Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Debby D. Wang"'
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-15 (2024)
Abstract The launch of AlphaFold series has brought deep-learning techniques into the molecular structural science. As another crucial problem, structure-based prediction of protein-ligand binding affinity urgently calls for advanced computational te
Externí odkaz:
https://doaj.org/article/9fc62943238b4e8ab19ee2bf67af39de
Autor:
Debby D. Wang, Moon-Tong Chan
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 1088-1096 (2022)
As a key element in structure-based drug design, binding affinity prediction (BAP) for putative protein-ligand complexes can be efficiently achieved by the incorporation of structural descriptors and machine-learning models. However, developing conci
Externí odkaz:
https://doaj.org/article/8e56df6a5fa8406dbdd247deb9488122
Publikováno v:
BMC Molecular and Cell Biology, Vol 22, Iss 1, Pp 1-13 (2021)
Abstract Background Epidermal growth factor receptor (EGFR) and its signaling pathways play a vital role in pathogenesis of lung cancer. By disturbing EGFR signaling, mutations of EGFR may lead to progression of cancer or the emergence of resistance
Externí odkaz:
https://doaj.org/article/72ff0c4962e545c9be5a7f5d28eacb98
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 19, Iss , Pp 6291-6300 (2021)
Binding affinity prediction (BAP) using protein–ligand complex structures is crucial to computer-aided drug design, but remains a challenging problem. To achieve efficient and accurate BAP, machine-learning scoring functions (SFs) based on a wide r
Externí odkaz:
https://doaj.org/article/0eb163c916dc4917b73286811f8c9bd6
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 18, Iss , Pp 439-454 (2020)
Purpose: Mutation-induced variation of protein-ligand binding affinity is the key to many genetic diseases and the emergence of drug resistance, and therefore predicting such mutation impacts is of great importance. In this work, we aim to predict th
Externí odkaz:
https://doaj.org/article/feb1483729f847f2bd78f6ddee4a5d54
Autor:
Sheryl Hui-Xian Ng, Nabilah Rahman, Ian Yi Han Ang, Srinath Sridharan, Sravan Ramachandran, Debby D. Wang, Chuen Seng Tan, Sue-Anne Toh, Xin Quan Tan
Publikováno v:
BMC Health Services Research, Vol 19, Iss 1, Pp 1-14 (2019)
Abstract Background High utilizers (HUs) are a small group of patients who impose a disproportionately high burden on the healthcare system due to their elevated resource use. Identification of persistent HUs is pertinent as interventions have not be
Externí odkaz:
https://doaj.org/article/5019f44be09948afa02709a00cf61ee2
Autor:
Nabilah Rahman, Sheryl Hui-Xian Ng, Sravan Ramachandran, Debby D. Wang, Srinath Sridharan, Chuen Seng Tan, Astrid Khoo, Xin Quan Tan
Publikováno v:
BMC Health Services Research, Vol 19, Iss 1, Pp 1-16 (2019)
Abstract Background As healthcare expenditure and utilization continue to rise, understanding key drivers of hospital expenditure and utilization is crucial in policy development and service planning. This study aims to investigate micro drivers of h
Externí odkaz:
https://doaj.org/article/1e17e4d8472d49aaa145761b6c179b2b
Publikováno v:
Scientific Reports, Vol 7, Iss 1, Pp 1-13 (2017)
Abstract Metastatic non-small-cell lung cancer (NSCLC) with activating EGFR mutations responds very well to first and second generation tyrosine-kinase inhibitors (TKI) including gefitinib, erlotinib and afatinib. Unfortunately, drug resistance will
Externí odkaz:
https://doaj.org/article/48baaceb101f44bbbb0e692bec36675e
Publikováno v:
IEEE Transactions on Emerging Topics in Computational Intelligence. 5:373-383
Prediction of protein–protein interaction sites plays an important role for understanding the protein interactions and functions. However, in the protein–protein interaction site prediction problem, the number of binding-site residues is usually
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2cfadfbb525ed2e468f2fd381102a5b
https://doi.org/10.1109/tetci.2019.2922340
https://doi.org/10.1109/tetci.2019.2922340
Publikováno v:
BMC Molecular and Cell Biology, Vol 22, Iss 1, Pp 1-13 (2021)
BMC Molecular and Cell Biology
BMC Molecular and Cell Biology
BackgroundEpidermal growth factor receptor (EGFR) and its signaling pathways play a vital role in pathogenesis of lung cancer. By disturbing EGFR signaling, mutations of EGFR may lead to progression of cancer or the emergence of resistance to EGFR-ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::200076283f76b06da3ae47d3936f0648
https://doaj.org/article/72ff0c4962e545c9be5a7f5d28eacb98
https://doaj.org/article/72ff0c4962e545c9be5a7f5d28eacb98