Computer Sciences Commons^™

A Parallelized Implementation Of Cut-And-Solve And A Streamlined Mixed-Integer Linear Programming Model For Finding Genetic Patterns Optimally Associated With Complex Diseases, Michael Yip-Hin Chan

Theses

With the advent of genetic sequencing, there was much hope of finding the inherited elements underlying complex diseases, such as late-onset Alzheimer’s disease (AD), but it has been a challenge to fully uncover the necessary information hidden in the data. A likely contributor to this failure is the fact that the pathogenesis of most complex diseases does not involve single markers working alone, but patterns of genetic markers interacting additively or epistatically. But as we move upwards beyond patterns of size two, it quickly becomes computationally infeasible to examine all combinations in the solution space. A common solution to solving …

Multi-Resolution Analysis Of Large Molecular Structures And Interactions, Kasra Manavi

Computer Science ETDs

Simulation of large molecular structures and their interactions has become a major component of modern biomolecular research. Methods to simulate these type of molecules span a wide array of resolutions, from all atom molecular dynamics to model interaction energetics to systems of linear equations to evaluate population kinetics. In recent years, there has been an acceleration of molecular structural information production, primarily from x-ray crystallography and electron microscopy. This data has provided modelers the ability to produce better representations of these molecular structures. The purpose of this research is to take advantage of this information to develop multi-resolution models for …

Seqothello: Querying Rna-Seq Experiments At Scale, Ye Yu, Jinpeng Liu, Xinan Liu, Yi Zhang, Eamonn Magner, Erik Lehnert, Chen Qian, Jinze Liu

Computer Science Faculty Publications

We present SeqOthello, an ultra-fast and memory-efficient indexing structure to support arbitrary sequence query against large collections of RNA-seq experiments. It takes SeqOthello only 5 min and 19.1 GB memory to conduct a global survey of 11,658 fusion events against 10,113 TCGA Pan-Cancer RNA-seq datasets. The query recovers 92.7% of tier-1 fusions curated by TCGA Fusion Gene Database and reveals 270 novel occurrences, all of which are present as tumor-specific. By providing a reference-free, alignment-free, and parameter-free sequence search system, SeqOthello will enable large-scale integrative studies using sequence-level data, an undertaking not previously practicable for many individual labs.

Linking Gait Dynamics To Mechanical Cost Of Legged Locomotion, David V. Lee, Sarah L. Harris

Life Sciences Faculty Research

For millenia, legged locomotion has been of central importance to humans for hunting, agriculture, transportation, sport, and warfare. Today, the same principal considerations of locomotor performance and economy apply to legged systems designed to serve, assist, or be worn by humans in urban and natural environments. Energy comes at a premium not only for animals, wherein suitably fast and economical gaits are selected through organic evolution, but also for legged robots that must carry sufficient energy in their batteries. Although a robot's energy is spent at many levels, from control systems to actuators, we suggest that the mechanical cost of …

Mathematical Modeling And Simulation With Deep Learning Methods Of Cancer Growth For Patient-Specific Therapy, Vishal Kobla, Joshua P. Smith, Pranav Unni, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Dexterous, Glove-Based Teleoperable Low-Power Soft Robotic Arm For Delicate Deep-Sea Biological Exploration, Brennan T. Phillips, Kaitlyn P. Becker, Shunichi Kurumaya, Kevin C. Galloway, Griffin Whittredge, Daniel M. Vogt, Clark B. Teeple, Michelle H. Rosen, Vincent A. Pieribone, David F. Gruber, Robert J. Wood

Publications and Research

Modern marine biologists seeking to study or interact with deep-sea organisms are confronted with few options beyond industrial robotic arms, claws, and suction samplers. This limits biological interactions to a subset of “rugged” and mostly immotile fauna. As the deep sea is one of the most biologically diverse and least studied ecosystems on the planet, there is much room for innovation in facilitating delicate interactions with a multitude of organisms. The biodiversity and physiology of shallow marine systems, such as coral reefs, are common study targets due to the easier nature of access; SCUBA diving allows for in situ delicate …

Amino Acid Pop-Set: Model File Name: Amino-Acid-Wgrp-Pop_Sc3.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model for protein primary structure. It consists of four amino acids (tryptophan, proline, arginine, and glycine) depicted in stick and space-fill representations, five peptide bonds depicted in space-fill, and an N-terminus and a C-terminus depicted in space-fill. It is designed so that students can make various peptides to explore the amount of space of the electron clouds of the amino acids and bonds, and explore the psi and phi angles for the peptides. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Amino acid pop-set”. This model has …

Lipoprotein Signal Peptidase Ii: Model File Name: 5dir-Lipoii-Reps_Sc1-5.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of lipoprotein signal peptidase II (PDB: 5DIR). It is designed with different regions of the protein depicted in space-filling, ribbon, stick, and backbone-only representations to explore protein secondary structure and illustrate how much space the protein takes up. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Lipoprotein signal peptidase II” and is intended to accompany the “Crambin”, “Cytochrome c” and “3 water molecules” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in …

3 Water Molecules: Model File Name: 3hoh-Final.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of 3 water molecules depicted in space-fill. It is designed to the same scale as the “Lipoprotein signal peptidase II”, “Crambin”, and “Cytochrome c” models to illustrate the amount of space taken up by proteins. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “3 water molecules” and is intended to accompany the “Lipoprotein signal peptidase II”, “Crambin”, and “Cytochrome c” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering …

Crambin: Model File Name: 2fd7-Crambin-Stick_Sc1-5.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of cytochrome c (PDB: 2FD7). It is designed in a stick representation to explore protein secondary structure and how much space the protein takes up. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Crambin” and is intended to accompany the “Lipoprotein signal peptidase II”, “Cytochrome c”, and “3 water molecules” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following material: Processed Versatile Plastic (Strong & Flexible Plastic).

Cytochrome C: Model File Name: 1b7v-Cytc-Stick_Sc1-5.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of cytochrome c (PDB: 1B7V). It is designed in a stick representation to explore protein secondary structure and how much space the protein takes up. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Cytochrome c” and is intended to accompany the “Lipoprotein signal peptidase II”, “Crambin”, and “3 water molecules” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following material: Processed Versatile Plastic (Strong & Flexible Plastic).

Building Iot Based Applications For Smart Cities: How Can Ontology Catalogs Help?, Amelia Gyrard, Antoine Zimmermann, Amit P. Sheth

Kno.e.sis Publications

The Internet of Things (IoT) plays an ever-increasing role in enabling smart city applications. An ontology-based semantic approach can help improve interoperability between a variety of IoT-generated as well as complementary data needed to drive these applications. While multiple ontology catalogs exist, using them for IoT and smart city applications require significant amount of work. In this paper, we demonstrate how can ontology catalogs be more effectively used to design and develop smart city applications? We consider four ontology catalogs that are relevant for IoT and smart cities: 1) READY4SmartCities; 2) linked open vocabulary (LOV); 3) OpenSensingCity (OSC); and 4) …

Using Electronic Health Records To Characterize Prescription Patterns: Focus On Antidepressants In Nonpsychiatric Outpatient Settings, Joseph J. Deferio, Tomer T. Levin, Judith Cukor, Samprit Banerjee, Rozan Abdulrahman, Amit P. Sheth, Neel Mehta, Jyotishman Pathak

Kno.e.sis Publications

Objective

To characterize nonpsychiatric prescription patterns of antidepressants according to drug labels and evidence assessments (on-label, evidence-based, and off-label) using structured outpatient electronic health record (EHR) data. Methods

A retrospective analysis was conducted using deidentified EHR data from an outpatient practice at a New York City-based academic medical center. Structured “medication–diagnosis” pairs for antidepressants from 35 325 patients between January 2010 and December 2015 were compared to the latest drug product labels and evidence assessments. Results

Of 140 929 antidepressant prescriptions prescribed by primary care providers (PCPs) and nonpsychiatry specialists, 69% were characterized as “on-label/evidence-based uses.” Depression diagnoses were associated …

Poster: Privacy-Preserving Boosting With Random Linear Classifiers, Sagar Sharma, Keke Chen

Kno.e.sis Publications

We propose SecureBoost, a privacy-preserving predictive modeling framework, that allows service providers (SPs) to build powerful boosting models over encrypted or randomly masked user submit- ted data. SecureBoost uses random linear classifiers (RLCs) as the base classifiers. A Cryptographic Service Provider (CSP) manages keys and assists the SP’s processing to reduce the complexity of the protocol constructions. The SP learns only the base models (i.e., RLCs) and the CSP learns only the weights of the base models and a limited leakage function. This separated parameter holding avoids any party from abusing the final model or conducting model-based attacks. We evaluate …

Human Hexokinase I - Allosteric Regulation: Model File Name: 1dgk-Editb22-Allostery_Sc06.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of human Hexokinase I in a surface representation with small molecules ADP and G6P included (PDB: 1DGK). It is designed to be hollow with a lever to mimic allosteric regulation. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Human Hexokinase I - Allosteric regulation model”. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following material: Processed Versatile Plastic (Strong & Flexible Plastic).

Imapsplice: Alleviating Reference Bias Through Personalized Rna-Seq Alignment, Xinan Liu, James N. Macleod, Jinze Liu

Computer Science Faculty Publications

Genomic variants in both coding and non-coding sequences can have functionally important and sometimes deleterious effects on exon splicing of gene transcripts. For transcriptome profiling using RNA-seq, the accurate alignment of reads across exon junctions is a critical step. Existing algorithms that utilize a standard reference genome as a template sometimes have difficulty in mapping reads that carry genomic variants. These problems can lead to allelic ratio biases and the failure to detect splice variants created by splice site polymorphisms. To improve RNA-seq read alignment, we have developed a novel approach called iMapSplice that enables personalized mRNA transcriptome profiling. The …

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, …

Evaluation Of Drug-Loaded Gold Nanoparticle Cytotoxicity As A Function Of Tumor Tissue Heterogeneity., Hunter Allan Miller

Electronic Theses and Dissertations

The inherent heterogeneity of tumor tissue presents a major challenge to nanoparticle-medicated drug delivery. This heterogeneity spans from the molecular to the cellular (cell types) and to the tissue (vasculature, extra-cellular matrix) scales. Here we employ computational modeling to evaluate therapeutic response as a function of vascular-induced tumor tissue heterogeneity. Using data with three-layered gold nanoparticles loaded with cisplatin, nanotherapy is simulated with different levels of tissue heterogeneity, and the treatment response is measured in terms of tumor regression. The results show that tumor vascular density non-trivially influences the nanoparticle uptake and washout, and the associated tissue response. The drug …

Creating Real-Time Dynamic Knowledge Graphs, Swati Padhee, Sarasi Lalithsena, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

New Methods To Improve Protein Structure Modeling, Maha Abdelrasoul

Computer Science Theses & Dissertations

Proteins are considered the central compound necessary for life, as they play a crucial role in governing several life processes by performing the most essential biological and chemical functions in every living cell. Understanding protein structures and functions will lead to a significant advance in life science and biology. Such knowledge is vital for various fields such as drug development and synthetic biofuels production.

Most proteins have definite shapes that they fold into, which are the most stable state they can adopt. Due to the fact that the protein structure information provides important insight into its functions, many research efforts …

Inference And Analysis Of Multilayered Mirna-Mediated Networks In Cancer, Duc Do

Dissertations (1934 -)

MicroRNAs (miRNAs) are small noncoding transcripts that can regulate gene expression, thereby controlling diverse biological processes. Aberrant disruptions of miRNA expression and their interactions with other biological agents (e.g., coding and noncoding transcripts) have been associated with several types of cancer. The goal of this dissertation is to use multidimensional genomic data to model two different gene regulation mechanisms by miRNAs in cancer. This dissertation results from two research projects. The first project investigates a miRNA-mediated gene regulation mechanism called competing endogenous RNA (ceRNA) interactions, which suggests that some transcripts can indirectly regulate one another's activity through their interactions with …

Deep Learning For Segmentation Of 3d Cryo-Em Images, Devin Reid Haslam

Computer Science Theses & Dissertations

Cryo-electron microscopy (cryo-EM) is an emerging biophysical technique for structural determination of protein complexes. However, accurate detection of secondary structures is still challenging when cryo-EM density maps are at medium resolutions (5-10 Å). Most existing methods are image processing methods that do not fully utilize available images in the cryo-EM database. In this paper, we present a deep learning approach to segment secondary structure elements as helices and β-sheets from medium- resolution density maps. The proposed 3D convolutional neural network is shown to detect secondary structure locations with an F1 score between 0.79 and 0.88 for six simulated test cases. …

Quantitative Electroencephalography For Detecting Concussions, Sara Krehbiel, Kathy Hoke, Joanna Wares

Biology and Medicine Through Mathematics Conference

No abstract provided.

Augmented Personalized Health: Using Semantically Integrated Multimodal Data For Patient Empowered Health Management Strategies, Amit P. Sheth, Hong Y. Yip, Utkarshani Jaimini, Dipesh Kadariya, Vaikunth Sridharan, R. Venkataramanan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra

Kno.e.sis Publications

Healthcare as we know it is in the process of going through a massive change from:

1. Episodic to continuous

2. Disease-focused to wellness and quality of life focused

3. Clinic-centric to anywhere a patient is

4. Clinician controlled to patient empowered

5. Being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data-driven URL: https://mhealth.md2k.org/2018-tech-showcase-home

Tgmi: An Efficient Algorithm For Identifying Pathway Regulators Through Evaluation Of Triple-Gene Mutual Interaction, Chathura J. Gunasekara, Kui Zhang, Wenping Deng, Laura E. Brown, Hairong Wei

Michigan Tech Publications, Part 1

Despite their important roles, the regulators for most metabolic pathways and biological processes remain elusive. Presently, the methods for identifying metabolic pathway and biological process regulators are intensively sought after. We developed a novel algorithm called triple-gene mutual interaction (TGMI) for identifying these regulators using high-throughput gene expression data. It first calculated the regulatory interactions among triple gene blocks (two pathway genes and one transcription factor (TF)), using conditional mutual information, and then identifies significantly interacted triple genes using a newly identified novel mutual interaction measure (MIM), which was substantiated to reflect strengths of regulatory interactions within each triple gene …

“Musical Exercise” For People With Visual Impairments: A Preliminary Study With The Blindfolded, Ridwan Ahmed Khan, Myounghoon Jeon, Tejin Yoon

Michigan Tech Publications, Part 1

Performing independent physical exercise is critical to maintain one's good health, but it is specifically hard for people with visual impairments. To address this problem, we have developed a Musical Exercise platform for people with visual impairments so that they can perform exercise in a good form consistently. We designed six different conditions, including blindfolded or visual without audio conditions, and blindfolded or visual with two different types of audio feedback (continuous vs. discrete) conditions. Eighteen sighted participants participated in the experiment, by doing two exercises - squat and wall sit with all six conditions. The results show that Musical …

Heterogeneous Activity Causes A Nonlinear Increase In The Group Energy Use Of Ant Workers Isolated From Queen And Brood, Nolan Ferral, Kyara Holloway, Mingzhong Li, Zhaozheng Yin, Chen Hou

Computer Science Faculty Research & Creative Works

Increasing evidence has shown that the energy use of ant colonies increases sublinearly with colony size so that large colonies consume less per capita energy than small colonies. It has been postulated that social environment (e.g., in the presence of queen and brood) is critical for the sublinear group energetics, and a few studies of ant workers isolated from queens and brood observed linear relationships between group energetics and size. In this paper, we hypothesize that the sublinear energetics arise from the heterogeneity of activity in ant groups, that is, large groups have relatively more inactive members than small groups. …

Bird Abundance At Bird Feeders In Response To Temperature, Wind Speed And Precipitation During The Winter Season, Siddhant Kahal

Master's Theses

The goal of this project is to explore how 23 different bird species respond to 3 climatic attributes. These attributes are lower than average temperatures, wind speed and precipitation level. Information about the bird species and all of the data associated with them is provided by Project FeederWatch (PFW). This is a citizen based survey study that provides key information about bird species abundance through the use of backyard and community feeders. The study volunteers from across the United States and Canada monitor these bird feeders and note important information about the species such as the number of individuals seen. …

Critical Parameters In A Computational Model Of Tgf-Beta-Induced Epithelial Mesenchymal Transition., Mario J. Mendez, Seth H. Weinberg

Biology and Medicine Through Mathematics Conference

No abstract provided.

Hypoxic And Viral Contributions To The Etiopathogenesis Of Schizophrenia: A Whole Transcriptome Analysis, Kathryn A. Gorski

Theses

Schizophrenia is a mental illness with a complex and as of yet unclear etiology. It is highly heritable and has a strong polygenic character, however, studies examining the genetics of schizophrenia have not sufficiently explained all variability in its prevalence. Environmental causes are theorized to have a non trivial contribution to the pathoetiology of schizophrenia, including interactions with genetic components, but these mechanisms remain unclear. Analyzing schizophrenia dysfunction using transcriptomic approaches is a paradigm still in its infancy, and fewer studies still have examined non neurological contributions to schizophrenia pathology with next generation sequencing technologies. This pilot study uses several …