Zobrazeno 1 - 10
of 849
pro vyhledávání: '"J., Ballester"'
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-17 (2024)
Abstract Poly ADP-ribose polymerase 1 (PARP1) is an attractive therapeutic target for cancer treatment. Machine-learning scoring functions constitute a promising approach to discovering novel PARP1 inhibitors. Cutting-edge PARP1-specific machine-lear
Externí odkaz:
https://doaj.org/article/a02fc69f5f844477a791bb844350e043
Publikováno v:
Health Data Science, Vol 4 (2024)
Background: Gemcitabine is a first-line chemotherapy for pancreatic adenocarcinoma (PAAD), but many PAAD patients do not respond to gemcitabine-containing treatments. Being able to predict such nonresponders would hence permit the undelayed administr
Externí odkaz:
https://doaj.org/article/d41587731ca34dd6b72ce2100512e5f5
Autor:
A. Lacima, H. Petetin, A. Soret, D. Bowdalo, O. Jorba, Z. Chen, R. F. Méndez Turrubiates, H. Achebak, J. Ballester, C. Pérez García-Pando
Publikováno v:
Geoscientific Model Development, Vol 16, Pp 2689-2718 (2023)
Over the last century, our societies have experienced a sharp increase in urban population and fossil-fuelled transportation, turning air pollution into a critical issue. It is therefore key to accurately characterize the spatiotemporal variability o
Externí odkaz:
https://doaj.org/article/057318958874452cb2fed27f382b86b1
Publikováno v:
Current Research in Structural Biology, Vol 4, Iss , Pp 206-210 (2022)
The interaction between PD1 and its ligand PDL1 has been shown to render tumor cells resistant to apoptosis and promote tumor progression. An innovative mechanism to inhibit the PD1/PDL1 interaction is PDL1 dimerization induced by small-molecule PDL1
Externí odkaz:
https://doaj.org/article/c2188ab0cefc4892bbc48d0f3e49eaf5
Autor:
Adeolu Z. Ogunleye, Chayanit Piyawajanusorn, Anthony Gonçalves, Ghita Ghislat, Pedro J. Ballester
Publikováno v:
Advanced Science, Vol 9, Iss 24, Pp n/a-n/a (2022)
Abstract Doxorubicin is a common treatment for breast cancer. However, not all patients respond to this drug, which sometimes causes life‐threatening side effects. Accurately anticipating doxorubicin‐resistant patients would therefore permit to s
Externí odkaz:
https://doaj.org/article/23bededaf5204aaf9bc65e9fb73c41aa
Publikováno v:
Biomolecules, Vol 13, Iss 3, p 498 (2023)
Machine learning-based models have been widely used in the early drug-design pipeline. To validate these models, cross-validation strategies have been employed, including those using clustering of molecules in terms of their chemical structures. Howe
Externí odkaz:
https://doaj.org/article/7d187048d9894295a87124325bb3e03a
Publikováno v:
Natural Hazards and Earth System Sciences, Vol 21, Pp 375-391 (2021)
Trends of extreme-temperature episodes in cities are increasing (in frequency, magnitude and duration) due to regional climate change in interaction with urban effects. Urban morphologies and thermal properties of the materials used to build them are
Externí odkaz:
https://doaj.org/article/39197fb3130c4dabb5dc5cc7519ee3a1
Autor:
Pedro J. Ballester, Javier Carmona
Publikováno v:
npj Precision Oncology, Vol 5, Iss 1, Pp 1-3 (2021)
Externí odkaz:
https://doaj.org/article/4ddc45445d914b4f83be2cf6a3232029
Autor:
A. Bataller Català, J. Ballester Roca
Publikováno v:
Red U, Vol 17, Iss 1, Pp 153-165 (2019)
We address the challenges of adult literacy in an American context from a European perspective. We focus on the context of adult education in Peru, a country with a great cultural and linguistic diversity, based on the interaction produced with a hun
Externí odkaz:
https://doaj.org/article/0070c1f585dd446ba97b43b3b6e67b02
Publikováno v:
Journal of Chemical Information and Modeling. 63:1401-1405
We discuss how data unbiasing and simple methods such as protein-ligand Interaction FingerPrint (IFP) can overestimate virtual screening performance. We also show that IFP is strongly outperformed by target-specific machine-learning scoring functions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::383cda50c410a76e234a368e6c857315
https://doi.org/10.1021/acs.jcim.3c00218
https://doi.org/10.1021/acs.jcim.3c00218