Shotgun metagenomics has become a pivotal technology in microbiome research, enabling in-depth analysis of microbial communities at both the high-resolution taxonomic and functional levels. This approach provides valuable insights of microbial diversity, interactions, and their roles in health and disease. However, the complexity of data processing and the need for reproducibility pose significant challenges to researchers.
View Article and Find Full Text PDFThe rapid growth of microbiome research has generated an unprecedented amount of multi-omics data, presenting challenges in data analysis and visualization. To address these issues, we present MicrobiomeStatPlots, a comprehensive platform offering streamlined, reproducible tools for microbiome data analysis and visualization. This platform integrates essential bioinformatics workflows with multi-omics pipelines and provides 82 distinct visualization cases for interpreting microbiome datasets.
View Article and Find Full Text PDFThe Conference 2024 provides a platform to promote the development of an innovative scientific research ecosystem for microbiome and One Health. The four key components - Technology, Research (Biology), Academic journals, and Social media - form a synergistic ecosystem. Advanced technologies drive biological research, which generates novel insights that are disseminated through academic journals.
View Article and Find Full Text PDFBackground: Ectoparasites of rodents play significant roles in disease transmission to humans. Conventional poisoning potentially reduces the population densities of rodents, however, they may increase the ectoparasite loads on the surviving hosts. EP-1 has been shown to have anti-fertility effects on many rodent species, while ivermectin is effective in controlling ectoparasites.
View Article and Find Full Text PDFReplicated multiple scale species distribution models (SDMs) have become increasingly important to identify the correct variables determining species distribution and their influences on ecological responses. This study explores multi-scale habitat relationships of the snow leopard () in two study areas on the Qinghai-Tibetan Plateau of western China. Our primary objectives were to evaluate the degree to which snow leopard habitat relationships, expressed by predictors, scales of response, and magnitude of effects, were consistent across study areas or locally landcape-specific.
View Article and Find Full Text PDFHabitat evaluation constitutes an important and fundamental step in the management of wildlife populations and conservation policy planning. Geographic information system (GIS) and species presence data provide the means by which such evaluation can be done. Maximum Entropy (MaxEnt) is widely used in habitat suitability modeling due to its power of accuracy and additional descriptive properties.
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