Recurrence Quantification Analysis in Molecular Dynamics

Manetti, Cesare; Ceruso, Marc-Antoine; Giuliani, Alessandro; Webber, Charles L.; Zbilut, Joseph P.

doi:10.1111/j.1749-6632.1999.tb10429.x

Cited by 12 publications

(12 citation statements)

References 35 publications

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“…Besides the global impression given by the appearance of the recurrent plot, quantitative descriptors were developed and are included in the recurrence quantification analysis method (RQA). These are recurrence, determinism, ratio, entropy, maxline, trend, and spatio-temporal entropy [18,19]. Recurrence quantifies the percentage of the plot occupied by recurrent points.…”

Section: Measurementsmentioning

confidence: 99%

“…Recurrence plot analysis is a relatively new technique for the qualitative assessment of time series [18,19]. Technically, this method expands a one-dimensional time series into a higher dimensional space.…”

Section: Measurementsmentioning

confidence: 99%

“…On multivariate analysis, the best predictors of CFS were HR-tilt-R/L, PTTtilt-R/L, HR-supine-DET, PTT-tilt-WAVE, and HR-tilt-SD. Based on these predictors, the 'Fractal & Recurrence Analysisbased Score' (FRAS) was calculated: FRAS = 76.2 + 0.04*HRsupine-DET -12.9*HR-tilt-R/L -0.31*HR-tilt-SD - 19.27*PTT-tilt-R/L -9.42* PTT-tilt-WAVE. The best cut-off differentiating CFS from the control population was FRAS = + 0.22.…”

Section: Introductionmentioning

confidence: 99%

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Fractal analysis and recurrence quantification analysis of heart rate and pulse transit time for diagnosing chronic fatigue syndrome

Naschitz¹,

Sabo²,

Naschitz³

et al. 2002

Clinical Autonomic Research

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This study aimed to develop a method to distinguish between the cardiovascular reactivity in chronic fatigue syndrome (CFS) and other patient populations. Patients with CFS (n = 23), familial Mediterranean fever (n = 15), psoriatic arthritis (n = 10), generalized anxiety disorder (n = 12), neurally mediated syncope (n = 20), and healthy subjects (n = 20) were evaluated with a shortened head-up tilt test (HUTT). A 10-minute supine phase of the HUTT was followed by recording 600 cardiac cycles on tilt, i. e., 5 to 10 minutes. Beat-to-beat heart rate (HR) and pulse transit time (PTT) were acquisitioned. Data were processed by recurrence plot and fractal analysis. Fifty-two variables were calculated in each subject. On multivariate analysis, the best predictors of CFS were HR-tilt-R/L, PTT-tilt-R/L, HR-supine-DET, PTT-tilt-WAVE, and HR-tilt-SD. Based on these predictors, the 'Fractal & Recurrence Analysis-based Score' (FRAS) was calculated: FRAS = 76.2 + 0.04*HR-supine-DET - 12.9*HR-tilt-R/L - 0.31*HR-tilt-SD - 19.27*PTT-tilt-R/L - 9.42* PTT-tilt-WAVE. The best cut-off differentiating CFS from the control population was FRAS = + 0.22. FRAS > + 0.22 was associated with CFS (sensitivity 70 % and specificity 88 %). The cardiovascular reactivity received mathematical expression with the aid of the FRAS. The shortened HUTT was well tolerated. The FRAS provides objective criteria which could become valuable in the assessment of CFS.

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Section: Measurementsmentioning

confidence: 99%

Section: Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fractal analysis and recurrence quantification analysis of heart rate and pulse transit time for diagnosing chronic fatigue syndrome

Naschitz¹,

Sabo²,

Naschitz³

et al. 2002

Clinical Autonomic Research

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“…8,9 Technically, this method expands a one-dimensional time series into a higher dimensional space. This is done by using a 'delayed coordinate embedding,' which creates a phase space portrait (recurrence plot) of the system.…”

Section: Recurrence Quantitative Analysis (Rqa)mentioning

confidence: 99%

“…These include fractal analysis, 6,7 recurrence quantification analysis, 8,9 and multivariate models that consider the relation between two or more cardiovascular signals. 10 It has been suggested that joint quantification of BP and HR fluctuations, and utilization of non-Euclidean mathematic analysis may provide more reliable information on cardiovascular reactivity.…”

Section: Introductionmentioning

confidence: 99%

Assessment of cardiovascular reactivity by fractal and recurrence quantification analysis of heart rate and pulse transit time

et al. 2003

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Elucidating protein secondary structures using alpha‐carbon recurrence quantifications

Webber

Giuliani

Zbilut³

et al. 2001

Proteins

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Secondary structures of proteins were studied by recurrence quantification analysis (RQA). High-resolution, 3-dimensional coordinates of alpha-carbon atoms comprising a set of 68 proteins were downloaded from the Protein Data Bank. By fine-tuning four recurrence parameters (radius, line, residue, separation), it was possible to establish excellent agreement between percent contribution of alpha-helix and beta-sheet structures determined independently by RQA and that of the DSSP algorithm (Define Secondary Structure of Proteins). These results indicate that there is an equivalency between these two techniques, which are based upon totally different pattern recognition strategies. RQA enhances qualitative contact maps by quantifying the arrangements of recurrent points of alpha carbons close in 3-dimensional space. For example, the radius was systematically increased, moving the analysis beyond local alpha-carbon neighborhoods in order to capture super-secondary and tertiary structures. However, differences between proteins could only be detected within distances up to about 6-11 A, but not higher. This result underscores the complexity of alpha-carbon spacing when super-secondary structures appear at larger distances. Finally, RQA-defined secondary structures were found to be robust against random displacement of alpha carbons upwards of 1 A. This finding has potential import for the dynamic functions of proteins in motion.

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Recurrence Quantification Analysis in Molecular Dynamics

Cited by 12 publications

References 35 publications

Fractal analysis and recurrence quantification analysis of heart rate and pulse transit time for diagnosing chronic fatigue syndrome

Fractal analysis and recurrence quantification analysis of heart rate and pulse transit time for diagnosing chronic fatigue syndrome

Assessment of cardiovascular reactivity by fractal and recurrence quantification analysis of heart rate and pulse transit time

Elucidating protein secondary structures using alpha‐carbon recurrence quantifications

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