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Immaculate Tumwebaze

Researcher at University of Giessen

Publications -  6
Citations -  37

Immaculate Tumwebaze is an academic researcher from University of Giessen. The author has contributed to research in topics: Bulinus & Population. The author has an hindex of 3, co-authored 3 publications receiving 11 citations.

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Molecular identification of Bulinus spp. intermediate host snails of Schistosoma spp. in crater lakes of western Uganda with implications for the transmission of the Schistosoma haematobium group parasites.

TL;DR: This first detailed malacological study of the crater lakes systems in western Uganda revealed presence of Bulinus species that are either not known or not regionally known to be hosts for S. haematobium, the causing agent of human urogenital schistosomiasis.
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Cryptic intermediate snail host of the liver fluke Fasciola hepatica in Africa

TL;DR: A hitherto neglected distinct species, G. mweruensis, now appears a major host of F. hepatica throughout sub-Saharan Africa and is proposed to be a distinct species according to the phylogenetic analyses and genetic distance.
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Assessing the diversity and distribution of potential intermediate hosts snails for urogenital schistosomiasis: Bulinus spp. (Gastropoda: Planorbidae) of Lake Victoria.

TL;DR: DNA sequences from part of the cytochrome c oxidase subunit 1 (cox1) gene and the internal transcribed spacer 2 (ITS2) region were used to investigate Bulinus populations obtained from a longitudinal survey in Lake Victoria and neighbouring systems during 2010–2019 to determine specimen identities, diversity and phylogenetic positions.
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Evolution and Biogeography of Freshwater Snails of the Genus Bulinus (Gastropoda) in Afromontane Extreme Environments

TL;DR: Bayesian phylogenetic inference employing a fossil-calibrated molecular clock resulted in a strongly supported phylogeny resolving the relationships between the four Bulinus groups, and whether the Afromontane regions represent “sky islands”.
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Factors Controlling the Distribution of Intermediate Host Snails of Schistosoma in Crater Lakes in Uganda: A Machine Learning Approach

TL;DR: The study explores the applicability of a machine learning algorithm, random forest, to determine significant predictors of IH distribution and their variation across different geographic scales in crater lakes in western Uganda and demonstrates the importance of combining a comprehensive set of predictor variables.