Single Molecule Analysis Research Tool (SMART): An Integrated Approach for Analyzing Single Molecule Data

作者: Max Greenfeld , Dmitri S. Pavlichin , Hideo Mabuchi , Daniel Herschlag

DOI: 10.1371/JOURNAL.PONE.0030024

关键词:

摘要: Single molecule studies have expanded rapidly over the past decade and ability to provide an unprecedented level of understanding biological systems. A common challenge upon introduction novel, data-rich approaches is management, processing, analysis complex data sets that are generated. We a standardized approach for analyzing these in freely available software package SMART: Molecule Analysis Research Tool. SMART provides format organizing easily accessing single data, general hidden Markov modeling algorithm fitting array possible models specified by user, structure graphical user interfaces streamline visualization data. This guides experimental design, facilitating acquisition maximal information from experiments. also allow dissemination transparency reported

参考文章(67)
Paul R Selvin, Taekjip Ha, Single-molecule techniques : a laboratory manual Cold Spring Harbor Laboratory Press. ,(2008)
Steven L Scott, Bayesian Methods for Hidden Markov Models Journal of the American Statistical Association. ,vol. 97, pp. 337- 351 ,(2002) , 10.1198/016214502753479464
James Franklin, The elements of statistical learning : data mining, inference,and prediction The Mathematical Intelligencer. ,vol. 27, pp. 83- 85 ,(2005) , 10.1007/BF02985802
Gunnar F. Schröder, Helmut Grubmüller, Maximum likelihood trajectories from single molecule fluorescence resonance energy transfer experiments Journal of Chemical Physics. ,vol. 119, pp. 9920- 9924 ,(2003) , 10.1063/1.1616511
Tobias Ryden, Olivier Capp, Eric Moulines, Inference in Hidden Markov Models ,(2008)
Peter J. Bickel, Ya’acov Ritov, Tobias Rydén, Asymptotic normality of the maximum-likelihood estimator for general hidden Markov models Annals of Statistics. ,vol. 26, pp. 1614- 1635 ,(1998) , 10.1214/AOS/1024691255
P. J. Choi, L. Cai, K. Frieda, X. S. Xie, A Stochastic Single-Molecule Event Triggers Phenotype Switching of a Bacterial Cell Science. ,vol. 322, pp. 442- 446 ,(2008) , 10.1126/SCIENCE.1161427
L. Liporace, Maximum likelihood estimation for multivariate observations of Markov sources IEEE Transactions on Information Theory. ,vol. 28, pp. 729- 734 ,(1982) , 10.1109/TIT.1982.1056544