scholarly journals 2D Regional Correlation Analysis of Single-Molecule Time Trajectories

2008 ◽  
Vol 112 (47) ◽  
pp. 14920-14926 ◽  
Author(s):  
Xuefei Wang ◽  
H. Peter Lu
Keyword(s):  
Correlation Analysis ◽  
Single Molecule ◽  
Regional Correlation

Signal-Pair Correlation Analysis of Single-Molecule Trajectories

2011 ◽  
Vol 50 (52) ◽  
pp. 12643-12646 ◽  
Author(s):  
Armin Hoffmann ◽  
Michael T. Woodside
Keyword(s):  
Correlation Analysis ◽  
Single Molecule ◽  
Pair Correlation

scholarly journals Correlation analysis framework for localization-based superresolution microscopy

2018 ◽  
Vol 115 (13) ◽  
pp. 3219-3224 ◽  
Author(s):  
Joerg Schnitzbauer ◽  
Yina Wang ◽  
Shijie Zhao ◽  
Matthew Bakalar ◽  
Tulip Nuwal ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Single Molecule ◽  
Quantitative Description ◽  
Superior Performance ◽  
Cellular Structures ◽  
Analysis Framework ◽  
Biophysical Parameters ◽  
Superresolution Microscopy ◽  
Analysis Platform ◽  
Multiple Scenarios

Superresolution images reconstructed from single-molecule localizations can reveal cellular structures close to the macromolecular scale and are now being used routinely in many biomedical research applications. However, because of their coordinate-based representation, a widely applicable and unified analysis platform that can extract a quantitative description and biophysical parameters from these images is yet to be established. Here, we propose a conceptual framework for correlation analysis of coordinate-based superresolution images using distance histograms. We demonstrate the application of this concept in multiple scenarios, including image alignment, tracking of diffusing molecules, as well as for quantification of colocalization, showing its superior performance over existing approaches.

scholarly journals Analyzing the Effects of Sea Surface Temperature (SST) on Soil Moisture (SM) in Coastal Areas of Eastern China

2020 ◽  
Vol 12 (14) ◽  
pp. 2216
Author(s):  
Yingying Liu ◽  
Yuanzhi Zhang ◽  
Jingze Cai ◽  
Jin Yeu Tsou
Keyword(s):  
Soil Moisture ◽  
Correlation Analysis ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Eastern China ◽  
Sea Surface ◽  
Causality Analysis ◽  
China Sea ◽  
Regional Correlation ◽  
Four Seasons

In this paper, we applied the re-analysis data cobe-SST (cobe-sea surface temperature) and Global Land Data Assimilation System (GLDAS) surface soil moisture (SM) data from 1961 to 2011 by using regional correlation analysis and time series causality analysis to trace annual variations in and identify the abnormal relationship of sea surface temperature (SST) in the eastern China Sea and SM in eastern China (EC). We also used satellite Moderate Resolution Imaging Spectroradiometer (MODIS) SST and AMSR-E SM data to examine the correlation of SST and SM in EC from 2004–2009. The results show that the SST in the eastern China Sea has experienced a warming trend since 1987, whereas the SM in EC has shown a drying trend since 1978. Before 1967 and after 1997, SST and SM changed during opposite phases, whereas from 1967 to 1997 they changed during the same phase. The differences between them may result from the abnormal summer precipitation causing abnormal SM. According to the regional correlation analysis, SST of the East China Sea is significantly related to SM in the southeast coastal area, and temporal sequence causality analysis shows that SST is correlated with and has higher influence on SM than vice versa. SM during spring and autumn shows a similar correlation with SST during the four seasons, so that SM in spring and autumn is positively correlated with SST in autumn and negatively correlated with SST in other seasons. SM in summer and winter correlated with SST in the four seasons, contradicting the foregoing conclusions. All these findings indicate that the thermodynamic state of the eastern China Sea has affected SM in EC.

Correlation Analysis of Atomic and Single-Molecule Junction Conductance

ACS Nano ◽  
2012 ◽  
Vol 6 (4) ◽  
pp. 3411-3423 ◽  
Author(s):  
Péter Makk ◽  
Damian Tomaszewski ◽  
Jan Martinek ◽  
Zoltán Balogh ◽  
Szabolcs Csonka ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Single Molecule ◽  
Molecule Junction ◽  
Single Molecule Junction ◽  
Junction Conductance

scholarly journals A correlation analysis framework for localization-based super-resolution microscopy

2017 ◽  
Author(s):  
Joerg Schnitzbauer ◽  
Yina Wang ◽  
Matthew Bakalar ◽  
Baohui Chen ◽  
Tulip Nuwal ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Single Molecule ◽  
Quantitative Description ◽  
Super Resolution ◽  
Analysis Framework ◽  
Biophysical Parameters ◽  
Wide Range ◽  
The Time Domain ◽  
Analysis Platform ◽  
Super Resolution Microscopy

AbstractSuper-resolution images reconstructed from single-molecule localizations can reveal cellular structures close to the macromolecular scale and are now being used routinely in many biomedical research applications. However, because of their coordinate-based representation, a widely applicable and unified analysis platform that can extract a quantitative description and biophysical parameters from these images is yet to be established. Here, we propose a conceptual framework for correlation analysis of coordinate-based super-resolution images using distance histograms. We demonstrate the application of this concept in multiple scenarios including image alignment, tracking of diffusing molecules, as well as for quantification of colocalization.Significance statementCorrelation analysis is one of the most widely used image processing method. In the quantitative analysis of localization-based super-resolution images, there still lacks a generalized coordinate-based correlation analysis framework to take fully advantage of the super-resolution information. We show a coordinate-based correlation analysis framework for localization-based super-resolution microscopy. This framework is highly general and flexible in that it can be easily extended to model the effect of localization uncertainty, to the time domain and other distance definitions, enabling it to be adapted for a wide range of applications. Our work will greatly benefit the quantitative interpretation of super-resolution images and thus the biological application of super-resolution microscopy.

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