Parsimonious Clone Tree Integration in cancer

BACKGROUND: Every tumor is composed of heterogeneous clones, each corresponding to a distinct subpopulation of cells that accumulated different types of somatic mutations, ranging from single-nucleotide variants (SNVs) to copy-number aberrations (CNAs). As the analysis of this intra-tumor heterogeneity has important clinical applications, several computational methods have been introduced to identify clones from DNA sequencing data. However, due to technological and methodological limitations, current analyses are restricted to identifying tumor clones only based on either SNVs or CNAs, preventing a comprehensive characterization of a tumor's clonal composition. RESULTS: To overcome these challenges, we formulate the identification of clones in terms of both SNVs and CNAs as a integration problem while accounting for uncertainty in the input SNV and CNA proportions. We thus characterize the computational complexity of this problem and we introduce PACTION (PArsimonious Clone Tree integratION), an algorithm that solves the problem using a mixed integer linear programming formulation. On simulated data, we show that tumor clones can be identified reliably, especially when further taking into account the ancestral relationships that can be inferred from the input SNVs and CNAs. On 49 tumor samples from 10 prostate cancer patients, our integration approach provides a higher resolution view of tumor evolution than previous studies. CONCLUSION: PACTION is an accurate and fast method that reconstructs clonal architecture of cancer tumors by integrating SNV and CNA clones inferred using existing methods

Parsimonious Clone Tree Reconciliation in Cancer

Every tumor is composed of heterogeneous clones, each corresponding to a distinct subpopulation of cells that accumulated different types of somatic mutations, ranging from single-nucleotide variants (SNVs) to copy-number aberrations (CNAs). As the analysis of this intra-tumor heterogeneity has important clinical applications, several computational methods have been introduced to identify clones from DNA sequencing data. However, due to technological and methodological limitations, current analyses are restricted to identifying tumor clones only based on either SNVs or CNAs, preventing a comprehensive characterization of a tumor's clonal composition. To overcome these challenges, we formulate the identification of clones in terms of both SNVs and CNAs as a reconciliation problem while accounting for uncertainty in the input SNV and CNA proportions. We thus characterize the computational complexity of this problem and we introduce a mixed integer linear programming formulation to solve it exactly. On simulated data, we show that tumor clones can be identified reliably, especially when further taking into account the ancestral relationships that can be inferred from the input SNVs and CNAs. On 49 tumor samples from 10 prostate cancer patients, our reconciliation approach provides a higher resolution view of tumor evolution than previous studies

Flow control and sensing using data-driven reduced-order modeling

Transfer operators, such as the Koopman operator, are driving a paradigm shift in how we perform data-driven modeling of fluid flows. Approximations of the Koopman operator provide linear representations even for strongly nonlinear flows, which enables the application of standard linear methods for estimation and control under realistic flow conditions. In the past decade, we have witnessed several breakthroughs in obtaining low-dimensional approximations of the Koopman operators, providing a tractable reduced-order model for complex fluid flows using data from numerical simulations or experiments. In this thesis, we leverage these recent developments in operator-theoretic modeling of fluid flows and provide data-driven solutions to the flow control and sensing problems. The contributions of this thesis can be divided into three parts. In the first part, we introduce a novel method, low-rank Dynamic Mode Decomposition (lrDMD), for data-driven reduced-order modeling of fluid flows. While existing data-driven modeling methods fit an endomorphic linear function on a low-dimensional subspace, lrDMD approximates flow dynamics using a linear map between different subspaces. We show that this approach leads to the design of better reduced-order feedback controllers. We formulate a rank-constrained matrix optimization problem and propose two complementary methods to solve the problem. lrDMD outperforms existing methods in feedback control and optimal actuator placement. In the second part, we present a completely data-driven framework for sensor placement in fluid flows. This framework can be applied in conjunction with any reduced-order modeling technique that constructs a linear model for the flow dynamics. We formulate an optimization problem that minimizes the trace of a data-driven approximation of the estimation error covariance matrix, where the estimates are provided by a Kalman filter. We propose an efficient adjoint-based gradient descent method to solve the optimization problem. We show that sensors placed using our method lead to better performance in important applications, such as flow estimation and control, compared to existing data-driven sensor placement methods. In the third and final part, we propose a new method of interface tracking and reconstruction in multiphase flows using shadowgraphs or back-lit imaging data. First, we show that while traditional modeling methods provide valuable information about the spatio-temporal structure of flow instabilities, they are not able to resolve spatial or temporal discontinuities, such as the liquid-gas interface, in the data. To remedy this, we propose a two-step approach, using data-driven modeling techniques in conjunction with optical flow methods, that preserves sharp interfaces and provides reliable reconstruction and short-time prediction of the flow. We apply our method to an experimental liquid jet with a co-axial air-blast atomizer using back-lit imaging. Our method is able to accurately reconstruct and predict the flow while preserving the sharpness of the liquid-gas interface

Influence of customer focused mission statement on customer satisfaction

The purpose of this study is to examine the influence of customer-focused mission statements on customer satisfaction in selected cell phone manufacturing companies in the United States. The study employed content analysis for the mission statement and data from America customer satisfaction index (ACSI). In analysing our data, Pearson correlation, and multiple regression techniques were used. The result showed that product and service, technology, philosophy, self-concept, and public image mission statement components are strongly positively correlated with customer satisfaction. Customer, survival, growth and profitability and market mission statement components are insignificantly negatively correlated with customer satisfaction. The study, therefore, recommends that companies that want to remain competitive by enhancing customer satisfaction should formulate mission statements from a customer perspective so that they include product and service, technology, philosophy, self-concept, and public image components. The main limitation of the study represents the sample size and structure. This study empirically investigated the correlation and association of nine mission statement components with customer satisfaction.O

Consumers’ social media brand behaviors: uncovering underlying motivators and deriving meaningful consumer segments

The current research identifies the range of social media brand behaviors (i.e., brand touch points) that consumers can exhibit on social media, and subsequently queries a representative sample of consumers with regard to such behaviors. The analysis reveals four underlying motivators for consumers’ social media behaviors, including brand tacit engagement, brand exhibiting, brand patronizing and brand deal seeking. These motivators are used to derive meaningful consumer segments identified as content seekers, observers, deal hunters, hard-core fans, posers and respectively patronizers, and described through co-variates including brand loyalty, brand attachment and social media usage. The findings are critically discussed in the light of literature on the needs that consumers meet through brand consumption and on the types of relationships consumers build with brands. Not least, the managerial implications of the current findings are debated

Conceptualizing and measuring strategy implementation – a multi-dimensional view

Through quantitative methodological approaches for studying the strategic management and planning process, analysis of data from 208 senior managers involved in strategy processes within ten UK industrial sectors provides evidence on the measurement properties of a multi-dimensional instrument that assesses ten dimensions of strategy implementation. Using exploratory factor analysis, results indicate the sub-constructs (the ten dimensions) are uni-dimensional factors with acceptable reliability and validity; whilst using three additional measures, and correlation and hierarchical regression analysis, the nomological validity for the multi-dimensional strategy implementation construct was established. Relative importance of ten strategy implementation dimensions (activities) for practicing managers is highlighted, with the mutually and combinative effects drawing conclusion that senior management involvement leads the way among the ten key identified activities vital for successful strategy implementation

Students\u27 Perceptions of Social Loafing: Its Antecedents and Consequences in Undergraduate Business Classroom Teams

We report the findings from a 2-stage study of student perceptions of social loafing as it occurs in undergraduate business classroom teams. Given the popularity of student teams as a teaching and learning tool in undergraduate business classrooms, as well as the near absence of research that has focused on students\u27 definition of the problem, our purpose was to develop preliminary findings and spur new thinking about social loafing in this context. A definition of the construct was developed, and its key antecedents and consequences identified by way of exploratory analysis of student perceptions. The resulting hypotheses and conceptual model were tested using a structural equations model by way of a survey of 349 students taking classes in an undergraduate business program. Student perceptions of social loafing seem more complex than current views suggest. They point to student apathy and social disconnectedness as antecedents, and note that they take compensatory action when members of their teams social loaf. We identify issues for future research and discuss implications for instructors and program administrators

An empirical investigation of the marketing strategy implementation process

This dissertation is an empirical investigation of the marketing strategy implementation process. It aims to develop a holistic understanding of how managers implement market related strategies and realize intended objectives. An extensive review of implementation literature from diverse academic disciplines was initially conducted. Four research questions that appeared relevant to the marketing strategy implementation process and potentially contributive to the current literature were identified from this review. The research question and the study were exploratory, the methodology was naturalistic and conclusions were drawn inductively. Qualitative data was collected via open ended questions from personal interviews with forty managers selected from small sized technology based firms located in the Central Upstate New York area. The interviews were pre-structured, however, additional probing questions were used in all interviews. In terms of the major findings, the concept of marketing strategy implementation evoked diffuse gestalts among the managers included in the study, and were generally related to sales, tasks, and planning. The nature of planning activities ranged on a continuum of no planning on the one hand to highly formalized and structured planning on the other. Similarly, implementation processes ranged along a continuum of ad hoc and disconnected activities on the one hand to a thoughtful, connected and coherent stream of marketing led organizational activities on the other. Planning and implementation were highly interrelated. Flexibility and responsiveness in both the planning and implementation functions to accommodate shifts in markets and customer preferences were widely cited as crucial for marketing implementation. In implementing their marketing plans and strategies, managers spent considerable energies directed at integrating the firms diverse functional groups (e.g., sales, customer services, manufacturing, engineering, R&D) and coordinating their activities with marketing initiatives aimed at meeting customer needs. Several tactics used by managers to foster such integration were identified. The marketing strategy implementation process appeared complex, gestaltic, and a highly inter-related process concerned with integrating the firm\u27s skills and competencies with customer needs. A number of managerial recommendations, as well as questions for future research also were developed from the data

Fork of Supplementary data: The architecture of SARS-CoV-2 transcriptome

High-throughput RNA sequencing of Vero lysates infected with SARS-CoV-2 generated with Oxford Nanopore Technologies direct RNA sequencing and MGITech DNBseq