176 research outputs found
THROUGH GLOBAL TELEVISION FORMATS
No full textThis dissertation is dedicated to the love of my life and “war-time consigliere”, Gil Shahaf, and to our little miracle-baby, Ella, who participated in utero and as a newborn in the writing efforts. Without your love and support none of this would have been possible. Acknowledgments The completion of this dissertation would not have been possible without the support and help of a great many people- family, friends and colleagues. I wish to take this opportunity to express my gratitude to all those people who made it possible. My deepest gratitude is to my advisor, Dr. Shanti Kumar. I feel immensely fortunate to have had the opportunity to work with such an outstanding scholar, whose wisdom, brilliance, and knowledge are surpassed only by his profound humanity. To say that Shanti has been an invaluable source of guidance, inspiration, and support through some of the most intense and exciting years of my life would be an understatement. As an excellent, rigorous, and insightful academic advisor he constantly challenged me to take my research to the next level, making me dig deeper and expose the depth of my own argumentation. Perhaps even more importantly, he was always there for me, showing
Bioinformatic solutions for addressing the grape metabolome
Get PDFA complete overview of all metabolites present in a particular organism forms an invaluable source of information, even if available in only semiquantitative or qualitative form – the human metabolome database is a good example. For other organisms, such resources are rarely available. In our laboratories we are concentrating on the elucidation of the metabolome of the grape berry, and I will describe the challenges that arise in attempting to obtain a comprehensive overview of all chemical compounds, distributed over many different chemical classes. This wide variety in metabolites forces the use of several different analytical platforms, each one necessitating its own analytical optimisation [1-3].
Conversely, data analysis is a complicated and elaborate process in which several sources of information need to be combined. The complex nature of the raw data necessitate extensive fine-tuning, and building in quality control steps along the process is vital. While commercial software, as provided by, e.g., instrument manufacturers, has shown dramatic improvements in capabilities, flexibility and quality, it is in general a black box and, more often than not, vendor-specific. Currently, open-source software forms a viable alternative, with powerful methods and a large user community. The only downside is the level of expertise required: these programs can only be used with adequate bioinformatics support. This contribution highlights the elements of our in-house data-processing pipeline for the elucidation of the grape metabolome, processing hundreds of large data files and yielding intensity values for thousands of variables. The results contain both known and unknown compounds, and serve as the starting point for more elaborate statistical analyses. Practical implications of such labour- and time-intensive scientific projects will be discussed as wel
Immunoglobulin variable-region gene mutational lineage tree analysis: application to autoimmune diseases
Get PDFLineage trees have frequently been drawn to illustrate diversification, via somatic hypermutation (SHM), of immunoglobulin variable-region (IGV) genes. In order to extract more information from IGV sequences, we developed a novel mathematical method for analyzing the graphical properties of IgV gene lineage trees, allowing quantification of the differences between the dynamics of SHM and antigen-driven selection in different lymphoid tissues, species, and disease situations. Here, we investigated trees generated from published IGV sequence data from B cell clones participating in autoimmune responses in patients with Myasthenia Gravis (MG), Rheumatoid Arthritis (RA), and Sjögren's Syndrome (SS). At present, as no standards exist for cell sampling and sequence extraction methods, data obtained by different research groups from two studies of the same disease often vary considerably. Nevertheless, based on comparisons of data groups within individual studies, we show here that lineage trees from different individual patients are often similar and can be grouped together, as can trees from two different tissues in the same patient, and even from IgG- and IgA-expressing B cell clones. Additionally, lineage trees from most studies reflect the chronic character of autoimmune diseases
Deception detection in dialogues
Get PDFIn the social media era, it is commonplace to engage in written conversations. People sometimes even form connections across large distances, in writing. However, human communication is in large part non-verbal. This means it is now easier for people to hide their harmful intentions. At the same time, people can now get in touch with more people than ever before. This puts vulnerable groups at higher risk for malevolent interactions, such as bullying, trolling, or predatory behavior. Furthermore, such growing behaviors have most recently led to waves of fake news and a growing industry of deceit creators and deceit detectors. There is now an urgent need for both theory that explains deception and applications that automatically detect deception.
In this thesis I address this need with a novel application that learns from examples and detects deception reliably in natural-language dialogues. I formally define the problem of deception detection and identify several domains where it is useful. I introduce and evaluate new psycholinguistic features of deception in written dialogues for two datasets. My results shed light on the connection between language, deception, and perception. They also underline the challenges and difficulty of assessing perceptions from written text.
To automatically learn to detect deception I first introduce an expressive logical model and then present a probabilistic model that simplifies the first and is learnable from labeled examples. I introduce a belief-over-belief formalization, based on Kripke semantics and situation calculus. I use an observation model to describe how utterances are produced from the nested beliefs and intentions. This allows me to easily make inferences about these beliefs and intentions given utterances, without needing to explicitly represent perlocutions. The agents’ belief states are filtered with the observed utterances, resulting in an updated Kripke structure.
I then translate my formalization to a practical system that can learn from a small dataset and is able to perform well using very little structural background knowledge in the form of a relational dynamic Bayesian network structure.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-08-01The student, Codruta Girlea, accepted the attached license on 2017-07-11 at 17:06.The student, Codruta Girlea, submitted this Dissertation for approval on 2017-07-11 at 17:12.This Dissertation was approved for publication on 2017-07-12 at 17:06.DSpace SAF Submission Ingestion Package generated from Vireo submission #11409 on 2018-03-02 at 13:01:34Made available in DSpace on 2018-03-02T19:59:34Z (GMT). No. of bitstreams: 3
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Previous issue date: 2017-07-12Embargo set by: Seth Robbins for item 105045
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Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 105045
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Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Only Restriction Lifted for Item 105045 on 2020-03-03T10:15:11Z
MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments
Get PDFDue to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments.In this paper we will review the major steps which constitute such a data processing pipeline, discussing them in the context of open source software for untargeted Liquid Chromatography Mass Spectrometry (LC-MS) and Gas Chromatography Mass Spectrometry (GC-MS) metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework
Lineage tree analysis of immunoglobulin variable-region gene mutations in autoimmune diseases: chronic activation, normal selection
Get PDFAutoimmune diseases show high diversity in the affected organs, clinical manifestations and disease dynamics. Yet they all share common features, such as the ectopic germinal centers found in many affected tissues. Lineage trees depict the diversification, via somatic hypermutation (SHM), of immunoglobulin variable-region (IGV) genes. We previously developed an algorithm for quantifying the graphical properties of IGV gene lineage trees, allowing evaluation of the dynamical interplay between SHM and antigen-driven selection in different lymphoid tissues, species, and disease situations. Here, we apply this method to ectopic GC B cell clones from patients with Myasthenia Gravis, Rheumatoid Arthritis, and Sjögren’s Syndrome, using data scaling to minimize the effects of the large variability due to methodological differences between groups. Autoimmune trees were found to be significantly larger relative to normal controls. In contrast, comparison of the measurements for tree branching indicated that similar selection pressure operates on autoimmune and normal control clones
Ig gene diversification and selection in follicular lymphoma, diffuse large B cell lymphoma and primary central nervous system lymphoma revealed by lineage tree and mutation analyses
No full textFollicular lymphoma (FL), diffuse large B cell lymphoma (DLBCL) and primary central nervous system lymphoma are B cell malignancies. FL and DLBCL have a germinal center origin. We have applied mutational analyses and a novel algorithm for quantifying shape properties of mutational lineage trees to investigate the nature of the diversification, somatic hypermutation and selection processes that affect B cell clones in these malignancies and reveal whether they differ from normal responses. Lineage tree analysis demonstrated higher diversification and mutations per cell in the lymphoma clones. This was caused solely by the longer diversification times of the malignant clones, as their recent diversification processes were similar to those of normal responses, implying similar mutation frequencies. Since previous analyses of antigen-driven selection were shown to yield false positives, we performed a corrected analysis of replacement and silent mutation patterns, which revealed selection against replacement mutations in the framework regions, responsible for the structural integrity of the B cell receptor, but not for positive selection for replacements in the complementary determining regions. Most replacements, however, were neutral or conservative, suggesting that if at all selection operates in these malignancies it is for structural B cell receptor integrity but not for antigen binding
Density of Gabor Systems Via the Short Time Fourier Transform
No full textWe apply a new approach to the study of the density of Gabor systems, and obtain a simple and straightforward proof to Ramanathan and Steger’s well-known result regarding the density of Gabor frames and Gabor Riesz sequences. Moreover, this point of view allows us to extend this result in several directions. The approach we use was first observed by Olevskii and the third author in their study of exponential systems, here we develop and simplify it further
Femtosecond Covariance Spectroscopy
Get PDFThe success of non-linear optics relies largely on pulse-to-pulse
consistency. In contrast, covariance based techniques used in photoionization
electron spectroscopy and mass spectrometry have shown that wealth of
information can be extracted from noise that is lost when averaging multiple
measurements. Here, we apply covariance based detection to nonlinear optical
spectroscopy, and show that noise in a femtosecond laser is not necessarily a
liability to be mitigated, but can act as a unique and powerful asset. As a
proof of principle we apply this approach to the process of stimulated Raman
scattering in alpha-quartz. Our results demonstrate how nonlinear processes in
the sample can encode correlations between the spectral components of
ultrashort pulses with uncorrelated stochastic fluctuations. This in turn
provides richer information compared to the standard non-linear optics
techniques that are based on averages over many repetitions with well-behaved
laser pulses. These proof-of-principle results suggest that covariance based
nonlinear spectroscopy will improve the applicability of fs non-linear
spectroscopy in wavelength ranges where stable, transform limited pulses are
not available such as, for example, x-ray free electron lasers which naturally
have spectrally noisy pulses ideally suited for this approach
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