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Full-Text Articles in Life Sciences
Improved Computational Prediction Of Function And Structural Representation Of Self-Cleaving Ribozymes With Enhanced Parameter Selection And Library Design, James D. Beck
Boise State University Theses and Dissertations
Biomolecules could be engineered to solve many societal challenges, including disease diagnosis and treatment, environmental sustainability, and food security. However, our limited understanding of how mutational variants alter molecular structures and functional performance has constrained the potential of important technological advances, such as high-throughput sequencing and gene editing. Ribonuleic Acid (RNA) sequences are thought to play a central role within many of these challenges. Their continual discovery throughout all domains of life is evidence of their significant biological importance (Weinreb et al., 2016). The self-cleaving ribozyme is a class of noncoding Ribonuleic Acid (ncRNA) that has been useful for …
Integrating National Ecological Observatory Network (Neon) Airborne Remote Sensing And In-Situ Data For Optimal Tree Species Classification, Victoria M. Scholl, Megan E. Cattau, Maxwell B. Joseph, Jennifer K. Balch
Integrating National Ecological Observatory Network (Neon) Airborne Remote Sensing And In-Situ Data For Optimal Tree Species Classification, Victoria M. Scholl, Megan E. Cattau, Maxwell B. Joseph, Jennifer K. Balch
Human-Environment Systems Research Center Faculty Publications and Presentations
Accurately mapping tree species composition and diversity is a critical step towards spatially explicit and species-specific ecological understanding. The National Ecological Observatory Network (NEON) is a valuable source of open ecological data across the United States. Freely available NEON data include in-situ measurements of individual trees, including stem locations, species, and crown diameter, along with the NEON Airborne Observation Platform (AOP) airborne remote sensing imagery, including hyperspectral, multispectral, and light detection and ranging (LiDAR) data products. An important aspect of predicting species using remote sensing data is creating high-quality training sets for optimal classification purposes. Ultimately, manually creating training data …