香蕉枯萎病(race 1 of Fusarium oxysp-orum f.cubense Snyder et Hansen),又称香蕉巴拿马病,在我国主要为害粉蕉类(糯米蕉)和过山香蕉(龙牙蕉)品种,极少为害香蕉和大蕉。该病属危险性病害,是国际植检对象之一。1960年此病仅在我国广西...香蕉枯萎病(race 1 of Fusarium oxysp-orum f.cubense Snyder et Hansen),又称香蕉巴拿马病,在我国主要为害粉蕉类(糯米蕉)和过山香蕉(龙牙蕉)品种,极少为害香蕉和大蕉。该病属危险性病害,是国际植检对象之一。1960年此病仅在我国广西南宁、邕宁、博白等地零星发生。1975—1977年扩展到海南文昌、海口、儋县。1983—1990年又在广东中山、花县、番禺等地陆续相继发生,发病面积逐年扩大,目前此病在花县和中山县蕉区已成为毁灭性病害,严重阻碍粉蕉和过山香蕉的生产和发展。1988年开始,我们在美籍台湾学者、世界著名植物病理学家。展开更多
Single-molecule force spectroscopy(SMFS)measurements of the dynamics of biomolecules typically require identifying massive events and states from large data sets,such as extracting rupture forces from force-extension ...Single-molecule force spectroscopy(SMFS)measurements of the dynamics of biomolecules typically require identifying massive events and states from large data sets,such as extracting rupture forces from force-extension curves(FECs)in pulling experiments and identifying states from extension-time trajectories(ETTs)in force-clamp experiments.The former is often accomplished manually and hence is time-consuming and laborious while the latter is always impeded by the presence of baseline drift.In this study,we attempt to accurately and automatically identify the events and states from SMFS experiments with a machine learning approach,which combines clustering and classification for event identification of SMFS(ACCESS).As demonstrated by analysis of a series of data sets,ACCESS can extract the rupture forces from FECs containing multiple unfolding steps and classify the rupture forces into the corresponding conformational transitions.Moreover,ACCESS successfully identifies the unfolded and folded states even though the ETTs display severe nonmonotonic baseline drift.Besides,ACCESS is straightforward in use as it requires only three easy-to-interpret parameters.As such,we anticipate that ACCESS will be a useful,easy-to-implement and high-performance tool for event and state identification across a range of single-molecule experiments.展开更多
文摘香蕉枯萎病(race 1 of Fusarium oxysp-orum f.cubense Snyder et Hansen),又称香蕉巴拿马病,在我国主要为害粉蕉类(糯米蕉)和过山香蕉(龙牙蕉)品种,极少为害香蕉和大蕉。该病属危险性病害,是国际植检对象之一。1960年此病仅在我国广西南宁、邕宁、博白等地零星发生。1975—1977年扩展到海南文昌、海口、儋县。1983—1990年又在广东中山、花县、番禺等地陆续相继发生,发病面积逐年扩大,目前此病在花县和中山县蕉区已成为毁灭性病害,严重阻碍粉蕉和过山香蕉的生产和发展。1988年开始,我们在美籍台湾学者、世界著名植物病理学家。
基金the support from the Physical Research Platform in the School of Physics of Sun Yat-sen University(PRPSP,SYSU)Project supported by the National Natural Science Foundation of China(Grant No.12074445)the Open Fund of the State Key Laboratory of Optoelectronic Materials and Technologies of Sun Yat-sen University(Grant No.OEMT-2022-ZTS-05)。
文摘Single-molecule force spectroscopy(SMFS)measurements of the dynamics of biomolecules typically require identifying massive events and states from large data sets,such as extracting rupture forces from force-extension curves(FECs)in pulling experiments and identifying states from extension-time trajectories(ETTs)in force-clamp experiments.The former is often accomplished manually and hence is time-consuming and laborious while the latter is always impeded by the presence of baseline drift.In this study,we attempt to accurately and automatically identify the events and states from SMFS experiments with a machine learning approach,which combines clustering and classification for event identification of SMFS(ACCESS).As demonstrated by analysis of a series of data sets,ACCESS can extract the rupture forces from FECs containing multiple unfolding steps and classify the rupture forces into the corresponding conformational transitions.Moreover,ACCESS successfully identifies the unfolded and folded states even though the ETTs display severe nonmonotonic baseline drift.Besides,ACCESS is straightforward in use as it requires only three easy-to-interpret parameters.As such,we anticipate that ACCESS will be a useful,easy-to-implement and high-performance tool for event and state identification across a range of single-molecule experiments.
