Zobrazeno 1 - 10
of 198
pro vyhledávání: '"D.J. van Dijk"'
Autor:
Floris van der Flier, Dave Estell, Sina Pricelius, Lydia Dankmeyer, Sander van Stigt Thans, Harm Mulder, Rei Otsuka, Frits Goedegebuur, Laurens Lammerts, Diego Staphorst, Aalt D.J. van Dijk, Dick de Ridder, Henning Redestig
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 3489-3497 (2024)
Protein engineering increasingly relies on machine learning models to computationally pre-screen promising novel candidates. Although machine learning approaches have proven effective, their performance on prospective screening data leaves room for i
Externí odkaz:
https://doaj.org/article/88f0342ceb3642ada11fbbe3b130864d
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 630-643 (2023)
Recent breakthroughs in protein structure prediction demarcate the start of a new era in structural bioinformatics. Combined with various advances in experimental structure determination and the uninterrupted pace at which new structures are publishe
Externí odkaz:
https://doaj.org/article/4773121e190141b88c59ee46abe466a0
Publikováno v:
F1000Research, Vol 11 (2023)
Background: Many studies have demonstrated the utility of machine learning (ML) methods for genomic prediction (GP) of various plant traits, but a clear rationale for choosing ML over conventionally used, often simpler parametric methods, is still la
Externí odkaz:
https://doaj.org/article/9cc4f41fc90f41ff8807fc7add203afa
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 18, Iss , Pp 981-992 (2020)
The vast number of protein structures currently available opens exciting opportunities for machine learning on proteins, aimed at predicting and understanding functional properties. In particular, in combination with homology modelling, it is now pos
Externí odkaz:
https://doaj.org/article/9d5801ede6c74ba596617da056238853
Autor:
Yanxia Zhang, Yiyun Li, Thijs de Zeeuw, Kilian Duijts, Dorota Kawa, Jasper Lamers, Kristina S. Munzert, Hongfei Li, Yutao Zou, A. Jessica Meyer, Jinxuan Yan, Francel Verstappen, Yixuan Wang, Tom Gijsberts, Jielin Wang, Nora Gigli-Bisceglia, Timo Engelsdorf, Aalt D.J van Dijk, Christa Testerink
Salinity stress constrains lateral root (LR) growth and severely impacts plant growth. Auxin signaling is indispensable for the regulation of LR formation. Nevertheless, the molecular mechanism of how salinity affects root auxin signaling and whether
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2118befc4544d27855879148149faacc
https://doi.org/10.1101/2023.04.25.538210
https://doi.org/10.1101/2023.04.25.538210
Autor:
Dóra Szakonyi, Sofie Van Landeghem, Katja Baerenfaller, Lieven Baeyens, Jonas Blomme, Rubén Casanova-Sáez, Stefanie De Bodt, David Esteve-Bruna, Fabio Fiorani, Nathalie Gonzalez, Jesper Grønlund, Richard G.H. Immink, Sara Jover-Gil, Asuka Kuwabara, Tamara Muñoz-Nortes, Aalt D.J. van Dijk, David Wilson-Sánchez, Vicky Buchanan-Wollaston, Gerco C. Angenent, Yves Van de Peer, Dirk Inzé, José Luis Micol, Wilhelm Gruissem, Sean Walsh, Pierre Hilson
Publikováno v:
Current Plant Biology, Vol 2, Iss C, Pp 1-11 (2015)
The information that connects genotypes and phenotypes is essentially embedded in research articles written in natural language. To facilitate access to this knowledge, we constructed a framework for the curation of the scientific literature studying
Externí odkaz:
https://doaj.org/article/88c05d836f014f6cb55fda1dc527d00d
Autor:
Aalt D.J. van Dijk, Jaap Molenaar
Publikováno v:
PeerJ, Vol 5, p e3197 (2017)
The appropriate timing of flowering is crucial for the reproductive success of plants. Hence, intricate genetic networks integrate various environmental and endogenous cues such as temperature or hormonal statues. These signals integrate into a netwo
Externí odkaz:
https://doaj.org/article/a6a3b92a437f4177afa692adc260e56b
Autor:
Joachim W. Bargsten, Edouard I. Severing, Jan-Peter Nap, Gabino F. Sanchez-Perez, Aalt D.J. van Dijk
Publikováno v:
Current Plant Biology, Vol 1, Iss C, Pp 73-82 (2014)
Accurate annotation of protein function is key to understanding life at the molecular level, but automated annotation of functions is challenging. We here demonstrate the combination of a method for protein function annotation that uses network infor
Externí odkaz:
https://doaj.org/article/abf7a4f779fd4729ac669f9984a1b5c3
Many studies have demonstrated the utility of machine learning (ML) methods for genomic prediction (GP) of various plant traits, but a clear rationale for choosing ML over conventionally used, often simpler parametric methods is still lacking. Predic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b851a57387e1d2264e6d6b3e14a519ca
https://doi.org/10.21203/rs.3.rs-1315622/v1
https://doi.org/10.21203/rs.3.rs-1315622/v1