Search Results - Bayesian disease mapping.

Mapping QTL for multiple traits using Bayesian statistics by Xu, Chenwu, Wang, Xuefeng, Li, Zhikang, Xu, Shizhong

“…We also apply the method to mapping QTLs responsible for multiple disease resistances to the blast fungus of rice. …”
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Adding Bayesian disease mapping and co-factor analysis to the PAZ project in the Lake Victoria Crest, Kenya by Dopfer, D., Amene, E., Doble, L., Glanville, William A. de, Fèvre, Eric M.

“…The data from the PAZ Project will be analyzed using (1) Principal Component Analysis (PCA); (2) Cluster Analysis (CA); and finally (3) Bayesian Disease Mapping (BDM) methods. The proposed oral presentation will describe the project and strategic plans for and the preliminary outcomes of the data analysis.…”
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Bayesian geostatistical analysis and prediction of Rhodesian human African trypanosomiasis by Wardrop, N.A., Atkinson, P.M., Gething, P.W., Fèvre, Eric M., Picozzi, K., Kakembo, A.S.

“…Predictive mapping indicates an increased risk of high HAT prevalence in the future in areas surrounding livestock markets, demonstrating the importance of livestock trading for continuing disease spread. …”
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Genome-wide association mapping in a rice MAGIC Plus population detects QTLs and genes useful for biofortification by Descalsota, Gwen Iris L., Swamy, B.P. Mallikarjuna, Zaw, Hein, Inabangan-Asilo, Mary Ann, Amparado, Amery, Mauleon, Ramil, Chadha-Mohanty, Prabhjit, Arocena, Emily C., Raghavan, Chitra, Leung, Hei, Hernandez, Jose E., Lalusin, Antonio B., Mendioro, Merlyn S., Diaz, Ma. Genaleen Q., Reinke, Russell

Subjects: “…chromosome mapping…”
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Mapping brucellosis risk in Kenya and its implications for control strategies in sub-Saharan Africa by Akoko, James M., Mwatondo, Athman, Muturi, Mathew, Wambua, Lillian, Abkallo, Hussein M., Nyamota, Richard, Bosire, Caroline, Oloo, Stephen, Limbaso, K.S., Gakuya, F., Nthiwa, D., Bartlow, A., Middlebrook, E., Fair, J., Ogutu, J.O., Gachohi, J., Njenga, K., Bett, Bernard K.

“…Therefore, we conducted a study to establish the national prevalence and develop a risk map for Brucella spp. in cattle to contribute to plans to eliminate the disease in Kenya by the year 2040. …”
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Mapping novel yellow and leaf rust loci and predicting resistance in cross derived Canadian durum wheat by Menor de Gaspar, Juan, Domínguez Rondón, Alejandro, García-Abadillo, Juan, Knox, Ron, Bokore, Firdissa, Boyle, Kerry, Ammar, Karim, Huerta-Espino, Julio, Berraies, Samia, Meyer, Brad, Zhang, Wentao, Cuthbert, Richard, Fobert, Pierre, Ruan, Yuefeng, Isidro y Sánchez, Julio

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Modeling multiple phenotypes in wheat using data-driven genomic exploratory factor analysis and Bayesian network learning by Momen, Mehdi, Bhatta, Madhav, Hussain, Waseem, Yu, Haipeng, Morota, Gota

“…The objectives of this study were to illustrate the manner in which data‐driven exploratory factor analysis can map observed phenotypes into a smaller number of latent variables and infer a genomic latent factor network using 45 agro‐morphological, disease, and grain mineral phenotypes measured in synthetic hexaploid wheat lines (Triticum aestivum L.). …”
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Where to Invest Project Efforts for Greater Benefit: A Framework for Management Performance Mapping with Examples for Potato Seed Health by Buddenhagen, C., Xing, Y., Andrade-Piedra, J.L., Forbes, G., Kromann, P., Navarrete, I., Thomas-Sharma, Sara, Choudhury, R.A., Andersen, K.F., Schulte-Geldermann, E., Etherton, B.A., Plex Sulá, A.I., Garrett, K.A.

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Mapping the risk of Rift Valley fever in Uganda using national seroprevalence data from cattle, sheep and goats by Tumusiime, Dan, Isingoma, E., Tashoroora, O.B., Ndumu, D.B., Bahati, M., Nantima, N., Mugizi, Denis, Jost, C., Bett, Bernard K.

“…Serum samples collected were screened at the National Animal Disease Diagnostics and Epidemiology Centre (NADDEC) using a competition multispecies anti-RVF IgG ELISA kit. …”
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Spatial analysis and risk mapping of Crimean-Congo hemorrhagic fever (CCHF) in sub-Saharan Africa by Ilboudo, Abdoul K., Oloo, Stephen O., Sircely, Jason, Nijhof, A.M., Bett, Bernard K.

“…The geographical distribution of the disease and factors that influence its occurrence are poorly known. …”
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Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa by Redding, D., Tiedt, S., Lo Iacono, G., Bett, Bernard K., Jones, K.

“…Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). …”
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Camel Streptococcus agalactiae populations are associated with specific disease complexes and acquired the tetracycline resistance gene tetM via a Tn916-like element by Fischer, A., Liljander, Anne M., Kaspar, H., Muriuki, C., Fuxelius, H.H., Bongcam-Rudloff, E., Villiers, Etienne P. de, Huber, C.A., Frey, J., Daubenberger, C.A., Bishop, Richard P., Younan, M., Jores, Joerg

“…Camel GBS sequence types (STs) were distinct from other STs reported so far. We mapped specific STs and capsular types to major disease complexes caused by GBS. …”
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Spatiotemporal analysis of historical records (2001–2012) on dengue fever in Vietnam and development of a statistical model for forecasting risk by Bett, Bernard K., Grace, Delia, Hu Suk Lee, Lindahl, Johanna F., Hung Nguyen-Viet, Phuc Pham-Duc, Nguyen Huu Quyen, Tran Anh Tu, Tran Dac Phu, Dang Quang Tan, Vu Sinh Nam

“…We analyzed surveillance records from health centers in Vietnam collected between 2001–2012 to determine seasonal trends, develop risk maps and an incidence forecasting model. Methods The data were analyzed using a hierarchical spatial Bayesian model that approximates its posterior parameter distributions using the integrated Laplace approximation algorithm (INLA). …”
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Diversidad genómica y mapeo por asociación para la resistencia a la podredumbre húmeda del capítulo causada por Sclerotinia sclerotiorum en girasol by Filippi, Carla Valeria

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Spatial and temporal distribution of Taenia solium and its risk factors in Uganda by Ngwili, Nicholas, Sentamu, Derrick N., Korir, M., Adriko, M., Beinamaryo, P., Dione, Michel M., Kaducu, J.M., Mubangizi, A., Mwinzi, P.N., Thomas, Lian F., Dixon, M.A.

“…Background The lack of sub-national mapping of the zoonotic cestode Taenia solium in endemic countries presents a major challenge to achieving intensified T. solium control milestones, as outlined in the “World Health Organization neglected tropical disease roadmap by 2030”. …”
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