Zobrazeno 1 - 10
of 631
pro vyhledávání: '"Dinh, Q"'
Autor:
Nicholas L. Bartelli, Victor J. Passanisi, Karolina Michalska, Kiho Song, Dinh Q. Nhan, Hongjun Zhou, Bonnie J. Cuthbert, Lucy M. Stols, William H. Eschenfeldt, Nicholas G. Wilson, Jesse S. Basra, Ricardo Cortes, Zainab Noorsher, Youssef Gabraiel, Isaac Poonen-Honig, Elizabeth C. Seacord, Celia W. Goulding, David A. Low, Andrzej Joachimiak, Frederick W. Dahlquist, Christopher S. Hayes
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-17 (2022)
Contact-dependent growth inhibition (CDI) is an important mechanism of bacterial competition. Here, Bartelli et al. show that proteolytic processing of a CDI toxin induces a conformational switch required for translocation into target bacteria.
Externí odkaz:
https://doaj.org/article/86ac2e542326412c8e314121e49b5241
Publikováno v:
Research on Crops; Sep2024, Vol. 25 Issue 3, p363-368, 6p
Akademický článek
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Akademický článek
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Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Preference Network (PN) that jointly models various types of domain knowledge
Externí odkaz:
http://arxiv.org/abs/1407.5764
Autor:
Nicholas L. Bartelli, Victor J. Passanisi, Karolina Michalska, Kiho Song, Dinh Q. Nhan, Hongjun Zhou, Bonnie J. Cuthbert, Lucy M. Stols, William H. Eschenfeldt, Nicholas G. Wilson, Jesse S. Basra, Ricardo Cortes, Zainab Noorsher, Youssef Gabraiel, Isaac Poonen-Honig, Elizabeth C. Seacord, Celia W. Goulding, David A. Low, Andrzej Joachimiak, Frederick W. Dahlquist, Christopher S. Hayes
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-1 (2022)
Externí odkaz:
https://doaj.org/article/01fc3aaf029c427cba9b0bc69da67bf3
Hierarchical beta process has found interesting applications in recent years. In this paper we present a modified hierarchical beta process prior with applications to hierarchical modeling of multiple data sources. The novel use of the prior over a h
Externí odkaz:
http://arxiv.org/abs/1210.4855
Collaborative filtering is an effective recommendation technique wherein the preference of an individual can potentially be predicted based on preferences of other members. Early algorithms often relied on the strong locality in the preference data,
Externí odkaz:
http://arxiv.org/abs/1205.2611
This paper proposes an algorithmic framework for solving parametric optimization problems which we call adjoint-based predictor-corrector sequential convex programming. After presenting the algorithm, we prove a contraction estimate that guarantees t
Externí odkaz:
http://arxiv.org/abs/1109.2800