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Full-Text Articles in Genetics and Genomics
Comparative Population Genomics And Speciation Of Snakes Across The North American Deserts, Edward A. Myers
Comparative Population Genomics And Speciation Of Snakes Across The North American Deserts, Edward A. Myers
Dissertations, Theses, and Capstone Projects
Understanding the process of speciation is of central interest to evolutionary biologists. Speciation can be studied using a phylogeographic approach, by identifying regions that promote lineage divergence, addressing whether speciation has occurred with gene flow, and when extended to multiple taxa, addressing if the same patterns of speciation are shared across codistributed groups with different ecologies. Here I examine the comparative phylogeographic histories and population genomics of thirteen snake taxa that are widely distributed and co-occur across the arid southwest of North America. I first quantify the degree to which these species groups have a shared history of population divergence …
Machine Learning Meta-Analysis Of Large Metagenomic Datasets: Tools And Biological Insight, Edoardo Pasolli, Duy Tin Truong, Faizan Malik, Levi Waldron, Nicola Segata
Machine Learning Meta-Analysis Of Large Metagenomic Datasets: Tools And Biological Insight, Edoardo Pasolli, Duy Tin Truong, Faizan Malik, Levi Waldron, Nicola Segata
Publications and Research
Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction …