-1 …

Image Harvest: An Open-Source Platform For High-Throughput Plant Image Processing And Analysis, Avi C. Knecht, Malachy T. Campbell, Adam Caprez, David R. Swanson, Harkamal Walia

Holland Computing Center: Faculty Publications

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources …

Exploring Factors Influencing Information Technology Portfolio Selection Process In Government-Funded Bioinformatics Projects, Braulio J. Cabral

Walden Dissertations and Doctoral Studies

In 2012, the National Cancer Institute's (NCI) Board of Scientific Advisors (BSA) conducted a review of the Center for Biomedical Informatics and Information Technology's (CBIIT) bioinformatics program. The BSA suggested that the lack of a formal project selection process made it difficult to determine the alignment of projects with the mission of the organization. The problem addressed by this study was that CBIIT did not have an in-depth understanding of the project selection process and the factors influencing the process. The purpose of this study was to understand the project selection process at CBIIT. The research methodology was an exploratory …

A Study Of Social Web Data On Buprenorphine Abuse Using Semantic Web Technology, Raminta Daniulaityte, Amit P. Sheth

Kno.e.sis Publications

The Specific Aims of this application are to use a paradigmatic approach that combines Semantic Web technology, Natural Language Processing and Machine Learning techniques to:

1) Describe drug users’ knowledge, attitudes, and behaviors related to the non-medical use of Suboxone and Subutex as discussed on Web-based forums.
2) Identify and describe temporal patterns of non-medical use of Suboxone and Subutex as discussed on Web-based forums.

The research was carried out by an interdisciplinary team of members of the Center for Interventions, Treatment and Addictions Research (CITAR) and the Ohio Center of Excellence in Knowledge- enabled Computing (Kno.e.sis) at Wright State …

Building The Web Of Knowledge With Smart Iot Applications, Amelie Gyrard, Pankesh Patel, Amit P. Sheth, Martin Serrano

Kno.e.sis Publications

The Internet of Things (IoT) is experiencing fast adoption because of its positive impact to change all aspects of our lives, from agriculture in rural areas, to health and wellness, to smart home and smart-x applications in cities. The development of IoT applications and deployment of smart IoT-based solutions is just starting; smart IoT applications will modify our physical world and our interaction with cyber spaces, from how we remotely control appliances at home to how we care for patients or elderly persons. The massive deployment of IoT devices represents a tremendous economic impact and at the same time offers …

Co-Evolution Of Rdf Datasets, Sidra Faisal, Kemele M. Endris, Saeedeh Shekarpour, Sören Auer, Maria-Esther Vidal

Kno.e.sis Publications

Linking Data initiatives have fostered the publication of large number of RDF datasets in the Linked Open Data (LOD) cloud, as well as the development of query processing infrastructures to access these data in a federated fashion. However, different experimental studies have shown that availability of LOD datasets cannot be always ensured, being RDF data replication required for envisioning reliable federated query frameworks. Albeit enhancing data availability, RDF data replication requires synchronization and conflict resolution when replicas and source datasets are allowed to change data over time, i.e., co-evolution management needs to be provided to ensure consistency. In this paper, …

Selective Mutation Accumulation: A Computational Model Of The Paternal Age Effect, Eoin C. Whelan, Alexander C. Nwala, Christopher Osgood, Stephan Olariu

Biological Sciences Faculty Publications

Motivation: As the mean age of parenthood grows, the effect of parental age on genetic disease and child health becomes ever more important. A number of autosomal dominant disorders show a dramatic paternal age effect due to selfish mutations: substitutions that grant spermatogonial stem cells (SSCs) a selective advantage in the testes of the father, but have a deleterious effect in offspring. In this paper we present a computational technique to model the SSC niche in order to examine the phenomenon and draw conclusions across different genes and disorders.

Results: We used a Markov chain to model the probabilities of …

Assessing Accuracies And Improving Efficiency For Segmentation-Based Rna Secondary Structure Prediction Methods, Gerardo A. Cardenas

Open Access Theses & Dissertations

RNA secondary structure prediction has become an important area of interest in biology and medicine because it helps in understanding the mechanisms of many biological processes such as gene regulation and viral replication, and in designing RNA-based therapies to treat various diseases such as cancers and AIDS. Different thermodynamics-based computational algorithms for RNA structure prediction exist, and have been used to help understand the disease mechanisms and design treatments. However, most of these computational tools that can predict complex pseudoknot structures have a sequence length limitation of few hundred nucleotide bases due to their high demands of computer resources. Yet, …

A Flexible Pet-Based Wearable Sensor For Arterial Pulse Waveform Measurement, Dan Wang, Dean Krusienski, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

In light of the need of health monitoring, the paper presents a flexible polyethylene terephthalate (PET)-based wearable sensor for arterial pulse waveform measurement. The sensor encompasses a polydimethylsiloxane (PDMS) microstructure embedded with an electrolyte-enabled 5×1 transducer array, which spans 6mm and has a spatial resolution of 1.5mm. A pulse signal exerts a deflection on the microstructure and is recorded as a resistance change by a transducer at the site of the pulse. An untrained individual can easily align the sensor on a targeted artery with a negligible margin and then acquire the arterial pulse waveform continuously and non-invasively. This sensor …

Missing Gene Identification Using Functional Coherence Scores, Meghana Chitale, Ishita K. Khan, Daisuke Kihara

Department of Biological Sciences Faculty Publications

Reconstructing metabolic and signaling pathways is an effective way of interpreting a genome sequence. A challenge in a pathway reconstruction is that often genes in a pathway cannot be easily found, reflecting current imperfect information of the target organism. In this work, we developed a new method for finding missing genes, which integrates multiple features, including gene expression, phylogenetic profile, and function association scores. Particularly, for considering function association between candidate genes and neighboring proteins to the target missing gene in the network, we used Co-occurrence Association Score (CAS) and PubMed Association Score (PAS), which are designed for capturing functional …

Evaluating And Improving The Efficiency Of Software And Algorithms For Sequence Data Analysis, Hugh L. Eaves

Theses and Dissertations

With the ever-growing size of sequence data sets, data processing and analysis are an increasingly large portion of the time and money spent on nucleic acid sequencing projects. Correspondingly, the performance of the software and algorithms used to perform that analysis has a direct effect on the time and expense involved. Although the analytical methods are widely varied, certain types of software and algorithms are applicable to a number of areas. Targeting improvements to these common elements has the potential for wide reaching rewards. This dissertation research consisted of several projects to characterize and improve upon the efficiency of several …

Rcd+: Fast Loop Modeling Server, José R. López-Blanco, Alejandro J. Canosa-Valis, Yaohang Li, Pablo Chacón

Computer Science Faculty Publications

Modeling loops is a critical and challenging step in protein modeling and prediction. We have developed a quick online service (http://rcd.chaconlab.org) for ab initio loop modeling combining a coarse-grained conformational search with a full-atom refinement. Our original Random Coordinate Descent (RCD) loop closure algorithm has been greatly improved to enrich the sampling distribution towards near-native conformations. These improvements include a new workflow optimization, MPI-parallelization and fast backbone angle sampling based on neighbor-dependent Ramachandran probability distributions. The server starts by efficiently searching the vast conformational space from only the loop sequence information and the environment atomic coordinates. The generated closed loop …

Flexc: Protein Flexibility Prediction Using Context-Based Statistics, Predicted Structural Features, And Sequence Information, Ashraf Yaseen, Mais Nijim, Brandon Williams, Lei Qian, Min Li, Jianxin Wang, Yaohang Li

Computer Science Faculty Publications

The fluctuation of atoms around their average positions in protein structures provides important information regarding protein dynamics. This flexibility of protein structures is associated with various biological processes. Predicting flexibility of residues from protein sequences is significant for analyzing the dynamic properties of proteins which will be helpful in predicting their functions.

Deep Models For Brain Em Image Segmentation: Novel Insights And Improved Performance, Ahmed Fakhry, Hanchuan Peng, Shuiwang Ji

Computer Science Faculty Publications

Motivation: Accurate segmentation of brain electron microscopy (EM) images is a critical step in dense circuit reconstruction. Although deep neural networks (DNNs) have been widely used in a number of applications in computer vision, most of these models that proved to be effective on image classification tasks cannot be applied directly to EM image segmentation, due to the different objectives of these tasks. As a result, it is desirable to develop an optimized architecture that uses the full power of DNNs and tailored specifically for EM image segmentation.

Results: In this work, we proposed a novel design of DNNs for …

Synthesis Of Satellite Microwave Observations For Monitoring Global Land-Atmosphere Co2 Exchange, Lucas Alan Jones

Graduate Student Theses, Dissertations, & Professional Papers

This dissertation describes the estimation, error quantification, and incorporation of land surface information from microwave satellite remote sensing for modeling global ecosystem land-atmosphere net CO₂ exchange. Retrieval algorithms were developed for estimating soil moisture, surface water, surface temperature, and vegetation phenology from microwave imagery timeseries. Soil moisture retrievals were merged with model-based soil moisture estimates and incorporated into a light-use efficiency model for vegetation productivity coupled to a soil decomposition model. Results, including state and uncertainty estimates, were evaluated with a global eddy covariance flux tower network and other independent global model- and remote-sensing based products.

Reliability And Validity Of Neurobehavioral Function On The Psychology Experimental Building Language Test Battery In Young Adults, Brian J. Piper, Shane Mueller, Alexander R. Geerken, Kyle L. Dixon, Gregory Kroliczak, Reid H. Olsen, Jeremy K. Miller

Michigan Tech Publications, Part 1

Background. The Psychology Experiment Building Language (PEBL) software consists of over one-hundred computerized tests based on classic and novel cognitive neuropsychology and behavioral neurology measures. Although the PEBL tests are becoming more widely utilized, there is currently very limited information about the psychometric properties of these measures.

Methods. Study I examined inter-relationships among nine PEBL tests including indices of motor-function (Pursuit Rotor and Dexterity), attention (Test of Attentional Vigilance and Time-Wall), working memory (Digit Span Forward), and executive-function (PEBL Trail Making Test, Berg/Wisconsin Card Sorting Test, Iowa Gambling Test, and Mental Rotation) in a normative sample (N = 189, …

Intent Classification Of Short-Text On Social Media, Hemant Purohit, Guozhu Dong, Valerie L. Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Social media platforms facilitate the emergence of citizen communities that discuss real-world events. Their content reflects a variety of intent ranging from social good (e.g., volunteering to help) to commercial interest (e.g., criticizing product features). Hence, mining intent from social data can aid in filtering social media to support organizations, such as an emergency management unit for resource planning. However, effective intent mining is inherently challenging due to ambiguity in interpretation, and sparsity of relevant behaviors in social data. In this paper, we address the problem of multiclass classification of intent with a use-case of social data generated during crisis …

Computational Methods For Biomarker Identification In Complex Disease, Amin Ahmadi Adl

USF Tampa Graduate Theses and Dissertations

In a modern systematic view of biology, cell functions arise from the interaction between molecular components. One of the challenging problems in systems biology with high-throughput measurements is discovering the important components involved in the development and progression of complex diseases, which may serve as biomarkers for accurate predictive modeling and as targets for therapeutic purposes. Due to the non-linearity and heterogeneity of these complex diseases, traditional biomarker identification approaches have had limited success at finding clinically useful biomarkers. In this dissertation we propose novel methods for biomarker identification that explicitly take into account the non-linearity and heterogeneity of complex …