Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Eva Nittinger"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract How many near-neighbors does a molecule have? This fundamental question in chemistry is crucial for molecular optimization problems under the similarity principle assumption. Generative models can sample molecules from a vast chemical space
Externí odkaz:
https://doaj.org/article/33626a8e13b440e18e005f3c5b5ffc4c
Autor:
Jiazhen He, Alessandro Tibo, Jon Paul Janet, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-15 (2024)
Abstract Designing compounds with a range of desirable properties is a fundamental challenge in drug discovery. In pre-clinical early drug discovery, novel compounds are often designed based on an already existing promising starting compound through
Externí odkaz:
https://doaj.org/article/e73ae601958648b29407a92e9414254a
Autor:
Yumeng Zhang, Janosch Menke, Jiazhen He, Eva Nittinger, Christian Tyrchan, Oliver Koch, Hongtao Zhao
Publikováno v:
Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-12 (2023)
Abstract Siamese networks, representing a novel class of neural networks, consist of two identical subnetworks sharing weights but receiving different inputs. Here we present a similarity-based pairing method for generating compound pairs to train Si
Externí odkaz:
https://doaj.org/article/10381a29e0844082b6416bac76c4e32a
Autor:
Andrea Volkamer, Sereina Riniker, Eva Nittinger, Jessica Lanini, Francesca Grisoni, Emma Evertsson, Raquel Rodríguez-Pérez, Nadine Schneider
Publikováno v:
Artificial Intelligence in the Life Sciences, Vol 3, Iss , Pp 100056- (2023)
Academic and pharmaceutical industry research are both key for progresses in the field of molecular machine learning. Despite common open research questions and long-term goals, the nature and scope of investigations typically differ between academia
Externí odkaz:
https://doaj.org/article/3dbd74aebfed4c2c90bcf7e32a3f8e64
Autor:
Charles Tapley Hoyt, Barbara Zdrazil, Rajarshi Guha, Nina Jeliazkova, Karina Martinez-Mayorga, Eva Nittinger
Publikováno v:
Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-3 (2023)
Externí odkaz:
https://doaj.org/article/fcfad7aacfdf4aebb8312bcd9b732b50
Publikováno v:
Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-3 (2023)
Externí odkaz:
https://doaj.org/article/5390a48e23d04683a80938ce90f0b9f7
Autor:
Karolina Kwapien, Eva Nittinger, Jiazhen He, Christian Margreitter, Alexey Voronov, Christian Tyrchan
Publikováno v:
ACS Omega, Vol 7, Iss 30, Pp 26573-26581 (2022)
Externí odkaz:
https://doaj.org/article/4b37582a47ca4c40be452cd25aae695e
Autor:
Jiazhen He, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum, Ola Engkvist
Publikováno v:
Journal of Cheminformatics, Vol 14, Iss 1, Pp 1-14 (2022)
Abstract Molecular optimization aims to improve the drug profile of a starting molecule. It is a fundamental problem in drug discovery but challenging due to (i) the requirement of simultaneous optimization of multiple properties and (ii) the large c
Externí odkaz:
https://doaj.org/article/305c5561153a4e0a8b809bbb8268b7d8
Autor:
Jeff Guo, Jon Paul Janet, Matthias R. Bauer, Eva Nittinger, Kathryn A. Giblin, Kostas Papadopoulos, Alexey Voronov, Atanas Patronov, Ola Engkvist, Christian Margreitter
Publikováno v:
Journal of Cheminformatics, Vol 13, Iss 1, Pp 1-21 (2021)
Abstract Recently, we have released the de novo design platform REINVENT in version 2.0. This improved and extended iteration supports far more features and scoring function components, which allows bespoke and tailor-made protocols to maximize impac
Externí odkaz:
https://doaj.org/article/52346401511c411199adbbd42216b9e7
Autor:
Daniel Fernández-Llaneza, Silas Ulander, Dea Gogishvili, Eva Nittinger, Hongtao Zhao, Christian Tyrchan
Publikováno v:
ACS Omega, Vol 6, Iss 16, Pp 11086-11094 (2021)
Externí odkaz:
https://doaj.org/article/841c43e6fedb4fcd8e4012c94e727858