Trends in template/fragment-free protein structure prediction

Predicting the structure of a protein from its amino acid sequence is a long-standing unsolved problem in computational biology. Its solution would be of both fundamental and practical importance as the gap between the number of known sequences and the number of experimentally solved structures widens rapidly. Currently, the most successful approaches are based on fragment/template reassembly. Lacking progress in template-free structure prediction calls for novel ideas and approaches. This article reviews trends in the development of physical and specific knowledge-based energy functions as well as sampling techniques for fragment-free structure prediction. Recent physical- and knowledge-based studies demonstrated that it is possible to sample and predict highly accurate protein structures without borrowing native fragments from known protein structures. These emerging approaches with fully flexible sampling have the potential to move the field forward

Numerical study of urban expansion and its influence on urban environment using Landsat TM/ETM plus images

Multi-temporal Landsat TM/ETM+ imagery of 1990, 2000, and 2005 were used in this study. And the vegetation abundances, percent impervious surface, normalized difference impervious surface index(NDISI) and brightness temperature were retrieved from each TM/ETM+ dataset. Then the urban expansion, urban heat island and the relationships between LST and other variables which relate to urban environment were investigated. Results indicated that the percentage of urban area in Guangzhou increased significantly, which grew from 18.35% in 1990, to 24-16% in 2000, and further to 33.29% in 2005. But the intensity of urban heat island was not always enlarged during 1990-2005. And the regression analyses showed that, at the pixel-scale, the relationships between LST and other two variables (vegetation abundances and percent impervious surface) were relatively more complicated and could not be described by using the linear regression model. However, LST had a strong positive and negative correlation with percent impervious area and vegetation abundance in the region-scale, respectively. These results may be very useful for moderate- or large-scale ecological modeling and climate modeling

基于实时精密单点定位技术的暴雨短临预报

Author name used in this publication: 朱建军Author name used in this publication: 陈武Author name used in this publication: 陈永奇Author name used in this publication: 龙四春Author name used in this publication: 李洪玉Title in Traditional Chinese: 基于實時精密單點定位技術的暴雨短臨預報Journal title in Traditional Chinese: 地球物理學報2011-2012 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe