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Michael Miller
Researcher at Donald Danforth Plant Science Center
Publications - 5
Citations - 614
Michael Miller is an academic researcher from Donald Danforth Plant Science Center. The author has contributed to research in topics: Image processing & Endosperm. The author has an hindex of 4, co-authored 5 publications receiving 510 citations. Previous affiliations of Michael Miller include University of Nebraska–Lincoln.
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Journal ArticleDOI
The relation between baseline HIV drug resistance and response to antiretroviral therapy: re-analysis of retrospective and prospective studies using a standardized data analysis plan
Victor DeGruttola,Lynn Dix,Richard T. D'Aquila,Dan Holder,Andrew N. Phillips,Mounir Ait-Khaled,John D. Baxter,P. Clevenbergh,Scott M. Hammer,Richard Harrigan,David Katzenstein,Randall Lanier,Michael Miller,Michael F. Para,Sabine Yerly,Andrew R. Zolopa,Jeffrey Murray,Amy Patick,Veronica Miller,Steven Castillo,Louise Pedneault,John W. Mellors +21 more
TL;DR: Re-analysed studies confirmed the importance of both genotypic and phenotypic drug resistance as predictors of virological failure, whether these factors were analysed separately or adjusted for other baseline confounding factors.
Journal ArticleDOI
PlantCV v2: Image analysis software for high-throughput plant phenotyping
Malia A. Gehan,Noah Fahlgren,Arash Abbasi,Jeffrey C. Berry,Steven T. Callen,Steven T. Callen,Leonardo Chavez,Andrew N. Doust,Max J. Feldman,Kerrigan B. Gilbert,John G. Hodge,J. Steen Hoyer,J. Steen Hoyer,Andy Lin,Suxing Liu,Suxing Liu,Cesar Lizarraga,Argelia Lorence,Michael Miller,Michael Miller,Eric Platon,Monica Tessman,Monica Tessman,Tony Sax +23 more
TL;DR: New functionality in the second major release of PlantCV includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.
Journal ArticleDOI
Raspberry Pi–powered imaging for plant phenotyping
Jose Carlos Tovar,John Steen Hoyer,John Steen Hoyer,Andy Lin,Allison Tielking,Steven T. Callen,S. Elizabeth Castillo,Michael Miller,Monica Tessman,Noah Fahlgren,James C. Carrington,Dmitri A. Nusinow,Malia A. Gehan +12 more
TL;DR: This protocol describes three low‐cost platforms for image acquisition that are useful for quantifying plant diversity and when coupled with open‐source image processing tools, these imaging platforms provide viable low‐ cost solutions for incorporating high‐throughput phenomics into a wide range of research programs.
Journal ArticleDOI
MADS78 and MADS79 Are Essential Regulators of Early Seed Development in Rice
Puneet Paul,Balpreet K. Dhatt,Michael Miller,Jing J. Folsom,Zhen Wang,Inga Krassovskaya,Kan Liu,Jaspreet Sandhu,Huihui Yu,Chi Zhang,Toshihiro Obata,Paul E. Staswick,Harkamal Walia +12 more
TL;DR: It is shown that MADS78 and MADS79 are essential regulators of early seed developmental transition and impact both seed size and quality in rice.
Posted ContentDOI
Raspberry Pi Powered Imaging for Plant Phenotyping
Jose Carlos Tovar,John Steen Hoyer,Andy Lin,Allison Tielking,Steven T. Callen,S. Elizabeth Castillo,Michael Miller,Monica Tessman,Noah Fahlgren,James C. Carrington,Dmitri A. Nusinow,Malia A. Gehan +11 more
TL;DR: Three low-cost platforms for image acquisition that are useful for quantifying plant diversity are described, and when coupled with open-source image processing tools, these imaging platforms provide viable low- cost solutions for incorporating high-throughput phenomics into a wide range of research programs.