Search arXivSearch

arXiv · 1510.07290

Wavelet-Based Compression and Peak Detection Method for the Experimentally Estimation of Microtubules Dynamic Instability Parameters Identified in Three States

Abstract

Recent studies has revealed that Microtubules (MTs) exhibit three transition states of growth, shrinkage and pause. In this paper, we first introduce a three states random evolution model as a framework for studying MTs dynamics in three transition states of growth, pause and shrinkage. Then, we introduce a non-traditional stack run encoding scheme with 5 symbols for detecting transition states as well as to encode MT experimental data. The peak detection is carried out in the wavelet domain to effectively detect these three transition states. One of the added advantages of including peak information while encoding being that it enables to detect the peaks efficiently and encodes them simultaneously in the wavelet domain without having the need to do further processing after the decoding stage. Experimental results show that using this form of non-traditional stack run encoding has better compression and reconstruction performance as opposed to traditional stack run encoding and run length encoding schemes. Parameters for MTs modeled in the three states are estimated and is shown to closely approximate original MT data for lower compression rates. As the compression rate increases, we may end up throwing away details that are required to detect transition states of MTs. Thus, choosing the right compression rate is a trade-off between admissible level of error in signal reconstruction, its parameter estimation and considerable rate of compression of MT data.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Shantia Yarahmadian, Vineetha Menon, Majid Mahrooghy, Vahid A. Rezania. 2015-10-25. Wavelet-Based Compression and Peak Detection Method for the Experimentally Estimation of Microtubules Dynamic Instability Parameters Identified in Three States. https://arxiv.org/abs/1510.07290

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

A Persistent Random-Walk Model of Molecular Transport in Neuronal Dendritic Trees

A two-level analytical framework is presented for modeling random walk transport of messenger ribonucleic acid (mRNA) molecules along neuronal microtubules from soma to synapses. Motivated by empirical observations of mRNA cargo motion, the transport within a dendrite is modeled by a persistent telegraph process with pauses. Theoretical expressions for the probability of traversing the dendrite and the mean time for such travel are derived for different and equal probabilities of persistence. These results are used for the construction of a semi-Markov model of motion of mRNA cargo within the whole neuron. The semi-Markov model provides the probabilities of absorption at a given synapse and corresponding mean first-passage times (MFPTs) from the soma, where mRNA is transcribed. The theoretical expressions, together with experimentally obtained parameter values, are used to calculate MFPTs for neurons with empirically reconstructed morphology. The model predicts that when retrograde persistence is stronger, the MFPT to each synapse is effectively the same. Otherwise, when the persistence is more pronounced in the anterograde direction, the transport in the neuron resembles the motion along a single dendrite -- nearly linear dependence of MFPT on the distance between soma and synapse. These findings are theoretically justified when the lengths of dendrites are considerably longer than the distance traversed during a typical run.

q-bio.SC

Clustering versus sorting: a mass-conserving reaction-diffusion model of planar polarity puncta

Planar cell polarity is preceded by the clustering of polarity proteins into discrete, low-turnover membrane subdomains (puncta), yet the minimal interactions that nucleate puncta, set their number, and segregate opposite orientations remain unclear. We address these questions with a mass-conserving reaction-diffusion model in which two diffusible monomers bind reversibly across a cell-cell junction into trans-complexes of two orientations, with feedback entering only through concentration-dependent rates. Above a critical density, the uniform state undergoes a long-wavelength mass-redistribution instability rather than a finite-wavelength Turing bifurcation. The form of the feedback then selects between two morphologies: broad mesas fixed by a Maxwell construction under saturating feedback, and narrow mass-limited spikes under unbounded feedback. For spikes we obtain closed-form expressions exhibiting a clean separation of amplitude (mass and feedback), width (the complex diffusion length), and spacing (the monomer screening length). Within a fast-monomer reduction we prove, for any number and arrangement of puncta, that like-oriented arrays coarsen, so multiplicity is metastable and kinetically determined. The second monomer reservoir introduces a second screening length that rate-limits competition by the harmonic mean of the monomer diffusivities, and the spectrum of a punctum remains free of oscillatory ("blinking") instabilities throughout. Finally, sign-definite cross-modulation of turnover converts clustering into orientation sorting - the mutual exclusion of orientations along a single contact: mass redistribution sets puncta number, and the sign of the cross-coupling determines whether orientations segregate. Puncta number and orientation sorting are thus governed by mathematically separable ingredients.

q-bio.SC

Distributed delay stabilizes bistable genetic networks

Delay is an inherent feature of genetic regulatory networks. It represents the time required for the assembly of functional regulator proteins. The protein production process is complex, as it includes transcription, translocation, translation, folding, and oligomerization. Because these steps are noisy, the resulting delay associated with protein production is distributed (random). We here consider how distributed delay impacts the dynamics of bistable genetic circuits. We show that for a variety of genetic circuits that exhibit bistability, increasing the noise level in the delay distribution dramatically stabilizes the metastable states. By this we mean that mean residence times in the metastable states dramatically increase. Relevance to Life Sciences. Bistable genetic regulatory networks are ubiquitous in living organisms. Evolutionary processes seem to have tuned such networks so that they switch between metastable states when it is important to do so, but small fluctuations do not cause unwanted switching. Understanding how evolution has tuned the stability of biological switches is an important problem. In particular, such understanding can guide the design of forward-engineered synthetic bistable genetic regulatory networks. Mathematical Content. We use two methods to explain this stabilization phenomenon. First, we introduce and simulate stochastic hybrid models that depend on a switching-rate parameter. These stochastic hybrid models allow us to unfold the distributed-delay models in the sense that, in certain cases, the distributed-delay model can be viewed as a fast-switching limit of the corresponding stochastic hybrid model. Second, we generalize the three-states model, a symbolic model of bistability, and analyze this extension.

q-bio.SC