Samuel E. Miller
University of Chicago
5 Papers
Samuel E. Miller is an academic researcher from University of Chicago. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 2, co-authored 2 publications.
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Papers
Community-led, integrated, reproducible multi-omics with anvi'o.
A. Murat Eren,Evan Kiefl,Alon Shaiber,Iva Veseli,Samuel E. Miller,Matthew S. Schechter,Isaac Fink,Jessica N. Pan,Mahmoud Yousef,Emily Fogarty,Florian Trigodet,Andrea R. Watson,Özcan C. Esen,Ryan M Moore,Quentin Clayssen,Michael D. Lee,Veronika Kivenson,Elaina D. Graham,Bryan D. Merrill,Antti Karkman,Daniel Blankenberg,Daniel Blankenberg,John M. Eppley,Andreas Sjödin,Jarrod J. Scott,Xabier Vázquez-Campos,Luke J. McKay,Elizabeth A. McDaniel,Sarah L. R. Stevens,Rika E. Anderson,Jessika Fuessel,Antonio Fernandez-Guerra,Lois Maignien,Lois Maignien,Tom O. Delmont,Amy D. Willis +35 more
TL;DR: The workflows designed to enable researchers to interpret data can constrain the biological questions that can be asked as discussed by the authors, but the workflows can also be difficult to adapt to real-world applications.
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Analysis of queuosine and 2-thio tRNA modifications by high throughput sequencing
TL;DR: A periodate-treatment method that enables single base resolution profiling of Q-modification in tRNAs by Nextgen sequencing from biological RNA samples is described and periodate oxidizes the Q-base, which results in specific deletion signatures in the RNA-seq data.
Metaproteomics reveals functional partitioning and vegetational variation among permafrost-affected Arctic soil bacterial communities
TL;DR: In this article , the authors studied in situ processes in Alaskan soils using original metaproteomic methods in order to relate important heterotrophic functions to microbial taxa and to understand the microbial response to Arctic greening.
Structure-informed microbial population genetics elucidate selective pressures that shape protein evolution
Evan Kiefl,Ozcan C Esen,Samuel E. Miller,Kourtney L. Kroll,Amy D. Willis,Michael S. Rappé,Tao Pan,A. Murat Eren +7 more
TL;DR: The utility of structure-informed metrics to understand the distribution of nonsynonymous polymorphism, establish insights into the impact of changing nutrient availability on protein evolution, and show that even synonymous variants are scrutinized strictly to maximize translational efficiency when selection is high are demonstrated.
Postnovo: Postprocessing Enables Accurate and FDR-Controlled de Novo Peptide Sequencing
TL;DR: A new open-source tool that postprocesses de novo sequence predictions to find high-accuracy results, Postnovo, which uses a predictive model to rescore and rerank candidate sequences in a manner akin to database search postprocessing tools such as Percolator.