Scholarly Work - Computer Science
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/3034
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Item Persistent Homology for the Quantitative Evaluation of Architectural Features in Prostate Cancer Histology(2019-02) Lawson, Peter; Sholl, Andrew B.; Brown, J. Quincy; Fasy, Brittany T.; Wenk, CarolaThe current system for evaluating prostate cancer architecture is the Gleason grading system which divides the morphology of cancer into five distinct architectural patterns, labeled 1 to 5 in increasing levels of cancer aggressiveness, and generates a score by summing the labels of the two most dominant patterns. The Gleason score is currently the most powerful prognostic predictor of patient outcomes; however, it suffers from problems in reproducibility and consistency due to the high intra-observer and inter-observer variability amongst pathologists. In addition, the Gleason system lacks the granularity to address potentially prognostic architectural features beyond Gleason patterns. We evaluate prostate cancer for architectural subtypes using techniques from topological data analysis applied to prostate cancer glandular architecture. In this work we demonstrate the use of persistent homology to capture architectural features independently of Gleason patterns. Specifically, using persistent homology, we compute topological representations of purely graded prostate cancer histopathology images of Gleason patterns 3,4 and 5, and show that persistent homology is capable of clustering prostate cancer histology into architectural groups through a ranked persistence vector. Our results indicate the ability of persistent homology to cluster prostate cancer histopathology images into unique groups with dominant architectural patterns consistent with the continuum of Gleason patterns. In addition, of particular interest, is the sensitivity of persistent homology to identify specific sub-architectural groups within single Gleason patterns, suggesting that persistent homology could represent a robust quantification method for prostate cancer architecture with higher granularity than the existing semi-quantitative measures. The capability of these topological representations to segregate prostate cancer by architecture makes them an ideal candidate for use as inputs to future machine learning approaches with the intent of augmenting traditional approaches with topological features for improved diagnosis and prognosis.Item Physiological dynamic compression regulates central energy metabolism in primary human chondrocytes(2018-02) Salinas, Daniel; Mumey, Brendan M.; June, Ronald K.Chondrocytes use the pathways of central metabolism to synthesize molecular building blocks and energy for cartilage homeostasis. An interesting feature of the in vivo chondrocyte environment is the cyclical loading generated in various activities (e.g., walking). However, it is unknown whether central metabolism is altered by mechanical loading. We hypothesized that physiological dynamic compression alters central metabolism in chondrocytes to promote production of amino acid precursors for matrix synthesis. We measured the expression of central metabolites (e.g., glucose, its derivatives, and relevant co-factors) for primary human osteoarthritic chondrocytes in response to 0–30 minutes of compression. To analyze the data, we used principal components analysis and ANOVA-simultaneous components analysis, as well as metabolic flux analysis. Compression-induced metabolic responses consistent with our hypothesis. Additionally, these data show that chondrocyte samples from different patient donors exhibit different sensitivity to compression. Most importantly, we find that grade IV osteoarthritic chondrocytes are capable of synthesizing non-essential amino acids and precursors in response to mechanical loading. These results suggest that further advances in metabolic engineering of chondrocyte mechanotransduction may yield novel translational strategies for cartilage repair.Item Robust Topological Inference: Distance To a Measure and Kernel Distance(2018-06) Chazal, Frederic; Fasy, Brittany T.; Lecci, Fabrizio; Michel, Bertrand; Rinaldo, Alessandro; Wasserman, LaryLet P be a distribution with support S. The salient features of S can be quantified with persistent homology, which summarizes topological features of the sublevel sets of the distance function (the distance of any point x to S). Given a sample from P we can infer the persistent homology using an empirical version of the distance function. However, the empirical distance function is highly non-robust to noise and outliers. Even one outlier is deadly. The distance-to-a-measure (DTM), introduced by Chazal et al. (2011), and the kernel distance, introduced by Phillips et al. (2014), are smooth functions that provide useful topological information but are robust to noise and outliers. Chazal et al. (2015) derived concentration bounds for DTM. Building on these results, we derive limiting distributions and confidence sets, and we propose a method for choosing tuning parameters.Item Genome Context Viewer: visual exploration of multiple annotated genomes using microsynteny(2017-12) Cleary, Alan M.; Farmer, AndrewThe Genome Context Viewer is a visual data-mining tool that allows users to search across multiple providers of genome data for regions with similarly annotated content that may be aligned and visualized at the level of their shared functional elements. By handling ordered sequences of gene family memberships as a unit of search and comparison, the user interface enables quick and intuitive assessment of the degree of gene content divergence and the presence of various types of structural events within syntenic contexts. Insights into functionally significant differences seen at this level of abstraction can then serve to direct the user to more detailed explorations of the underlying data in other interconnected, provider-specific tools.Item An Architecture of Cloud-Assisted Information Dissemination in Vehicular Networks(2016-05) Binhai, Zhu; Wu, Shaoen; Yang, QingVehicular network technology allows vehicles to exchange real-time information between each other, which plays a vital role in the development of future intelligent transportation systems Existing research on vehicular networks assumes that each vehicle broadcasts collected information to neighboring vehicles, so that information is shared among vehicles. The fundamental problem of what information is delivered with which vehicle(s), however, has not been adequately studied. We propose an innovative cloud-assisted architecture to facilitate intelligent information dissemination among vehicles. Within the novel architecture, virtual social connections between vehicles are created and maintained on the cloud. Vehicles with similar driving histories are considered friends in a vehicular social network (VSN). The closeness of the relation between two vehicles in a VSN is then modeled by the three-valued subjective logic model. Based on the closeness between vehicles, only relevant information will be delivered to vehicles that are likely interested in it. The cloud-assisted architecture coordinates vehicular social connection construction, VSN maintenance, vehicle closeness assessment, and information dissemination.Item Factored performance functions and decision making in continuous time Bayesian networks(2017-01) Sturlaugson, Liessman E.; Perreault, Logan J.; Sheppard, John W.The continuous time Bayesian network (CTBN) is a probabilistic graphical model that enables reasoning about complex, interdependent, and continuous-time subsystems. The model uses nodes to denote subsystems and arcs to denote conditional dependence. This dependence manifests in how the dynamics of a subsystem changes based on the current states of its parents in the network. While the original CTBN definition allows users to specify the dynamics of how the system evolves, users might also want to place value expressions over the dynamics of the model in the form of performance functions. We formalize these performance functions for the CTBN and show how they can be factored in the same way as the network, allowing what we argue is a more intuitive and explicit representation. For cases in which a performance function must involve multiple nodes, we show how to augment the structure of the CTBN to account for the performance interaction while maintaining the factorization of a single performance function for each node. We introduce the notion of optimization for CTBNs, and show how a family of performance functions can be used as the evaluation criteria for a multi-objective optimization procedure.Item Intensification of Dryland Cropping Systems for Bio-feedstock Production: Energy Analysis of Camelina(2015-12) Keshavarz-Afshar, Reza; Chen, ChengciCamelina (Camelina sativa L. Crantz), as a bioenergy and bio-product feedstock, may be grown as a rotation crop in the wheat-based cropping system to increase land use efficiency in the Northern Great Plains (NGP). In this study, which was conducted from 2008 to 2011 in central Montana, we evaluated the energy balance of three 2-year cop rotational sequences that included camelina-winter wheat (Triticum aestivum L.) (CAM-WW) and barley (Hordeum vulgare L.)-winter wheat (BAR-WW) compared with a traditional fallow-winter wheat (FAL-WW) rotation. Results indicated that 52 and 57 % more energy input was invested in CAM-WW and BAR-WW compared to FAL-WW system (9182 MJ ha−1), respectively. In all rotations, nitrogen fertilizer was the most energy-consuming input and accounted for 76, 68, and 69 % of the total energy used in wheat, barley, and camelina production, respectively. Averaged over 3 years, CAM-WW and BAR-WW systems yielded 34 and 29 % greater gross energy output compared with FAL-WW. The CAM-WW and BAR-WW also outperformed FAL-WW by 30 and 6 % in terms of net energy output. No significant differences in energy efficiency were found between the FAL-WW and CAM-WW systems. Taking into account of the greater net energy as well as similar values of energy use efficiency, the CAM-WW system performed better than the traditional FAL-WW system under rainfed conditions in central Montana. There is a good potential to improve the energy efficiency of the CAM-WW cropping system (by more than 26 %) through refinement of agronomic practices, mainly nitrogen fertilization and herbicide application, which can further enhance the sustainability of camelina feedstock production.Item Legume information system (LegumeInfo.org): a key component of a set of federated data resources for the legume family(2016-01) Dash, Sudhansu; Campbell, Jacqueline D.; Cannon, Ethalinda K.S.; Cleary, Alan M.; Huang, Wei; Kalberer, Scott R.; Karingula, Vijay; Rice, Alex G.; Singh, Jugpreet; Umale, Pooja E.; Weeks, Nathan T.; Wilkey, Andrew P.; Farmer, Andrew D.; Cannon, Steven B.Legume Information System (LIS), at http://legumeinfo.org, is a genomic data portal (GDP) for the legume family. LIS provides access to genetic and genomic information for major crop and model legumes. With more than two-dozen domesticated legume species, there are numerous specialists working on particular species, and also numerous GDPs for these species. LIS has been redesigned in the last three years both to better integrate data sets across the crop and model legumes, and to better accommodate specialized GDPs that serve particular legume species. To integrate data sets, LIS provides genome and map viewers, holds synteny mappings among all sequenced legume species and provides a set of gene families to allow traversal among orthologous and paralogous sequences across the legumes. To better accommodate other specialized GDPs, LIS uses open-source GMOD components where possible, and advocates use of common data templates, formats, schemas and interfaces so that data collected by one legume research community are accessible across all legume GDPs, through similar interfaces and using common APIs. This federated model for the legumes is managed as part of the ‘Legume Federation’ project (accessible via http://legumefederation.org), which can be thought of as an umbrella project encompassing LIS and other legume GDPsItem Proteins Related to the Type I Secretion System Are Associated with Secondary SecA_DEAD Domain Proteins in Some Species of Planctomycetes, Verrucomicrobia, Proteobacteria, Nitrospirae and Chlorobi(2015-06) Kamneva, Olga K.; Poudel, Saroj; Ward, Naomi L.A number of bacteria belonging to the PVC (Planctomycetes-Verrucomicrobia-Chlamydiae) super-phylum contain unusual ribosome-bearing intracellular membranes. The evolutionary origins and functions of these membranes are unknown. Some proteins putatively associated with the presence of intracellular membranes in PVC bacteria contain signal peptides. Signal peptides mark proteins for translocation across the cytoplasmic membrane in prokaryotes, and the membrane of the endoplasmic reticulum in eukaryotes, by highly conserved Sec machinery. This suggests that proteins might be targeted to intracellular membranes in PVC bacteria via the Sec pathway. Here, we show that canonical signal peptides are significantly over-represented in proteins preferentially present in PVC bacteria possessing intracellular membranes, indicating involvement of Sec translocase in their cellular targeting. We also characterized Sec proteins using comparative genomics approaches, focusing on the PVC super-phylum. While we were unable to detect unique changes in Sec proteins conserved among membrane-bearing PVC species, we identified (1) SecA ATPase domain re-arrangements in some Planctomycetes, and (2) secondary SecA_DEAD domain proteins in the genomes of some Planctomycetes, Verrucomicrobia, Proteobacteria, Nitrospirae and Chlorobi. This is the first report of potentially duplicated SecA in Gram-negative bacteria. The phylogenetic distribution of secondary SecA_DEAD domain proteins suggests that the presence of these proteins is not related to the occurrence of PVC endomembranes. Further genomic analysis showed that secondary SecA_DEAD domain proteins are located within genomic neighborhoods that also encode three proteins possessing domains specific for the Type I secretion system.Item Identification of MicroRNAs and Transcript Targets in Camelina sativa by Deep Sequencing and Computational Methods(2015-03) Poudel, Saroj; Niranjan, Aryal; Lu, ChaofuCamelina sativa is an annual oilseed crop that is under intensive development for renewable resources of biofuels and industrial oils. MicroRNAs, or miRNAs, are endogenously encoded small RNAs that play key roles in diverse plant biological processes. Here, we conducted deep sequencing on small RNA libraries prepared from camelina leaves, flower buds and two stages of developing seeds corresponding to initial and peak storage products accumulation. Computational analyses identified 207 known miRNAs belonging to 63 families, as well as 5 novel miRNAs. These miRNAs, especially members of the miRNA families, varied greatly in different tissues and developmental stages. The predicted miRNA target genes are involved in a broad range of physiological functions including lipid metabolism. This report is the first step toward elucidating roles of miRNAs in C. sativa and will provide additional tools to improve this oilseed crop for biofuels and biomaterials.