While natural language interfaces (NLIs) are increasingly utilized to simplify the interaction with data visualization tools, improving and adapting the NLIs to the individual needs of users still requires the support...
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ISBN:
(纸本)9781450391566
While natural language interfaces (NLIs) are increasingly utilized to simplify the interaction with data visualization tools, improving and adapting the NLIs to the individual needs of users still requires the support of developers. ONYX introduces an interactive task learning (ITL) based approach which enables NLIs to learn from users through natural interactions. Users can personalize the NLI with new commands using direct manipulation, known commands, or by combining both. To further support users during the training process, we derived two design goals for the user interface, namely providing suggestions based on sub-parts of the command and addressing ambiguities through follow-up questions and instantiated them in ONYX. In order to trigger reflections and gain feedback on possible design trade-offs of ONYX and the instantiated design goals, we performed a formative user study to understand how to successfully integrate the suggestions and follow-up question into the interaction.
The autonomy of being able to visualize and analyze existing data and the knowledge that comes from it, is fundamental for the increase of the competitive advantage of organizations. In this context, data Visualizatio...
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ISBN:
(纸本)9789899843493
The autonomy of being able to visualize and analyze existing data and the knowledge that comes from it, is fundamental for the increase of the competitive advantage of organizations. In this context, data visualization tools are great aids in decision making by following techniques of Self-Service Business Intelligence. They aim to improve agility in different business departments, enable their users to create their own reports and access data at any time without being dependent on specialists. But this choice has to be made based on a good analysis of the companies and what they need to be able to find the one that best suits their needs. In order to improve this choice, is made a comparative evaluation of the four most used data visualization tools: Tableau, Microsoft Power BI, Sisense e QlikView.
Climate change is expected to alter the environmental factors that are known to influence the corrosion process, creating additional uncertainties in the long-term performance of reinforced concrete (RC) decks. With d...
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Climate change is expected to alter the environmental factors that are known to influence the corrosion process, creating additional uncertainties in the long-term performance of reinforced concrete (RC) decks. With due consideration of site-specific exposure and environmental conditions, this study aims to investigate the degree to which projected climate change may impact corrosion-induced damage for RC bridges. A hierarchical two-tier framework was developed incorporating the material deterioration process simulation at the local element level, and a component level prediction of the corrosion-induced damage severity and extent over the bridge deck domain. The predictive accuracy of this framework was validated against the historical bridge inspection data. Case studies were performed for decks located in Toronto and Victoria to investigate the influence of climate data resolution and climate projection models on deck deterioration status. At last, ANN (artificial neural network) and SVM (support vector machine) approaches were used to generate a series of cartographic expressions to reveal how the corrosion-induced deck deterioration risk varies with the region due to the difference in the environmental conditions. These maps can serve as visual tools to express the corrosion damage risks for different bridge locations and to formulate region-based durability design requirements.
Users are increasingly empowered to personalize natural language interfaces (NLIs) by teaching how to handle new natural language (NL) inputs. However, our formative study found that when teaching new NL inputs, users...
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ISBN:
(纸本)9781450394215
Users are increasingly empowered to personalize natural language interfaces (NLIs) by teaching how to handle new natural language (NL) inputs. However, our formative study found that when teaching new NL inputs, users require assistance in clarifying ambiguities that arise and want insight into which parts of the input the NLI understands. In this paper we introduce ONYX, an intelligent agent that interactively learns new NL inputs by combining NL programming and programming-by-demonstration, also known as multi-modal interactive task learning. To address the aforementioned challenges, ONYX provides suggestions on how ONYX could handle new NL inputs based on previously learned concepts or user-defned procedures, and poses follow-up questions to clarify ambiguities in user demonstrations, using visual and textual aids to clarify the connections. Our evaluation shows that users provided with ONYX's new features achieved signifcantly higher accuracy in teaching new NL inputs (median: 93.3%) in contrast to those without (median: 73.3%).
Communicating key finds is a crucial part of the research process. datavisualization is the field of graphically representing data to help communicate key findings. Building on previous chapters around data manipulat...
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Communicating key finds is a crucial part of the research process. datavisualization is the field of graphically representing data to help communicate key findings. Building on previous chapters around data manipulating using the R programming language this, chapter will explore how to use R to plot data and generate high-quality graphics. It will cover plotting using the base R plotting functionality and introduce the famous ggplot2 package [2] that is widely used for datavisualization in R. After this general introduction to data visualization tools, the chapter will explore more specific datavisualization techniques for metagenomics data and their use cases using these basic packages. less
Mapping how proteins form complexes and change binding partners is central to understanding cell signaling. Bulk biochemistry can provide a summary of what complexes are present in a cell, but information about the di...
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Mapping how proteins form complexes and change binding partners is central to understanding cell signaling. Bulk biochemistry can provide a summary of what complexes are present in a cell, but information about the diversity of individual protein complexes is lost. Here, we describe single-cell, single-molecule pull-down (sc-SiMPull), a TIRFTotal internal reflection fluorescence microscopy (TIRF) microscopy-based coimmunoprecipitation method, to visualize thousands of individual proteins, their binding partners, and protein complex stoichiometry directly from single-cell lysate. By iterating sc-SiMPull over time, temporal dynamics of protein complexes in response to signaling can be constructed. less
Resistance to chemotherapy is one major obstacle in current cancer treatment. Therefore, understanding the molecular basis of the acquisition of resistance is vital for the design and development of appropriate cancer...
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Resistance to chemotherapy is one major obstacle in current cancer treatment. Therefore, understanding the molecular basis of the acquisition of resistance is vital for the design and development of appropriate cancer therapy. Importantly, acquisition of resistance is not a single-step process, and the molecular signature of cells dynamically changes during this process. With the advent of next-generation omic technologies, today one can precisely map the molecular alterations not only in a population of tumor cells but also at the single-cell level as they attain chemo-resistance. In this chapter, we describe a detailed transcriptomic pipeline following next-generation sequencing for mapping alteration in expression during the process of attainment of resistance. We provide comprehensive information on the process to (1) track the differential expression of transcripts, (2) understand the gene ontology functions, (3) filter out candidate key genes, (4) identify the pathways regulated by them, and (5) generate a map of their probable interactions. We assume that our analytical method will be useful for research in this direction. less
Natural killer (NK) cells are an important component of the cancer immune surveillance system. They are regulated by germline-encoded receptors that activate and inhibit their effector function, such as secretion of c...
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Natural killer (NK) cells are an important component of the cancer immune surveillance system. They are regulated by germline-encoded receptors that activate and inhibit their effector function, such as secretion of cytokines and direct lysis of tumor cells and virus-infected cells. Without the need to be primed by prior exposure to tumor antigen, NK cells can detect ligands expressed on tumor cells and selectively kill these cells. NK cells are under strict control by inhibitory receptors that bind to HLA class I on target cells and block early activation signals, thus preventing lysis of target cells. The sensitivity to lysis by NK cells is therefore determined to a large extent by the expression of HLA class I molecules on tumor cells. In addition to receptor–ligand interactions that occur at NK–target cell synapses, many other factors determine the sensitivity of tumor cells to lysis by NK. Intrinsic properties of tumor cells, such as their metabolism and signaling networks establish a threshold above which they will succumb to the death pathways triggered by NK cell attack. Here we provide a protocol for a genome-wide CRISPR screen in tumor cells to identify factors that regulate their sensitivity to primary human NK cells. Tumor cells first transduced for expression of Cas9 are then transduced with a guide RNA (gRNA) library and co-cultured with NK cells. Deep sequencing of the library generated from the genome of tumor cells that survived the selection by NK cells and analysis of the distribution of guide RNAs is performed to identify genes that promote either sensitivity or resistance to NK-mediated killing. The contribution of individual genes to tumor sensitivity can be validated by knockouts using individual gRNAs. The techniques and workflow described here could be applied to primary tumors from cancer patients and reveal tumor-specific points of vulnerability that could be exploited for cancer immunotherapy, such as checkpoint blockade or expression of
“Omics” technologies (genomics, transcriptomics, proteomics, metabolomics, etc.) have significantly improved our understanding of biological systems. They have become standard tools in biological research, for examp...
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“Omics” technologies (genomics, transcriptomics, proteomics, metabolomics, etc.) have significantly improved our understanding of biological systems. They have become standard tools in biological research, for example, identifying and unraveling transcriptional networks, building predictive models, and discovering candidate biomarkers. The rapid increase of omics data presents both a challenge and great potential when it comes to providing valuable insights into the underlying patterns of the investigated biological processes. The challenge is extracting, processing, integrating, and interpreting the corresponding datasets. The potential, on the other hand, arises from generation of verifiable hypotheses to understand molecular mechanisms behind biological processes, for example, gene expression patterns. Exploratory data analysis techniques are used to get a first impression of the important characteristics of a dataset and to reveal its underlying structure. However, investigators are often faced with the difficulties of managing the high-dimensional nature of the data. In order to efficiently analyze biological data and to gain a deeper understanding of underlying biological mechanisms, it is essential to have robust and interactive data visualization tools. less
Systematic complex genetic interaction studies have provided insight into high-order functional redundancies and genetic network wiring of the cell. Here, we describe a method for screening and quantifying trigenic in...
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Systematic complex genetic interaction studies have provided insight into high-order functional redundancies and genetic network wiring of the cell. Here, we describe a method for screening and quantifying trigenic interactions from ordered arrays of yeast strains grown on agar plates as individual colonies. The protocol instructs users on the trigenic synthetic genetic array analysis technique, τ-SGA, for high-throughput screens. The steps describe construction of the double-mutant query strains and the corresponding single-mutant control query strains, which are screened in parallel in two replicates. The screening experimental set-up consists of sequential replica-pinning steps that enable automated mating, meiotic recombination and successive haploid selection steps for the generation of triple mutants, which are scored for colony size as a proxy for fitness, which enables the calculation of trigenic interactions. The procedure described here was used to conduct 422 trigenic interaction screens, which generated ~460,000 yeast triple mutants for trigenic interaction analysis. Users should be familiar with robotic equipment required for high-throughput genetic interaction screens and be proficient at the command line to execute the scoring pipeline. Large-scale screen computational analysis is achieved by using MATLAB pipelines that score raw colony size data to produce τ-SGA interaction scores. Additional recommendations are included for optimizing experimental design and analysis of smaller-scale trigenic interaction screens by using a web-based analysis system, SGAtools. This protocol provides a resource for those who would like to gain a deeper, more practical understanding of trigenic interaction screening and quantification methodology. less
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