138 research outputs found
Governance and organizational sponsorship as success factors in free/libre and open source software development: An empirical investigation using structural equation modeling
Recent advances in information technologies and subsequent explosive growth of computer software use in practically all aspects of everyday life provide tremendous opportunities and benefits for improving people\u27s lives. However, significant proportion of software projects represents cancelled, abandoned or otherwise failed projects. This situation exists not only in commercial software products or government information systems, but also in an increasingly popular and important domain of free/libre and open source software (FLOSS).
The problem of failures in software development projects requires identification and understanding of the factors of success and their interrelationships. Practice and previous research suggest that governance of software development projects plays crucial role in their success. Increasing adoption and sponsorship of FLOSS by commercial firms and government organizations present additional challenges; such sponsorship may also interact with governance in FLOSS projects and play a role in determining their success.
This dissertation focused on analyzing the role and significance of governance and organizational sponsorship in the success of FLOSS development. This study used both conceptual analysis and empirical methods. The conceptual analysis phase, a preliminary study based on the review of existing literature, produced a partial model of success in FLOSS development. This model was verified in an empirical phase, which statistically analyzed data from multiple FLOSS repositories and other public sources. The statistical analysis was based on structural equation modeling (SEM) approach.
Results of this study did not confirm hypothesized effects of the main two factors (governance and organizational sponsorship) on FLOSS success, but confirmed a positive effect of project maturity on the success. The likely reason of the lack of support for the main factors is unavailability of sufficient and correct data for proper operationalization. This and other uncovered issues are planned to be addressed in the future research on the topic, for which this dissertation formed a solid conceptual and data analysis framework
Undergraduate and Graduate Course Descriptions, 2018 Spring
Wright State University undergraduate and graduate course descriptions from Spring 2018
Undergraduate and Graduate Course Descriptions, 2016 Fall
Wright State University undergraduate and graduate course descriptions from Fall 2016
2019-2020, University of Memphis bulletin
University of Memphis bulletin containing the graduate catalog for 2019-2020.https://digitalcommons.memphis.edu/speccoll-ua-pub-bulletins/1439/thumbnail.jp
Enhanced independent vector analysis for audio separation in a room environment
Independent vector analysis (IVA) is studied as a frequency domain blind source separation method, which can theoretically avoid the permutation problem by retaining the dependency between different frequency bins of the same source vector while removing the dependency between different source vectors. This thesis focuses upon improving the performance of independent vector analysis when it is used to solve the audio separation problem in a room environment.
A specific stability problem of IVA, i.e. the block permutation problem, is identified and analyzed. Then a robust IVA method is proposed to solve this problem by exploiting the phase continuity of the unmixing matrix. Moreover, an auxiliary function based IVA algorithm with an overlapped chain type source prior is proposed as well to mitigate this problem.
Then an informed IVA scheme is proposed which combines the geometric information of the sources from video to solve the problem by providing an intelligent initialization for optimal convergence. The proposed informed IVA algorithm can also achieve a faster convergence in terms of iteration numbers and better separation performance. A pitch based evaluation method is defined to judge the separation performance objectively when the information describing the mixing matrix and sources is missing.
In order to improve the separation performance of IVA, an appropriate multivariate source prior is needed to better preserve the dependency structure within the source vectors. A particular multivariate generalized Gaussian distribution is adopted as the source prior. The nonlinear score function derived from this proposed source prior contains the fourth order relationships between different frequency bins, which provides a more informative and stronger dependency structure compared with the original IVA algorithm and thereby improves the separation performance.
Copula theory is a central tool to model the nonlinear dependency structure. The t copula is proposed to describe the dependency structure within the frequency domain speech signals due to its tail dependency property, which means if one variable has an extreme value, other variables are expected to have extreme values. A multivariate student's t distribution constructed by using a t copula with the univariate student's t marginal distribution is proposed as the source prior. Then the IVA algorithm with the proposed source prior is derived.
The proposed algorithms are tested with real speech signals in different reverberant room environments both using modelled room impulse response and real room recordings. State-of-the-art criteria are used to evaluate the separation performance, and the experimental results confirm the advantage of the proposed algorithms
LMS DESIGN INTERVENTIONS FORENHANCING THE INTENTION TO CONTINUE USE
Learners, according to the literature, believe that the use of a Learning Management System increases self-regulated behaviour, but even so, a significant number of them have no positive intention to use one. The goal of this thesis is to investigate this mismatch and to propose and test the use of Perceived Learning Self-regulation and Perceived Cognitive Absorption as predictors of the intention to use an LMS and to design and test interventions that improve the Continued Intention to Use an LMS that enhances Perceived Learning Self-Regulation and Perceived Cognitive Absorption.
Three intervention tools were designed on a theoretical basis and then implemented: herd behaviour was the basis for Tracking Technology, goal setting was the basis for Visualised Competency, and social learning theory was the basis for Social Media. The intervention designs were based on data from interviews, focus group discussions and online collaboration with 10 teachers. They were implemented on a computer science module with 400 registered students. Two questionnaires were circulated to examine the effects of these interventions on the PLSR, PCA and CIU (151 students) and assess their opinions (149 students).
All three interventions increased students' perceived cognitive absorption and perceived learning self-regulation and increased their continued intention to use a learning management system. Moreover, perceived cognitive absorption was found to be a critical antecedent to perceived learning self-regulation, which plays a mediating role between perceived cognitive absorption and their continued intention to use a learning management system. The survey analysis reported a positive perception overall among the students of the proposed interventions and the LMS with the given technology. Interaction analysis showed the continuous and consistent use of the intervention by the learners.
The main contribution to knowledge here is a new framework for interventions that can improve students perceived cognitive absorption and thereby their continued intention to use an LMS. This research integrated the theories of experience flow, self-regulation, herd behaviour and goal setting to explain the potential effects of tracking technology, visualised competency, and social media on the perceived learning self-regulation and perceived cognitive absorption, which improved the continued intention to use a learning management system.
According to the Information System Success Model, positive attitudes and the perception of benefits can be significant predictors of the intention to use a certain technology. Thus, Perceived Learning Self-Regulation and Perceived Cognitive Absorption were used to propose predictors of studentsâ continued intention to use a learning management system, instead of their perception of and attitude to possible benefits. For this reason, the present research aimed to develop a framework that introduced, evaluated, and examined the impact of interventions on improving learners perceived cognitive absorption and perceived learning self-regulation as well as affecting learnersâ continued intention to use in LMS. To fulfil this aim, the main research question was, âHow to improve studentsâ Continued Intention to Use (CIU) an LMS by improving their perceived learning self-regulation and perceived cognitive absorption?â
The results suggest that all interventions had a significant effect on the perceived cognitive absorption, perceived learning self-regulation and continue intention to use the LMS. perceived cognitive absorption was found to be a critical antecedent to the perceived learning self-regulation, which plays the mediating role between perceived cognitive absorption and continue intention to use LMS. The survey analysis also reported overall positive perceptions among students of the use of these interventions and the LMS with the technology. By using interaction analysis, the intervention showed continuous and consistent use among learners.
The main contribution to knowledge, as noted above, is a new framework to propose interventions that can improve the perceived cognitive absorption, and in turn, the continue intention to use can be improved. This research integrated experience flow, self-regulation, herd behaviour and goal-setting theories to explain the potential effects of the tracking tool, visualised competency, and social media on the perceived learning self-regulation and perceived cognitive absorption, which improved the learners continue intention to use learning management system
Human Practice. Digital Ecologies. Our Future. : 14. Internationale Tagung Wirtschaftsinformatik (WI 2019) : Tagungsband
Erschienen bei: universi - UniversitÀtsverlag Siegen. - ISBN: 978-3-96182-063-4Aus dem Inhalt:
Track 1: Produktion & Cyber-Physische Systeme
Requirements and a Meta Model for Exchanging Additive Manufacturing Capacities
Service Systems, Smart Service Systems and Cyber- Physical SystemsâWhatâs the difference? Towards a Unified Terminology
Developing an Industrial IoT Platform â Trade-off between Horizontal and Vertical Approaches
Machine Learning und Complex Event Processing: Effiziente Echtzeitauswertung am Beispiel Smart Factory
Sensor retrofit for a coffee machine as condition monitoring and predictive maintenance use case
Stakeholder-Analyse zum Einsatz IIoT-basierter Frischeinformationen in der Lebensmittelindustrie
Towards a Framework for Predictive Maintenance Strategies in Mechanical Engineering - A Method-Oriented Literature Analysis
Development of a matching platform for the requirement-oriented selection of cyber physical systems for SMEs
Track 2: Logistic Analytics
An Empirical Study of Customersâ Behavioral Intention to Use Ridepooling Services â An Extension of the Technology Acceptance Model
Modeling Delay Propagation and Transmission in Railway Networks
What is the impact of company specific adjustments on the acceptance and diffusion of logistic standards?
Robust Route Planning in Intermodal Urban Traffic
Track 3: Unternehmensmodellierung & Informationssystemgestaltung (Enterprise Modelling & Information Systems Design)
Work System Modeling Method with Different Levels of Specificity and Rigor for Different Stakeholder Purposes
Resolving Inconsistencies in Declarative Process Models based on Culpability Measurement
Strategic Analysis in the Realm of Enterprise Modeling â On the Example of Blockchain-Based Initiatives for the Electricity Sector
Zwischenbetriebliche Integration in der Möbelbranche: Konfigurationen und Einflussfaktoren
Novicesâ Quality Perceptions and the Acceptance of Process Modeling Grammars
Entwicklung einer Definition fĂŒr Social Business Objects (SBO) zur Modellierung von Unternehmensinformationen
Designing a Reference Model for Digital Product Configurators
Terminology for Evolving Design Artifacts
Business Role-Object Specification: A Language for Behavior-aware Structural Modeling of Business Objects
Generating Smart Glasses-based Information Systems with BPMN4SGA: A BPMN Extension for Smart Glasses Applications
Using Blockchain in Peer-to-Peer Carsharing to Build Trust in the Sharing Economy
Testing in Big Data: An Architecture Pattern for a Development Environment for Innovative, Integrated and Robust Applications
Track 4: Lern- und Wissensmanagement (e-Learning and Knowledge Management)
eGovernment Competences revisited â A Literature Review on necessary Competences in a Digitalized Public Sector
Say Hello to Your New Automated Tutor â A Structured Literature Review on Pedagogical Conversational Agents
Teaching the Digital Transformation of Business Processes: Design of a Simulation Game for Information Systems Education
Conceptualizing Immersion for Individual Learning in Virtual Reality
Designing a Flipped Classroom Course â a Process Model
The Influence of Risk-Taking on Knowledge Exchange and Combination
Gamified Feedback durch Avatare im Mobile Learning
Alexa, Can You Help Me Solve That Problem? - Understanding the Value of Smart Personal Assistants as Tutors for Complex Problem Tasks
Track 5: Data Science & Business Analytics
Matching with Bundle Preferences: Tradeoff between Fairness and Truthfulness
Applied image recognition: guidelines for using deep learning models in practice
Yield Prognosis for the Agrarian Management of Vineyards using Deep Learning for Object Counting
Reading Between the Lines of Qualitative Data â How to Detect Hidden Structure Based on Codes
Online Auctions with Dual-Threshold Algorithms: An Experimental Study and Practical Evaluation
Design Features of Non-Financial Reward Programs for Online Reviews: Evaluation based on Google Maps Data
Topic Embeddings â A New Approach to Classify Very Short Documents Based on Predefined Topics
Leveraging Unstructured Image Data for Product Quality Improvement
Decision Support for Real Estate Investors: Improving Real Estate Valuation with 3D City Models and Points of Interest
Knowledge Discovery from CVs: A Topic Modeling Procedure
Online Product Descriptions â Boost for your Sales?
EntscheidungsunterstĂŒtzung durch historienbasierte Dienstreihenfolgeplanung mit Pattern
A Semi-Automated Approach for Generating Online Review Templates
Machine Learning goes Measure Management: Leveraging Anomaly Detection and Parts Search to Improve Product-Cost Optimization
Bedeutung von Predictive Analytics fĂŒr den theoretischen Erkenntnisgewinn in der IS-Forschung
Track 6: Digitale Transformation und Dienstleistungen
Heuristic Theorizing in Software Development: Deriving Design Principles for Smart Glasses-based Systems
Mirroring E-service for Brick and Mortar Retail: An Assessment and Survey
Taxonomy of Digital Platforms: A Platform Architecture Perspective
Value of Star Players in the Digital Age
Local Shopping Platforms â Harnessing Locational Advantages for the Digital Transformation of Local Retail Outlets: A Content Analysis
A Socio-Technical Approach to Manage Analytics-as-a-Service â Results of an Action Design Research Project
Characterizing Approaches to Digital Transformation: Development of a Taxonomy of Digital Units
Expectations vs. Reality â Benefits of Smart Services in the Field of Tension between Industry and Science
Innovation Networks and Digital Innovation: How Organizations Use Innovation Networks in a Digitized Environment
Characterising Social Reading Platformsâ A Taxonomy-Based Approach to Structure the Field
Less Complex than Expected â What Really Drives IT Consulting Value
Modularity Canvas â A Framework for Visualizing Potentials of Service Modularity
Towards a Conceptualization of Capabilities for Innovating Business Models in the Industrial Internet of Things
A Taxonomy of Barriers to Digital Transformation
Ambidexterity in Service Innovation Research: A Systematic Literature Review
Design and success factors of an online solution for cross-pillar pension information
Track 7: IT-Management und -Strategie
A Frugal Support Structure for New Software Implementations in SMEs
How to Structure a Company-wide Adoption of Big Data Analytics
The Changing Roles of Innovation Actors and Organizational Antecedents in the Digital Age
Bewertung des Kundennutzens von Chatbots fĂŒr den Einsatz im Servicedesk
Understanding the Benefits of Agile Software Development in Regulated Environments
Are Employees Following the Rules? On the Effectiveness of IT Consumerization Policies
Agile and Attached: The Impact of Agile Practices on Agile Team Membersâ Affective Organisational Commitment
The Complexity Trap â Limits of IT Flexibility for Supporting Organizational Agility in Decentralized Organizations
Platform Openness: A Systematic Literature Review and Avenues for Future Research
Competence, Fashion and the Case of Blockchain
The Digital Platform Otto.de: A Case Study of Growth, Complexity, and Generativity
Track 8: eHealth & alternde Gesellschaft
Security and Privacy of Personal Health Records in Cloud Computing Environments â An Experimental Exploration of the Impact of Storage Solutions and Data Breaches
Patientenintegration durch Pfadsysteme
Digitalisierung in der StressprĂ€vention â eine qualitative Interviewstudie zu Nutzenpotenzialen
User Dynamics in Mental Health Forums â A Sentiment Analysis Perspective
Intent and the Use of Wearables in the Workplace â A Model Development
Understanding Patient Pathways in the Context of Integrated Health Care Services - Implications from a Scoping Review
Understanding the Habitual Use of Wearable Activity Trackers
On the Fit in Fitness Apps: Studying the Interaction of Motivational Affordances and Usersâ Goal Orientations in Affecting the Benefits Gained
Gamification in Health Behavior Change Support Systems - A Synthesis of Unintended Side Effects
Investigating the Influence of Information Incongruity on Trust-Relations within Trilateral Healthcare Settings
Track 9: Krisen- und KontinuitÀtsmanagement
Potentiale von IKT beim Ausfall kritischer Infrastrukturen: Erwartungen, Informationsgewinnung und Mediennutzung der Zivilbevölkerung in Deutschland
Fake News Perception in Germany: A Representative Study of Peopleâs Attitudes and Approaches to Counteract Disinformation
Analyzing the Potential of Graphical Building Information for Fire Emergency Responses: Findings from a Controlled Experiment
Track 10: Human-Computer Interaction
Towards a Taxonomy of Platforms for Conversational Agent Design
Measuring Service Encounter Satisfaction with Customer Service Chatbots using Sentiment Analysis
Self-Tracking and Gamification: Analyzing the Interplay of Motivations, Usage and Motivation Fulfillment
Erfolgsfaktoren von Augmented-Reality-Applikationen: Analyse von Nutzerrezensionen mit dem Review-Mining-Verfahren
Designing Dynamic Decision Support for Electronic Requirements Negotiations
Who is Stressed by Using ICTs? A Qualitative Comparison Analysis with the Big Five Personality Traits to Understand Technostress
Walking the Middle Path: How Medium Trade-Off Exposure Leads to Higher Consumer Satisfaction in Recommender Agents
Theory-Based Affordances of Utilitarian, Hedonic and Dual-Purposed Technologies: A Literature Review
Eliciting Customer Preferences for Shopping Companion Apps: A Service Quality Approach
The Role of Early User Participation in Discovering Software â A Case Study from the Context of Smart Glasses
The Fluidity of the Self-Concept as a Framework to Explain the Motivation to Play Video Games
Heart over Heels? An Empirical Analysis of the Relationship between Emotions and Review Helpfulness for Experience and Credence Goods
Track 11: Information Security and Information Privacy
Unfolding Concerns about Augmented Reality Technologies: A Qualitative Analysis of User Perceptions
To (Psychologically) Own Data is to Protect Data: How Psychological Ownership Determines Protective Behavior in a Work and Private Context
Understanding Data Protection Regulations from a Data Management Perspective: A Capability-Based Approach to EU-GDPR
On the Difficulties of Incentivizing Online Privacy through Transparency: A Qualitative Survey of the German Health Insurance Market
What is Your Selfie Worth? A Field Study on Individualsâ Valuation of Personal Data
Justification of Mass Surveillance: A Quantitative Study
An Exploratory Study of Risk Perception for Data Disclosure to a Network of Firms
Track 12: Umweltinformatik und nachhaltiges Wirtschaften
KommunikationsfĂ€den im Nadelöhr â Fachliche Prozessmodellierung der Nachhaltigkeitskommunikation am Kapitalmarkt
Potentiale und Herausforderungen der Materialflusskostenrechnung
Computing Incentives for User-Based Relocation in Carsharing
Sustainabilityâs Coming Home: Preliminary Design Principles for the Sustainable Smart District
Substitution of hazardous chemical substances using Deep Learning and t-SNE
A Hierarchy of DSMLs in Support of Product Life-Cycle Assessment
A Survey of Smart Energy Services for Private Households
Door-to-Door Mobility Integrators as Keystone Organizations of Smart Ecosystems: Resources and Value Co-Creation â A Literature Review
Ein EntscheidungsunterstĂŒtzungssystem zur ökonomischen Bewertung von Mieterstrom auf Basis der Clusteranalyse
Discovering Blockchain for Sustainable Product-Service Systems to enhance the Circular Economy
Digitale RĂŒckverfolgbarkeit von Lebensmitteln: Eine verbraucherinformatische Studie
Umweltbewusstsein durch audiovisuelles Content Marketing? Eine experimentelle Untersuchung zur Konsumentenbewertung nachhaltiger Smartphones
Towards Predictive Energy Management in Information Systems: A Research Proposal
A Web Browser-Based Application for Processing and Analyzing Material Flow Models using the MFCA Methodology
Track 13: Digital Work - Social, mobile, smart
On Conversational Agents in Information Systems Research: Analyzing the Past to Guide Future Work
The Potential of Augmented Reality for Improving Occupational First Aid
Prevent a Vicious Circle! The Role of Organizational IT-Capability in Attracting IT-affine Applicants
Good, Bad, or Both? Conceptualization and Measurement of Ambivalent User Attitudes Towards AI
A Case Study on Cross-Hierarchical Communication in Digital Work Environments
âShow Me Your People Skillsâ - Employing CEO Branding for Corporate Reputation Management in Social Media
A Multiorganisational Study of the Drivers and Barriers of Enterprise Collaboration Systems-Enabled Change
The More the Merrier? The Effect of Size of Core Team Subgroups on Success of Open Source Projects
The Impact of Anthropomorphic and Functional Chatbot Design Features in Enterprise Collaboration Systems on User Acceptance
Digital Feedback for Digital Work? Affordances and Constraints of a Feedback App at InsurCorp
The Effect of Marker-less Augmented Reality on Task and Learning Performance
Antecedents for Cyberloafing â A Literature Review
Internal Crowd Work as a Source of Empowerment - An Empirical Analysis of the Perception of Employees in a Crowdtesting Project
Track 14: GeschÀftsmodelle und digitales Unternehmertum
Dividing the ICO Jungle: Extracting and Evaluating Design Archetypes
Capturing Value from Data: Exploring Factors Influencing Revenue Model Design for Data-Driven Services
Understanding the Role of Data for Innovating Business Models: A System Dynamics Perspective
Business Model Innovation and Stakeholder: Exploring Mechanisms and Outcomes of Value Creation and Destruction
Business Models for Internet of Things Platforms: Empirical Development of a Taxonomy and Archetypes
Revitalizing established Industrial Companies: State of the Art and Success Principles of Digital Corporate Incubators
When 1+1 is Greater than 2: Concurrence of Additional Digital and Established Business Models within Companies
Special Track 1: Student Track
Investigating Personalized Price Discrimination of Textile-, Electronics- and General Stores in German Online Retail
From Facets to a Universal Definition â An Analysis of IoT Usage in Retail
Is the Technostress Creators Inventory Still an Up-To-Date Measurement Instrument? Results of a Large-Scale Interview Study
Application of Media Synchronicity Theory to Creative Tasks in Virtual Teams Using the Example of Design Thinking
TrustyTweet: An Indicator-based Browser-Plugin to Assist Users in Dealing with Fake News on Twitter
Application of Process Mining Techniques to Support Maintenance-Related Objectives
How Voice Can Change Customer Satisfaction: A Comparative Analysis between E-Commerce and Voice Commerce
Business Process Compliance and Blockchain: How Does the Ethereum Blockchain Address Challenges of Business Process Compliance?
Improving Business Model Configuration through a Question-based Approach
The Influence of Situational Factors and Gamification on Intrinsic Motivation and Learning
Evaluation von ITSM-Tools fĂŒr Integration und Management von Cloud-Diensten am Beispiel von ServiceNow
How Software Promotes the Integration of Sustainability in Business Process Management
Criteria Catalog for Industrial IoT Platforms from the Perspective of the Machine Tool Industry
Special Track 3: Demos & Prototyping
Privacy-friendly User Location Tracking with Smart Devices: The BeaT Prototype
Application-oriented robotics in nursing homes
Augmented Reality for Set-up Processe
Mixed Reality for supporting Remote-Meetings
Gamification zur Motivationssteigerung von Werkern bei der Betriebsdatenerfassung
Automatically Extracting and Analyzing Customer Needs from Twitter: A âNeedminingâ Prototype
GaNEsHA: Opportunities for Sustainable Transportation in Smart Cities
TUCANA: A platform for using local processing power of edge devices for building data-driven services
Demonstrator zur Beschreibung und Visualisierung einer kritischen Infrastruktur
Entwicklung einer alltagsnahen persuasiven App zur Bewegungsmotivation fĂŒr Ă€ltere Nutzerinnen und Nutzer
A browser-based modeling tool for studying the learning of conceptual modeling based on a multi-modal data collection approach
Exergames & Dementia: An interactive System for People with Dementia and their Care-Network
Workshops
Workshop Ethics and Morality in Business Informatics (Workshop Ethik und Moral in der Wirtschaftsinformatik â EMoWIâ19)
Model-Based Compliance in Information Systems - Foundations, Case Description and Data Set of the MobIS-Challenge for Students and Doctoral Candidates
Report of the Workshop on Concepts and Methods of Identifying Digital Potentials in Information Management
Control of Systemic Risks in Global Networks - A Grand Challenge to Information Systems Research
Die Mitarbeiter von morgen - Kompetenzen kĂŒnftiger Mitarbeiter im Bereich Business Analytics
Digitaler Konsum: Herausforderungen und Chancen der Verbraucherinformati
A computational and experimental study of HER2-signaling effects on cellular migration and proliferation
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, February 2007.Includes bibliographical references.The fundamental question posed in this thesis is: how does a cell 'decide' to behave in a particular way? The human body is comprised of [approx.] 1014 cells that interpret extracellular information and respond with such behavior as migration, proliferation, apoptosis, or differentiation. Thirty years of research in the related fields of biochemistry, molecular biology, and genetics have demonstrated that, in most cases, the cellular decision-making process cannot be described or predicted by regulation of only one gene or one protein alone. Instead, it has become clear that cellular behavior is a function of information flow through multiple intracellular molecules. Furthermore, the molecules responsible for the control of cell behavior comprise a surprisingly short list, indicating that factors such as signaling dynamics and intensity coupled with combinatorial control are essential to produce the wide array of observed cell behavior. The identification of protein kinases as transducers of large amounts of intracellular information led us to pose the hypothesis that the quantitative regulation of key kinases governs cellular behavior. The goal of this thesis was to identify rules governing multi-kinase behavioral control and to then, on the basis of these rules, predict changes in cell function in response to changes in receptor expression, ligand treatment, and pharmacological intervention.(cont.) A human mammary epithelial cell (HMEC) system with varying levels of the human epidermal growth factor receptor 2 (HER2) was chosen to explore cell decision processes. HER2 overexpression is found in 30% of breast cancers and correlates with poor prognosis and increased metastasis. In particular, we investigated the effects of HER2 overexpression on signaling networks and resultant cell proliferation and migration in the presence of epidermal growth factor (EGF) or heregulin (HRG), two EGFR-family ligands that promote HER2 heterodimerization. To investigate HER2-mediated signaling and cell behavior we developed and applied high-throughput experimental techniques to measure kinase activity and phosphorylation as well as cell proliferation and migration. Measurement of -~100 different kinases downstream of HER2 resulted in the identification of network signaling mechanisms. Application of a novel high-throughput migration assay enabled the identification of HER2-mediated increases in cell migration due to increases in the directional persistence of movement. Linear mapping techniques related to partial least squares regression (PLSR) defined and predicted cell behavior in response to HER2 overexpression.(cont.) Combining quantitative datasets of both biological signals and behavior using PLSR, we identified subsets of kinase phosphorylation events that most critically regulate HER2-mediated migration and proliferation. Importantly, we demonstrated that our models provide predictive ability through a priori predictions of cell behavior in HER2-overexpressing cells. Application of linear models in response to pharmacological inhibition resulted in the a priori prediction of cell migration, and identified an EGFR kinase inhibitor Gefitinib as a potent inhibitor of HER2-mediated migration. In conclusion, the application of computational linear modeling to quantitative biological signaling and behavior datasets captured systems-level regulation of cell behavior and, based on this, predicted cell migration and proliferation in response to HER2 overexpression and pharmacological inhibition. Further application of quantitative measurement together with linear modeling should enable the identification of salient cell signal-cell response elements to understand how cells make decisions and to predict how those decisions can be therapeutically manipulated.by Neil Kumar.Ph.D
Multivariat analyse som verktÞy til forstÄelse og reduksjon av kompleksitet av matematiske modeller i systembiologi
In the area of systems biology, technologies develop very fast, which allows us to collect massive amounts of various data. The main interest of scientists is to receive an insight into the obtained data sets and discover their inherent properties. Since the data often are rather complex and intimidating equations may be required for modelling, data analysis can be quite challenging for the majority of bio-scientists who do not master advanced mathematics. In this thesis it is proposed to use multivariate statistical methods as a tool for understanding the properties of complex models used for describing biological systems.
The methods of multivariate analysis employed in this thesis search for latent variables that form a basis of all processes in a system. This often reduces dimensions of the system and makes it easier to get the whole picture of what is going on. Thus, in this work, methods of multivariate analysis were used with a descriptive purpose in Papers I and IV to discover effects of input variables on a response.
Often it is necessary to know a functional form that could have generated the collected data in order to study the behaviour of the system when one or another parameter is tuned. For this purpose, we propose the Direct Look-Up (DLU) approach that is claimed here to be a worthy alternative to the already existing fitting methods due to its high computational speed and ability to avoid many problems such as subjectivity, choice of initial values, local optima and so on (Papers II and III).
Another aspect covered in this thesis is an interpretation of function parameters by the custom human language with the use of multivariate analysis. This would enable mathematicians and bio-scientists to understand each other when describing the same object. It was accomplished here by using the concept of a metamodel and sensory analysis in Paper IV. In Paper I, a similar approach was used even though the main focus of the paper was slightly different. The original aim of the article was to show the advantages of the multi-way GEMANOVA analysis over the traditional ANOVA analysis for certain types of data. However, in addition, the relationship between human profiling of data samples and function parameters was discovered.
In situations when funds for conducting experiments are limited and it is unrealizable to study all possible parameter combinations, it is necessary to have a smart way of choosing a few but most representative conditions for a particular system. In Paper V Multi-level Binary Replacement design (MBR) was developed as such, which can also be used for searching for a relevant parameter range. This new design method was applied here in Papers II and IV for selection of samples for further analyses.Teknologiutviklingen innenfor systembiologien er nÄ sÄ rask at det gir mulighet til Ä samle svÊrt store datamengder pÄ kort tid og til relativ lav pris. Hovedinteressen til forskerne er typisk Ä fÄ innsikt i dataene og deres iboende egenskaper. Siden data kan vÊre ganske komplekse og ofte beskrives ved kompliserte, gjerne ikke-lineÊre, funksjoner, kan dataanalyse vÊre ganske utfordrende for mange bioforskere som ikke behersker avansert matematikk. I dette arbeidet er det foreslÄtt Ä bruke multivariat statistisk analyse for Ä komme nÊrmere en forstÄelse av egenskapene av kompliserte modeller som blir brukt for Ä beskrive biologiske systemer.
De multivariate metodene som er benyttet i denne avhandlingen sÞker etter latente variabler som utgjÞr en lineÊr basis og tilnÊrming til de komplekse prosessene i et system. Dermed kan man oppnÄ en forenkling av systemet som er lettere Ä tolke. I dette arbeidet ble multivariate analysemetoder brukt i denne beskrivende hensikten i Artikler (Papers) I og IV til Ä oppdage effekter av funksjonsparametre pÄ egenskapene til komplekse matematiske modeller.
Ofte er det nÞdvendig Ä finne en matematisk funksjon som kunne ha generert de innsamlede dataene for Ä studere oppfÞrselen av systemet. Med den hensikt foreslÄr vi en metode for modelltilpasning ved DLU-metoden (the Direct Look-Up) som her pÄstÄs Ä vÊre et verdifullt alternativ til de eksisterende estimeringsmetodene pÄ grunn av hÞy fart og evne til Ä unngÄ typiske problemer som for eksempel subjektivitet, valg av initialverdier, lokale optima, m.m (Artikler II og III).
Et annet aspekt dekket i denne avhandlingen er bruken av multivariat analyse til Ä gi tolking av matematiske funksjonsparametre ved hjelp av et dagligdags vokabular. Dette kan gjÞre det enklere for matematikere og bioforskere Ä forstÄ hverandre nÄr de beskriver det samme objektet. Det var utfÞrt her ved Ä benytte ideen om en metamodell og sensorisk analyse i Artikkel IV. I Artikkel I var en lignende metode ogsÄ brukt for Ä fÄ sensoriske beskrivelser av bilder generert fra differensiallikninger. Hovedfokuset i Artikkel I var imidlertid et annet, nemlig Ä vise fordelen ved multi-way GEMANOVA-analyse fremfor den tradisjonelle ANOVA-analysen for visse datatyper. I denne artikkelen ble GEMANOVA brukt til Ä avdekke sammenhengen mellom kompliserte kombinasjoner av funksjonsparametrene og bildedeskriptorer.
I situasjoner der ressurser til Ä utfÞre eksperimenter er begrenset og det er umulig Ä prÞve ut alle kombinasjoner av parametre, er det behov for metoder som kan bestemme et fÄtall av parameterinnstillinger som er mest mulig representative for et bestemt system. I Artikkel V ble derfor Multi-level Binary Replacement (MBR) design utviklet som en sÄdan, og den kan ogsÄ brukes for Ä sÞke etter et relevant parameterrom for datasimuleringer. Den nye designmetoden ble anvendt i Artikler II og IV for utvelgelse av parameterverdier for videre analyser
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