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1. chinaXiv:201605.01445 [pdf]

Bayesian localization microscopy based on intensity distribution of fluorophores

Xu, Fan; Liu, Zhiyong; Zhang, Fa; Xu, Fan; Zhang, Mingshu; Xu, Pingyong
Subjects: Biology >> Biophysics >> Cell Biology

Super-resolution microscopy techniques have overcome the limit of optical diffraction. Recently, the Bayesian analysis of Bleaching and Blinking data (3B) method has emerged as an important tool to obtain super-resolution fluorescence images. 3B uses the change in information caused by adding or removing fluorophores in the cell to fit the data. When adding a new fluorophore, 3B selects a random initial position, optimizes this position and then determines its reliability. However, the fluorophores are not evenly distributed in the entire image region, and the fluorescence intensity at a given position positively correlates with the probability of observing a fluorophore at this position. In this paper, we present a Bayesian analysis of Bleaching and Blinking microscopy method based on fluorescence intensity distribution (FID3B). We utilize the intensity distribution to select more reliable positions as the initial positions of fluorophores. This approach can improve the reconstruction results and significantly reduce the computational time. We validate the performance of our method using both simulated data and experimental data from cellular structures. The results confirm the effectiveness of our method.

submitted time 2016-05-12 Hits1716Downloads942 Comment 0

2. chinaXiv:201605.01228 [pdf]

Drift correction for single-molecule imaging by molecular constraint field, a distance minimum metric

Han, Renmin; Xu, Fan; Ren, Fei; Zhang, Fa; Han, Renmin; Xu, Fan; Ren, Fei; Zhang, Fa; Han, Renmin; Xu, Fan; Wang, Liansan; Zhang, Yongdeng; Zhang, Mingshu; Liu, Zhiyong
Subjects: Biology >> Biophysics

Background: The recent developments of far-field optical microscopy (single molecule imaging techniques) have overcome the diffraction barrier of light and improve image resolution by a factor of ten compared with conventional light microscopy. These techniques utilize the stochastic switching of probe molecules to overcome the diffraction limit and determine the precise localizations of molecules, which often requires a long image acquisition time. However, long acquisition times increase the risk of sample drift. In the case of high resolution microscopy, sample drift would decrease the image resolution. Results: In this paper, we propose a novel metric based on the distance between molecules to solve the drift correction. The proposed metric directly uses the position information of molecules to estimate the frame drift. We also designed an algorithm to implement the metric for the general application of drift correction. There are two advantages of our method: First, because our method does not require space binning of positions of molecules but directly operates on the positions, it is more natural for single molecule imaging techniques. Second, our method can estimate drift with a small number of positions in each temporal bin, which may extend its potential application. Conclusions: The effectiveness of our method has been demonstrated by both simulated data and experiments on single molecular images.

submitted time 2016-05-11 Hits1609Downloads886 Comment 0

3. chinaXiv:201605.01226 [pdf]

OpenMS-Simulator: an open-source software for theoretical tandem mass spectrum prediction

Wang, Yaojun; Yang, Fei; Bu, Dongbo; Sun, Shiwei; Wang, Yaojun; Yang, Fei; Wu, Peng
Subjects: Biology >> Biophysics

Background: Tandem mass spectrometry (MS/MS) acts as a key technique for peptide identification. The MS/MS-based peptide identification approaches can be categorized into two families, namely, de novo and database search. Both of the two types of approaches can benefit from an accurate prediction of theoretical spectrum. A theoretical spectrum consists of m/z and intensity of possibly occurring ions, which are estimated via simulating the spectrum generating process. Extensive researches have been conducted for theoretical spectrum prediction; however, the prediction methods suffer from low prediciton accuracy due to oversimplifications in the spectrum simulation process. Results: In the study, we present an open-source software package, called OpenMS-Simulator, to predict theoretical spectrum for a given peptide sequence. Based on the mobile-proton hypothesis for peptide fragmentation, OpenMS-Simulator trained a closed-form model for the intensity ratio of adjacent y ions, from which the whole theoretical spectrum can be constructed. On a collection of representative spectra datasets with annotated peptide sequences, experimental results suggest that OpenMS-Simulator can predict theoretical spectra with considerable accuracy. The study also presents an application of OpenMS-Simulator: the similarity between theoretical spectra and query spectra can be used to re-rank the peptide sequence reported by SEQUEST/X!Tandem. Conclusions: OpenMS-Simulator implements a novel model to predict theoretical spectrum for a given peptide sequence. Compared with existing theoretical spectrum prediction tools, say MassAnalyzer and MSSimulator, our method not only simplifies the computation process, but also improves the prediction accuracy. Currently, OpenMS-Simulator supports the prediction of CID and HCD spectrum for peptides with double charges. The extension to cover more fragmentation models and support multiple-charged peptides remains as one of the future works.

submitted time 2016-05-11 Hits1421Downloads819 Comment 0

4. chinaXiv:201605.01198 [pdf]

A novel fully automatic scheme for fiducial marker-based alignment in electron tomography

Han, Renmin; Zhang, Fa; Han, Renmin; Sun, Fei; Liu, Zhiyong; Sun, Fei; Sun, Fei
Subjects: Biology >> Biophysics >> Biochemistry & Molecular Biology

Although the topic of fiducial marker-based alignment in electron tomography (ET) has been widely discussed for decades, alignment without human intervention remains a difficult problem. Specifically, the emergence of subtomogram averaging has increased the demand for batch processing during tomographic reconstruction; fully automatic fiducial marker-based alignment is the main technique in this process. However, the lack of an accurate method for detecting and tracking fiducial markers precludes fully automatic alignment. In this paper, we present a novel, fully automatic alignment scheme for ET. Our scheme has two main contributions: First, we present a series of algorithms to ensure a high recognition rate and precise localization during the detection of fiducial markers. Our proposed solution reduces fiducial marker detection to a sampling and classification problem and further introduces an algorithm to solve the parameter dependence of marker diameter and marker number. Second, we propose a novel algorithm to solve the tracking of fiducial markers by reducing the tracking problem to an incomplete point set registration problem. Because a global optimization of a point set registration occurs, the result of our tracking is independent of the initial image position in the tilt series, allowing for the robust tracking of fiducial markers without pre-alignment. The experimental results indicate that our method can achieve an accurate tracking, almost identical to the current best one in IMOD with half automatic scheme. Furthermore, our scheme is fully automatic, depends on fewer parameters (only requires a gross value of the marker diameter) and does not require any manual interaction, providing the possibility of automatic batch processing of electron tomographic reconstruction. (C) 2015 Elsevier Inc. All rights reserved.

submitted time 2016-05-11 Hits1573Downloads1007 Comment 0

5. chinaXiv:201605.00758 [pdf]

A local-optimization refinement algorithm in single particle analysis for macromolecular complex with multiple rigid modules

Shan, Hong; Yin, Chang-Cheng; Sun, Fei; Wang, Zihao; Zhang, Fa; Wang, Zihao; Zhang, Fa; Wang, Zihao; Sun, Fei; Xiong, Yong; Sun, Fei;
Subjects: Biology >> Biophysics >> Cell Biology

Single particle analysis, which can be regarded as an average of signals from thousands or even millions of particle projections, is an efficient method to study the three-dimensional structures of biological macromolecules. An intrinsic assumption in single particle analysis is that all the analyzed particles must have identical composition and conformation. Thus specimen heterogeneity in either composition or conformation has raised great challenges for high-resolution analysis. For particles with multiple conformations, inaccurate alignments and orientation parameters will yield an averaged map with diminished resolution and smeared density. Besides extensive classification approaches, here based on the assumption that the macromolecular complex is made up of multiple rigid modules whose relative orientations and positions are in slight fluctuation around equilibriums, we propose a new method called as local optimization refinement to address this conformational heterogeneity for an improved resolution. The key idea is to optimize the orientation and shift parameters of each rigid module and then reconstruct their three-dimensional structures individually. Using simulated data of 80S/70S ribosomes with relative fluctuations between the large (60S/50S) and the small (40S/30S) subunits, we tested this algorithm and found that the resolutions of both subunits are significantly improved. Our method provides a proof-of-principle solution for high-resolution single particle analysis of macromolecular complexes with dynamic conformations.

submitted time 2016-05-05 Hits1552Downloads882 Comment 0

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