Results 201 to 210 of about 1,369,061 (328)
Single nucleotide polymorphisms in the CDH18 gene affect growth traits in Hu sheep
Abstract Growth traits are critical economic traits in sheep. Genetic polymorphism has a great influence on the improvement of sheep traits. The aim of this study was to analyze the effect of cadherin 18 (CDH18) gene polymorphisms on growth traits in Hu sheep.
Tianyi Liu+5 more
wiley +1 more source
Optogenetic control of transgene expression in Marchantia polymorpha
Abstract Premise The model liverwort Marchantia polymorpha is an emerging testbed species for plant metabolic engineering but lacks well‐characterized inducible promoters, which are necessary to minimize biochemical and physiological disruption when over‐accumulating target products.
Anya Lillemor Lindström Battle+1 more
wiley +1 more source
Creating the CIPRES Science Gateway for inference of large phylogenetic trees
Mark A. Miller+2 more
semanticscholar +1 more source
Analysis of plant metabolomics data using identification‐free approaches
Abstract Plant metabolomes are structurally diverse. One of the most popular techniques for sampling this diversity is liquid chromatography–mass spectrometry (LC‐MS), which typically detects thousands of peaks from single organ extracts, many representing true metabolites.
Xinyu Yuan+2 more
wiley +1 more source
Improved maximum growth rate prediction from microbial genomes by integrating phylogenetic information. [PDF]
Xu L, Zakem E, Weissman JL.
europepmc +1 more source
A new spin on chemotaxonomy: Using non‐proteogenic amino acids as a test case
Abstract Premise Specialized metabolites serve various roles for plants and humans. Unlike core metabolites, specialized metabolites are restricted to certain plant lineages; thus, in addition to their ecological functions, specialized metabolites can serve as diagnostic markers of plant lineages.
Makenzie Gibson+4 more
wiley +1 more source
High Genetic Diversity of Histoplasma in the Amazon Basin, 2006-2017. [PDF]
Ly T+16 more
europepmc +1 more source
Abstract Premise Recently, plant science has seen transformative advances in scalable data collection for sequence and chemical data. These large datasets, combined with machine learning, have demonstrated that conducting plant metabolic research on large scales yields remarkable insights.
Rachel Knapp+2 more
wiley +1 more source