A Peak Synchronization Measure for Multiple Signals

Biswas, Rahul; Khamaru, Koulik; Majumdar, Kaushik

doi:10.1109/tsp.2014.2333568

Cited by 15 publications

(9 citation statements)

References 49 publications

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“…Gaussian weights were inferred based on a probability density function with threshold th = 0.0001 after which tails were considered insignificant and omitted, a central coefficient ca = 0.5 describing the bin width at which the maximum weight was applied, and SD = 1. The resulting consensus profiles were found very robust to the choice of these parameters as previously reported (63). Multi-mapping positions in sequences were excluded from computing the consensus profile.…”

Section: Consensus Rd Profilessupporting

confidence: 52%

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Inferring translational heterogeneity from ribosome profiling data

Bordignon

Pechmann

2019

Preprint

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Translation of messenger RNAs into proteins by the ribosome is the most important step of protein biosynthesis. Accordingly, translation is tightly controlled and heavily regulated to maintain cellular homeostasis. Ribosome profiling (Ribo-seq) has revolutionized the study of translation by revealing many of its underlying mechanisms. However, equally many aspects of translation remain mysterious, in part also due to persisting challenges in the interpretation of data obtained from Ribo-seq experiments. Here, we show that some of the variability observed in Ribo-seq data has biological origins and reflects programmed heterogeneity of translation. To systematically identify sequences that are differentially translated (DT) across mRNAs beyond what can be attributed to experimental variability, we performed a comparative analysis of Ribo-seq data from Saccharomyces cerevisiae and derived a consensus ribosome density profile that reflects consistent signals in individual experiments. Remarkably, the thus identified DT sequences link to mechanisms known to regulate translation elongation and are enriched in genes important for protein and organelle biosynthesis. Our results thus highlight examples of translational heterogeneity that are encoded in the genomic sequences and tuned to optimizing cellular homeostasis. More generally, our work highlights the power of Ribo-seq to understand the complexities of translation regulation.

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Section: Consensus Rd Profilessupporting

confidence: 52%

“…Consensus ribosome density profiles were computed with a peak synchronization algorithm initially developed for the analysis of EEG data (63). Herein, peaks in individual profiles were detected by segmentation above a threshold of profile mean + 1SD (standard deviation).…”

Section: Consensus Rd Profilesmentioning

confidence: 99%

Inferring translational heterogeneity from ribosome profiling data

Bordignon

Pechmann

2019

Preprint

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“…Due to the sensitivity of arresting translation during Ribo‐seq experiments, RD peaks in individual experiments may not be found at exactly the same positions but very slightly shifted. To account for this, we chose to derive a consensus profile upon applying a peak synchronization algorithm [65] (see Materials and methods). Importantly, the resulting consensus RD profile visibly reflected the main features of the individual profiles for the gene LTV1 (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Consensus RD profiles were computed with a peak synchronization algorithm initially developed for the analysis of electroencephalography data [65]. Herein, peaks in individual profiles were detected by segmentation above a threshold of profile mean + 1 SD (standard deviation) and represented as binary peak profile.…”

Section: Methodsmentioning

confidence: 99%

Inferring translational heterogeneity from Saccharomyces cerevisiae ribosome profiling

Bordignon

Pechmann

2021

The FEBS Journal

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Translation of mRNAs into proteins by the ribosome is the most important step of protein biosynthesis. Accordingly, translation is tightly controlled and heavily regulated to maintain cellular homeostasis. Ribosome profiling (Ribo‐seq) has revolutionized the study of translation by revealing many of its underlying mechanisms. However, equally many aspects of translation remain mysterious, in part also due to persisting challenges in the interpretation of data obtained from Ribo‐seq experiments. Here, we show that some of the variability observed in Ribo‐seq data has biological origins and reflects programmed heterogeneity of translation. Through a comparative analysis of Ribo‐seq data from Saccharomyces cerevisiae, we systematically identify short 3‐codon sequences that are differentially translated (DT) across mRNAs, that is, identical sequences that are translated sometimes fast and sometimes slowly beyond what can be attributed to variability between experiments. Remarkably, the thus identified DT sequences link to mechanisms known to regulate translation elongation and are enriched in genes important for protein and organelle biosynthesis. Our results thus highlight examples of translational heterogeneity that are encoded in the genomic sequences and tuned to optimizing cellular homeostasis. More generally, our work highlights the power of Ribo‐seq to understand the complexities of translation regulation.

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“…In order to measure the phase synchronization of the outputs at different steps of the coarse-graining process, for each hierarchical network, we calculate the index of synchronization occurring between K outputs, which would constitute a clique in this network. 36 For this, we calculate the instantaneous phase θ j (ν, t) of the output s j in the level ν at time t as…”

Section: Chaosmentioning

confidence: 99%

Dynamics of hierarchical weighted networks of van der Pol oscillators

Monsivais-Velazquez

Bhattacharya

Barrio

et al. 2020

Chaos: An Interdisciplinary Journal of Nonlinear Science

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We investigate the dynamics of regular fractal-like networks of hierarchically coupled van der Pol oscillators. The hierarchy is imposed in terms of the coupling strengths or link weights. We study the low frequency modes, as well as frequency and phase synchronization, in the network by a process of repeated coarse-graining of oscillator units. At any given stage of this process, we sum over the signals from the oscillator units of a clique to obtain a new oscillating unit. The frequencies and the phases for the coarse-grained oscillators are found to progressively synchronize with the number of coarse-graining steps. Furthermore, the characteristic frequency is found to decrease and finally stabilize to a value that can be tuned via the parameters of the system. We compare our numerical results with those of an approximate analytic solution and find good qualitative agreement. Our study on this idealized model shows how oscillations with a precise frequency can be obtained in systems with heterogeneous couplings. It also demonstrates the effect of imposing a hierarchy in terms of link weights instead of one that is solely topological, where the connectivity between oscillators would be the determining factor, as is usually the case.

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A Peak Synchronization Measure for Multiple Signals

Cited by 15 publications

References 49 publications

Inferring translational heterogeneity from ribosome profiling data

Inferring translational heterogeneity from ribosome profiling data

Inferring translational heterogeneity from Saccharomyces cerevisiae ribosome profiling

Dynamics of hierarchical weighted networks of van der Pol oscillators

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