Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Deanna L Auberry"'
Autor:
Owen P Leiser, Deanna L Auberry, Erica Bakker, Will Chrisler, Kristin Engbrecht, Heather Engelmann, Sarah Fansler, Vincent Gerbasi, Joshua Hansen, Chelsea Hutchinson, Janine Hutchison, Mary J Lancaster, Kathleen Lawrence, Angela Melville, Jennifer Mobberley, Isabelle O'Bryon, Kristie L Oxford, Tessa Oxford, Shelby Phillips, Kabrena E Rodda, James A Sanford, Athena Schepmoes, Brian E Staley, Kelcey Terrell, Kristin Victry, Cynthia Warner, Kristin M Omberg
Publikováno v:
PLoS ONE, Vol 18, Iss 4, p e0285042 (2023)
In 2020, the Department of Energy established the National Virtual Biotechnology Laboratory (NVBL) to address key challenges associated with COVID-19. As part of that effort, Pacific Northwest National Laboratory (PNNL) established a capability to co
Externí odkaz:
https://doaj.org/article/e0ec10df0e7b47ff951c40ec9c20b47b
Publikováno v:
Catalysis Today. 302:80-86
A new process for direct conversion of either levulinic acid (LA) or γ-valerolactone (GVL) to hydrocarbon fuel precursors was studied. The process involves passing an aqueous solution of LA or GVL containing a reducing agent, such as ethylene glycol
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d4cf77791b351d972e43a8ddc2f335b3
https://doi.org/10.1016/j.cattod.2017.06.021
https://doi.org/10.1016/j.cattod.2017.06.021
Autor:
Samuel O. Purvine, Karen W. Davenport, Migun Shakya, Bin Hu, T. B. K. Reddy, Mark I. Borkum, Yaxing Wei, Deanna L. Auberry, Kayd Miller, Lee Ann McCue, Jagadish Chandrabose Sundaramurthi, Stanton L. Martin, Nigel J Mouncey, Kjiersten Fagnan, Meghan M Drake, Shane Canon, Marcel Huntemann, Emiley A. Eloe-Fadrosh, Bruce E. Wilson, Yuri E. Corilo, Pajau Vangay, Chien-Chi Lo, Po-E Li, Hannah Blanco, Anubhav, Patrick S. G. Chain, Mark C. Flynn, Ranjeet Devarakonda, David Millard, Elisha M. Wood-Charlson, Mary S. Lipton, Mary Maxon, Paul D. Piehowski, Christopher J. Mungall, William D. Duncan, David Hays, Shweta Deshpande
Publikováno v:
Nature reviews. Microbiology, vol 18, iss 6
To harness the potential of microbiome science across the broad range of relevant disciplines, new approaches to data infrastructure and transdisciplinary collaboration are necessary. The National Microbiome Data Collaborative (NMDC) is a new initiat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39810a165710bd6aa772758ce1d56b22
https://doi.org/10.1038/s41579-020-0377-0
https://doi.org/10.1038/s41579-020-0377-0
Publikováno v:
PROTEOMICS. 5:123-131
Shedding (i.e., proteolysis of ectodomains of membrane proteins) plays an important pathophysiological role. In order to study the feasibility of identifying shed proteins, we analyzed serum-free media of human mammary epithelial cells by mass spectr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6e71b47cdb82c1c7bac24c34440a46e
https://doi.org/10.1002/pmic.200400912
https://doi.org/10.1002/pmic.200400912
Autor:
Harold R. Udseth, John R. Battista, Mary S. Lipton, Kwong Kwok Wong, Richard D. Smith, Amudhan Venkateswaran, Lye Meng Markillie, Deanna L. Auberry, Michael J. Daly, Rui Zhao, Heather M. Kostandarithes, Ronald J. Moore, James K. Fredrickson, Ljiljana Paša-Tolić, Eric Stritmatter, Yufeng Shen, Kim K. Hixson, Gordon A. Anderson, Christophe Masselon, David J. Anderson, Nikola Tolić, Margaret F. Romine
Publikováno v:
Proceedings of the National Academy of Sciences. 99:11049-11054
Understanding biological systems and the roles of their constituents is facilitated by the ability to make quantitative, sensitive, and comprehensive measurements of how their proteome changes, e.g., in response to environmental perturbations. To thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d95885664b004d61b07e8b125a5305c
https://doi.org/10.1073/pnas.172170199
https://doi.org/10.1073/pnas.172170199
Autor:
Jason M. Gilmore, Brian S. Hooker, Kelly Domico, Mudita Singhal, Ronald C. Taylor, Kenneth J. Auberry, H. Steven Wiley, Deanna L. Auberry, William R. Cannon, Denise D. Schmoyer, Don S. Daly, Greg Hurst, W. Hayes McDonald, Jason E. McDermott, Dale A. Pelletier, Amanda M. White
Publikováno v:
ResearcherID
We present a platform for the reconstruction of protein-protein interaction networks inferred from Mass Spectrometry (MS) bait-prey data. The Software Environment for Biological Network Inference (SEBINI), an environment for the deployment of network
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9b59f74ac294151cee23c38c81ade12
https://pubmed.ncbi.nlm.nih.gov/20052905
https://pubmed.ncbi.nlm.nih.gov/20052905
Autor:
Linda J. Foote, Denise D. Schmoyer, W. Judson Hervey, Elizabeth T. Owens, Brian S. Hooker, Yisong Wang, H. Steven Wiley, Don S. Daly, Gregory B. Hurst, Tse-Yuan Lu, Catherine K. McKeown, W. Hayes McDonald, William R. Cannon, Patricia K. Lankford, Jennifer L. Morrell-Falvey, Michelle V. Buchanan, Dale A. Pelletier, Mitchel J. Doktycz, Frank Larimer, Stephen J. Kennel, Jason M. Gilmore, Manesh B Shah, Deanna L. Auberry
Publikováno v:
Journal of proteome research. 7(8)
One of the most promising methods for large-scale studies of protein interactions is isolation of an affinity-tagged protein with its in vivo interaction partners, followed by mass spectrometric identification of the copurified proteins. Previous stu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5adca77a72dee3b31ab2a4f8ee3df0f
https://pubmed.ncbi.nlm.nih.gov/18590317
https://pubmed.ncbi.nlm.nih.gov/18590317
Autor:
Julia L. Sharp, Don S. Daly, Deanna L. Auberry, Amanda M. White, Jason M. Gilmore, Kevin K. Anderson
Publikováno v:
Bioinformatics (Oxford, England). 24(13)
Summary: The Bayesian Estimator of Protein–Protein Association Probabilities (BEPro aff3) is a software tool for estimating probabilities of protein–protein association between bait and prey protein pairs using data from multiple-bait, multiple-r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b5e1193169fd45f3f2cbf6c6b1db229
https://pubmed.ncbi.nlm.nih.gov/18499697
https://pubmed.ncbi.nlm.nih.gov/18499697
Autor:
Greg Hurst, William R. Cannon, Amanda M. White, Kelly Domico, Denise D. Schmoyer, W.H. McDonald, Brian S. Hooker, Kenneth J. Auberry, Mudita Singhal, Don S. Daly, Dale A. Pelletier, Deanna L. Auberry, Ronald C. Taylor, Jason E. McDermott
Publikováno v:
ICMLA
The Software Environment for Biological Network Inference (SEBINI) has been created to provide an interactive environment for the deployment and testing of network inference algorithms that use high-throughput expression data. Networks inferred from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7d1074859c6ad017b9aa6abb88656b3
https://doi.org/10.1109/icmla.2007.92
https://doi.org/10.1109/icmla.2007.92
Autor:
Ronald C. Taylor, Jason McDermott, W. Hayes McDonald, Dale Pelletier, Denise Schmoyer, William R. Cannon, Mudita Singhal, Don S. Daly, Kelly Domico, Amanda M. White, Deanna L. Auberry, Kenneth J. Auberry, Brian Hooker, Greg Hurst
Publikováno v:
ICMLA
We study agents situated in partially observable environments, who do not have sufficient resources to create conformant plans. Instead, they generate plans which are conditional and partial, execute or simulate them, and learn to evaluate their qual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3fefd0524d036083da545051831f78a9
https://doi.org/10.1109/icmla.2007.63
https://doi.org/10.1109/icmla.2007.63