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Filtering by: Creator Mochizuki%2C Masashi Remove constraint Creator: Mochizuki%2C Masashi Rights Statement In Copyright Remove constraint Rights Statement: In Copyright

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Understanding Circadian and Light-activated Transcriptional Regulatory Changes During Aging in Drosophila melanogaster

Creator:

Fey, Rosalyn M.

Abstract:

Systems biology is a powerful approach which considers and sheds light on all of the puzzle pieces which make up complex biological processes, and is an effective alternative to unraveling these processes using traditional molecular approaches alone. It is a natural companion approach for computational biology, which leverages the power...

Resource Type:

Dissertation
Application of modern NMR techniques to structure elucidation of bioactive natural products from tunicates

Creator:

Sikorska, Justyna

Abstract:

Recent developments in NMR hardware have extended the reach of natural products chemists to structure elucidation of compounds isolated on a nanomolar scale. In parallel with advances in hardware new NMR techniques for structure elucidation have evolved, e.g. quantitative NOEs, residual dipolar couplings (RDCs)and diffusion-ordered spectroscopy (DOSY). The application of...

Resource Type:

Dissertation

Full Text:

sp. containing agesamides A and B. Reproduced with permission from Masashi Tsuda et al, Org. Lett
Determination of magnetoelastic parameters in magnetic thin films from FMR spectra

Creator:

Masood, Khalid I.

Abstract:

The ferromagnetic resonance (FMR) phenomenon serves as a sensitive probe of the effective internal fields in a magnetic material. FMR spectroscopy has consequently become a well-established technique, extensively employed in assessing material properties such as magnetic anisotropy, Landé g-factor, damping parameter, and the magnetoelastic constants of magnetic materials. Determining these...

Resource Type:

Dissertation
Learning with Partial Supervision for Clustering and Classification

Creator:

Pei, Yuanli

Abstract:

In the field of machine learning, clustering and classification are two fundamental tasks. Traditionally, clustering is an unsupervised method, where no supervision about the data is available for learning; classification is a supervised task, where fully-labeled data are collected for training a classifier. In some scenarios, however, we may not...

Resource Type:

Dissertation

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Academic Affiliation

Electrical Engineering and Computer Science2
Biochemistry and Biophysics1
College of Pharmacy1

Advisor

Fern, Xiaoli1
Hendrix, David A.1
Jander, Albrecht1
Mcphail, Kerry L.1

Commencement Year

Commencement Year range begin – Commencement Year range end

Current results range from 2013 to 2024

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Committee Member

Raich, Raviv2
Coop, Leonard B.1
Dhagat, Pallavi1
Ishmael, Jane E.1
Maier, Claudia S.1
more Committee Members »

Creator

Fey, Rosalyn M.1
Masood, Khalid I.1
Pei, Yuanli1
Sikorska, Justyna1

Date

Date range begin – Date range end

Current results range from 2012 to 2024

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Decade

2020-20292
2010-20192

Degree Field

Biochemistry and Biophysics1
Computer Science1
Electrical and Computer Engineering1
Pharmacy1

Degree Level

Doctoral4

Degree Name

Doctor of Philosophy (Ph.D.)4

Language

English [eng]4

License

All rights reserved4

Non-Academic Affiliation

Oregon State University. Graduate School2

Peer Reviewed

No4

Resource Type

Dissertation4

Rights Statement

In Copyright[remove]4

Subject

Hydrolases1
Natural products -- Structure1
Nuclear magnetic resonance1
Tunicata -- South Africa1

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