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Filtering by: Creator Matteson, Keith M. Resource Type Dissertation Rights Statement In Copyright - Non-Commercial Use Permitted

Restoring Ponderosa Pine: Understanding Individual Tree Defenses, Disturbance Responses, and Resilience

Creator:

Johnson, Christal

Abstract:

The aim of this research was to provide forest managers and researchers with a better understanding of individual tree defenses and tree responses to disturbances, within a Collaborative Forest Landscape Restoration Program area. Forest restoration often aims to increase stand-level resistance to uncharacteristic changes, and stand-level resistance begins with tree-level...

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Dissertation

Full Text:

, 903–912. Cailleret, M., Dakos, V., Jansen, S., Robert, E.M.R., Aakala, T., Amoroso, M.M., Antos, J.A
Computational Approaches for Understanding Combinatorial Gene Regulation

Creator:

Ansariola, Mitra

Abstract:

Gene regulation is a complex mechanism that controls the spatial and temporal expression of genes in a living cell. My dissertation studies focus on two problems. First, tissue-specific gene expression prediction from DNA sequence and chromatin state, and second, the accurate discovery of small over-represented regulatory circuits in gene regulatory...

Resource Type:

Dissertation
Machine Learning for Precision Medicine: Application to Cancer Chemotherapy Response Prediction and Wound Healing Status Assessment

Creator:

Wei, Qi

Abstract:

Ph.D. candidate Qi Wei's thesis consists of two projects: Chemotherapy Project: a study based on the research paper "Predicting chemotherapy response of various cancer types using a variational auto-encoder approach" submitted to the bioRxiv preprint archive and accepted by the BMC bioinformatics; and Wound Monitor Project: implementing and assessing analytics...

Resource Type:

Dissertation

Full Text:

latent variable dimen- sion h⌧ m (Sec. 2.3.2.2): a vector of means µ and a vector of stan- dard

ScholarsArchive@OSU

Restoring Ponderosa Pine: Understanding Individual Tree Defenses, Disturbance Responses, and Resilience

Computational Approaches for Understanding Combinatorial Gene Regulation

Machine Learning for Precision Medicine: Application to Cancer Chemotherapy Response Prediction and Wound Healing Status Assessment

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