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Using remote sensing in soybean breeding: estimating soybean grain yield and soybean cyst nematode populationsAslan, Hatice January 1900 (has links)
Master of Science / Department of Agronomy / William T. Schapaugh / Remote sensing technologies might serve as indirect selection tools to improve phenotyping to differentiate genotypes for yield in soybean breeding program as well as the assessment of soybean cyst nematode (SCN), Heterodera glycines. The objective of these studies were to: i) investigate potential use of spectral reflectance indices (SRIs) and canopy temperature (CT) as screening tools for soybean grain yield in an elite, segregating population; ii) determine the most appropriate growth stage(s) to measure SRI’s for predicting grain yield; and iii) estimate SCN population density among and within soybean cultivars utilizing canopy spectral reflectance and canopy temperature. Experiment 1 was conducted at four environments (three irrigated and one rain-fed) in Manhattan, KS in 2012 and 2013. Each environment evaluated 48 F4- derived lines. In experiment 2, two SCN resistant cultivars and two susceptible cultivars were grown in three SCN infested field in Northeast KS, in 2012 and 2013. Initial (Pi) and final SCN soil population (Pf) densities were obtained. Analyses of covariance (ANCOVA) revealed that the green normalized vegetation index (GNDVI) was the best predictive index for yield compared to other SRI’s and differentiated genotype performance across a range of reproductive growth stages. CT did not differentiate genotypes across environments. In experiment 2, relationships between GNDVI, reflectance at single wavelengths (675 and 810 nm) and CT with Pf were not consistent across cultivars or environments. Sudden death syndrome (SDS) may have confounded the relationships between remote sensing data and Pf. Therefore, it would be difficult to assess SCN populations using remote sensing based on these results.
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Novel methods for the rapid and selective analysis of biological samples using hyphenated ion mobility-mass spectrometry with ambient ionizationDevenport, Neil A. January 2014 (has links)
The increased use of mass spectrometry in the clinical setting has led to a demand for high sample throughput. Developments such as ultra high performance liquid chromatography and the ambient ionization techniques enable high sample throughput by reducing chromatographic run times or by removing the requirement for sample preparation and fractionation prior to analysis. This thesis assesses the reproducibility and robustness of these high throughput techniques for the analysis of clinical and pharmaceutical samples by ion mobility-mass spectrometry. The rapid quantitative analysis of the urinary biomarkers of chronic obstructive pulmonary disease, desmosine and isodesmosine has been performed by ultra high performance liquid chromatography combined with ion mobility-mass spectrometry. The determination of health status based on the free unbound fraction rather than the total bound and unbound desmosine and isodesmosine, significantly reduces the time taken in sample preparation. The potential for direct analysis of the urinary metabolites from undeveloped TLC plates using a solvent extraction surface sample probe is demonstrated. The use of a solvent gradient for the extraction separates urinary metabolites from salts and other matrix components and allows fractionation of the sample as a result of differential retention on the undeveloped RP-TLC plate. This separation, combined with ion mobility-mass spectrometry provides a rapid ambient ionization method for urinary profiling. The combination of a thermal desorption probe with extractive electrospray ionization has been applied to the direct detection of a known genotoxic impurity from a surrogate active pharmaceutical ingredient. The volatility of the impurity compared to the matrix, allowed selective thermal desorption of the analyte, which was ionized by extractive electrospray and detected by mass spectrometry. The use of a rapid on-probe derivatisation reaction, combined with thermal desorption is demonstrated for the direct determination of urinary creatinine. The aqueous acylation of creatinine significantly increases the volatility of the analyte enabling separation from the urine matrix and analysis by thermal desorption extractive electrospray combined with ion mobility-mass spectrometry.
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RNAi Screening of the Kinome to Identify Mediators of proliferation and trastuzumab (Herceptin) resistance in HER2 Breast CancersLapin, Valentina 17 July 2013 (has links)
Breast cancers with overexpression or amplification of the HER2 tyrosine kinase receptor are more aggressive, resistant to chemotherapy, and associated with a worse prognosis. Currently, these breast cancers are treated with the monoclonal antibody trastuzumab (Herceptin®). Unfortunately, not all patients respond to trastuzumab drug therapy; some patients show de novo resistance, while others acquire resistance during treatment. This thesis describes our RNAi studies to identify novel regulators of the HER2 signaling pathway in breast cancer.
Three kinome-wide siRNA screens were performed on five HER2 amplified and seven HER2 non-amplified breast cancer cell lines, two normal breast cell lines, as well as two HER2-positive breast cancer cell lines with acquired trastuzumab resistance and their isogenic trastuzumab-sensitive controls. To understand the main kinase drivers of HER2 signaling, we performed a comprehensive screen that selected against growth inhibitors of the non-HER2 amplified breast cancer cell lines. This screen identified the loss of the HER2/HER3 heterodimer as the most prominent selective inhibitor of HER2-amplified breast cancers. In a trastuzumab sensitization screen on five trastuzumab-treated breast cancer cell lines, we identified several siRNA against the PI3K pathway as well as various other signaling pathways that inhibited proliferation. Finally, in a screen for acquired trastuzumab resistance, PKCη and its downstream targets were identified. Loss of PKCη resulted in a decrease in G1/S transition and upregulation of the cyclin dependent kinase inhibitor p27. Initial data suggest that PKCη promotes p27 ubiquitination and degradation.
Taken together, these studies provide novel insight into the complex signaling of HER2-positive breast cancers and the mechanisms of resistance to trastuzumab therapy. This work describes how various kinases can modulate cell proliferation, and points to possible novel drug targets for the treatment of HER2-positive breast cancers.
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The Automation of Glycopeptide Discovery in High Throughput MS/MS DataSwamy, Sajani January 2004 (has links)
Glycosylation, the addition of one or more carbohydrates molecules to a protein, is crucial for many cellular processes. Aberrant glycosylation is a key marker for various diseases such as cancer and rheumatoid arthritis. It has also recently been discovered that glycosylation is important in the ability of the Human Immunodeficiency Virus (HIV) to evade recognition by the immune system. Given the importance of glycosylation in disease, major efforts are underway in life science research to investigate the glycome, the entire glycosylation profile of an organelle, cell or tissue type. To date, little bioinformatics research has been performed in glycomics due to the complexity of glycan structures and the low throughput of carbohydrate analysis. Recent advances in mass spectrometry (MS) have greatly facilitated the analysis of the glycome. Increasingly, this technology is preferred over traditional methods of carbohydrate analysis which are often laborious and unsuitable for low abundance glycoproteins. When subject to mass spectrometry with collision-induced dissociation, glycopeptides produce characteristic MS/MS spectra that can be detected by visual inspection. However, given the high volume of data output from proteome studies today, manually searching for glycopeptides is an impractical task. In this thesis, we present a tool to automate the identification of glycopeptide spectra from MS/MS data. Further, we discuss some methodologies to automate the elucidation of the structure of the carbohydrate moiety of glycopeptides by adapting traditional MS/MS ion searching techniques employed in peptide sequence determination. MS/MS ion searching, a common technique in proteomics, aims to interpret MS/MS spectra by correlating structures from a database to the patterns represented in the spectrum. The tool was tested on high throughput proteomics data and was shown to identify 97% of all glycopeptides present in the test data. Further, the tool assigned correct carbohydrate structures to many of these glycopeptide MS/MS spectra. Applications of the tool in a proteomics environment for the analysis of glycopeptide expression in cancer tissue are also be presented.
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Mobile high-throughput phenotyping using watershed segmentation algorithmDammannagari Gangadhara, Shravan January 1900 (has links)
Master of Science / Department of Computing and Information Sciences / Mitchell L. Neilsen / This research is a part of BREAD PHENO, a PhenoApps BREAD project at K-State which combines contemporary advances in image processing and machine vision to deliver transformative mobile applications through established breeder networks. In this platform, novel image analysis segmentation algorithms are being developed to model and extract plant phenotypes. As a part of this research, the traditional Watershed segmentation algorithm has been extended and the primary goal is to accurately count and characterize the seeds in an image. The new approach can be used to characterize a wide variety of crops. Further, this algorithm is migrated into Android making use of the Android APIs and the first ever user-friendly Android application implementing the extended Watershed algorithm has been developed for Mobile field-based high-throughput phenotyping (HTP).
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Data Integration of High-Throughput Proteomic and Transcriptomic Data based on Public Database KnowledgeWachter, Astrid 22 March 2017 (has links)
No description available.
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Phage display to identify functional resistance mutations to RigosertibFilipovic, Nedim 01 January 2017 (has links)
In vitro protein selection has had major impacts in the field of protein engineering. Traditional screens assay individual proteins for specific function. Selection, however, analyzes a pool of mutants and yields the best variants. Phage display, a successful selection technique, also provides a reliable link between variant phenotype and genotype. It can also be coupled with high throughput sequencing to map protein mutations; potentially highlighting vital mutations in variants. We propose to apply this technique to cancer therapy. RAF, a serine/threonine kinase, is critical for cell regulation in mammals. RAF can be activated by oncogenic RAS, found in over 30% of cancers, to drive cancer proliferation. Rigosertib, a benzyl styryl sulfone in phase III clinical trials for myelodysplastic syndrome (MDS), is an inhibitor of the RAS binding domain (RBD) in RAF. Phage display can be used to select RAF mutants for RAS binding affinity, in the presence of Rigosertib. High-throughput sequencing of these variants can provide a means of anticipating, and mapping resistance to this anti-cancer drug.
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Highly comparative time-series analysisFulcher, Benjamin D. January 2012 (has links)
In this thesis, a highly comparative framework for time-series analysis is developed. The approach draws on large, interdisciplinary collections of over 9000 time-series analysis methods, or operations, and over 30 000 time series, which we have assembled. Statistical learning methods were used to analyze structure in the set of operations applied to the time series, allowing us to relate different types of scientific methods to one another, and to investigate redundancy across them. An analogous process applied to the data allowed different types of time series to be linked based on their properties, and in particular to connect time series generated by theoretical models with those measured from relevant real-world systems. In the remainder of the thesis, methods for addressing specific problems in time-series analysis are presented that use our diverse collection of operations to represent time series in terms of their measured properties. The broad utility of this highly comparative approach is demonstrated using various case studies, including the discrimination of pathological heart beat series, classification of Parkinsonian phonemes, estimation of the scaling exponent of self-affine time series, prediction of cord pH from fetal heart rates recorded during labor, and the assignment of emotional content to speech recordings. Our methods are also applied to labeled datasets of short time-series patterns studied in temporal data mining, where our feature-based approach exhibits benefits over conventional time-domain classifiers. Lastly, a feature-based dimensionality reduction framework is developed that links dependencies measured between operations to the number of free parameters in a time-series model that could be used to generate a time-series dataset.
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Screening for inhibitors of and novel proteins within the homologous recombination DNA repair pathwayKingham, Guy L. January 2012 (has links)
The homologous recombination (HR) pathway of DNA repair is essential for the faithful repair of double-stranded DNA breaks (DSBs) in all organisms and as such helps maintain genomic stability. Furthermore, HR is instrumental in the cellular response to exogenous DNA damaging agents such as those used in the clinic for chemo- and radiotherapy. HR in humans is a complex, incompletely understood process involving numerous stages and diverse biochemical activities. Advancing our knowledge of the HR pathway in humans aids the understanding of how chemo- and radiotherapies act and may be used to develop novel therapeutic strategies. Recent studies have identified inhibition of HR as one of the mechanisms via which a number of recently developed chemotherapeutics have their effect. Accordingly, the clinical potential of HR inhibitors is under investigation. My work has centred around the identification of both novel HR proteins and novel, small molecule HR inhibitors. To further these aims, I have successfully employed high-throughput RNAi and small molecule screening strategies. RNAi screens are commonly used to identify genes involved in a given cellular process via genetic loss of function, whilst small molecule, cell based screens are a powerful tool in the drug discovery process.
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A Comparative Analysis Of The Moose Rumen Microbiota And The Pursuit Of Improving Fibrolytic Systems.Pellegrini, Suzanne Ishaq 01 January 2015 (has links)
The goal of the work presented herein was to further our understanding of the rumen microbiota and microbiome of wild moose, and to use that understanding to improve other processes. The moose has adapted to eating a diet of woody browse, which is very high in fiber, but low in digestibility due to the complexity of the plant polysaccharides, and the presence of tannins, lignin, and other plant-secondary compounds. Therefore, it was hypothesized that the moose would host novel microorganisms that would be capable of a wide variety of enzymatic functions, such as improved fiber breakdown, metabolism of digestibility-reducing or toxic plant compounds, or production of functional metabolites, such as volatile fatty acids, biogenic amines, etc.
The first aim, naturally, was to identify the microorganisms present in the rumen of moose, in this case, the bacteria, archaea, and protozoa. This was done using a variety of high-throughput techniques focusing on the SSU rRNA gene (see CHAPTERS 2-5). The second aim was to culture bacteria from the rumen of the moose in order to study their biochemical capabilities (see CHAPTERS 6-7). The final aim was to apply those cultured bacterial isolates to improve other systems. Specifically, bacteria from the rumen of the moose was introduced to young lambs in order to colonize the digestive tract, speed the pace of rumen development, and improve dietary efficiency (see CHAPTER 8).
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