Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Nicholas Keone Lee"'
Autor:
Jacob Hepkema, Nicholas Keone Lee, Benjamin J. Stewart, Siwat Ruangroengkulrith, Varodom Charoensawan, Menna R. Clatworthy, Martin Hemberg
Publikováno v:
Genome Biology, Vol 24, Iss 1, Pp 1-22 (2023)
Abstract The binding of transcription factors at proximal promoters and distal enhancers is central to gene regulation. Identifying regulatory motifs and quantifying their impact on expression remains challenging. Using a convolutional neural network
Externí odkaz:
https://doaj.org/article/adb1c4ecc9f94a289b4b957c56315882
Publikováno v:
Genome Biology, Vol 24, Iss 1, Pp 1-14 (2023)
Abstract Deep neural networks (DNNs) hold promise for functional genomics prediction, but their generalization capability may be limited by the amount of available data. To address this, we propose EvoAug, a suite of evolution-inspired augmentations
Externí odkaz:
https://doaj.org/article/fdf641cadc6b46828d142ef24c8d0c0d
Publikováno v:
PLoS ONE, Vol 12, Iss 7, p e0180208 (2017)
The transition from prelife where self-replication does not occur, to life which exhibits self-replication and evolution, has been a subject of interest for many decades. Membranes, forming compartments, seem to be a critical component of this transi
Externí odkaz:
https://doaj.org/article/f2599bb4e5b1433983c351fad0986774
Deep neural networks (DNNs) hold promise for functional genomics prediction, but their generalization capability may be limited by the amount of available data. To address this, we propose EvoAug, a suite of evolution-inspired augmentations that enha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6617d8838d0889e6f2c26cb2ad61fe36
https://doi.org/10.1101/2022.11.03.515117
https://doi.org/10.1101/2022.11.03.515117
Autor:
Haishuai Wang, Hao Dai, Hien-haw Liow, Dong-Qing Wei, Huai-Meng Fan, Ching Chiek Koh, Nicholas Keone Lee, J.B. Brown, Luonan Chen, Li Li, Daniel Reker
Publikováno v:
Scientific Reports, Vol 9, Iss 1, Pp 1-12 (2019)
Scientific Reports
Scientific Reports
Identifying potential protein-ligand interactions is central to the field of drug discovery as it facilitates the identification of potential novel drug leads, contributes to advancement from hits to leads, predicts potential off-target explanations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09c8a4ee9d0ca593812ab78811817813
http://link.springer.com/article/10.1038/s41598-019-43125-6
http://link.springer.com/article/10.1038/s41598-019-43125-6
Publikováno v:
PLoS ONE
PLoS ONE, Vol 12, Iss 7, p e0180208 (2017)
PLoS ONE, Vol 12, Iss 7, p e0180208 (2017)
The transition from prelife where self-replication does not occur, to life which exhibits self-replication and evolution, has been a subject of interest for many decades. Membranes, forming compartments, seem to be a critical component of this transi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fedb444768ab8dbf3d11bc2b2821a3c8
https://pubmed.ncbi.nlm.nih.gov/28723913
https://pubmed.ncbi.nlm.nih.gov/28723913