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Biological noise

Seong Jun Park, Sanggeun Song, Gil-Suk Yang, Philip M Kim, Sangwoon Yoon, Ji-Hyun Kim, Jaeyoung Sung
Gene expression is a complex stochastic process composed of numerous enzymatic reactions with rates coupled to hidden cell-state variables. Despite advances in single-cell technologies, the lack of a theory accurately describing the gene expression process has restricted a robust, quantitative understanding of gene expression variability among cells. Here we present the Chemical Fluctuation Theorem (CFT), providing an accurate relationship between the environment-coupled chemical dynamics of gene expression and gene expression variability...
January 19, 2018: Nature Communications
Sandip Datta, Brian Seed
Experimental data indicate that stochastic effects exerted at the level of translation contribute substantially to the variation in abundance of proteins expressed at moderate to high levels. This study analyzes the theoretical consequences of fluctuations in residue-specific elongation rates during translation. A simple analytical framework shows that rate variation during elongation gives rise to protein production rates that consist of sums of products of random variables. Simulations show that because the contribution to total variation of products of random variables greatly exceeds that of sums of random variables, the overall distribution exhibits approximately log-normal behavior...
2018: PloS One
Zhuocheng Xiao, Jiwei Zhang, Andrew T Sornborger, Louis Tao
Line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next...
November 2017: Physical Review. E
Ira B Schwartz, Klimka Szwaykowska, Thomas W Carr
Networks of interacting, communicating subsystems are common in many fields, from ecology, biology, and epidemiology to engineering and robotics. In the presence of noise and uncertainty, interactions between the individual components can lead to unexpected complex system-wide behaviors. In this paper, we consider a generic model of two weakly coupled dynamical systems, and we show how noise in one part of the system is transmitted through the coupling interface. Working synergistically with the coupling, the noise on one system drives a large fluctuation in the other, even when there is no noise in the second system...
October 2017: Physical Review. E
Tommaso Spanio, Jorge Hidalgo, Miguel A Muñoz
Variability on external conditions has important consequences for the dynamics and the organization of biological systems. In many cases, the characteristic timescale of environmental changes as well as their correlations play a fundamental role in the way living systems adapt and respond to it. A proper mathematical approach to understand population dynamics, thus, requires approaches more refined than, e.g., simple white-noise approximations. To shed further light onto this problem, in this paper we propose a unifying framework based on different analytical and numerical tools available to deal with "colored" environmental noise...
October 2017: Physical Review. E
Duccio Fanelli, Francesco Ginelli, Roberto Livi, Niccoló Zagli, Clement Zankoc
We study a simple stochastic model of neuronal excitatory and inhibitory interactions. The model is defined on a directed lattice and internodes couplings are modulated by a nonlinear function that mimics the process of synaptic activation. We prove that such a system behaves as a fully tunable amplifier: the endogenous component of noise, stemming from finite size effects, seeds a coherent (exponential) amplification across the chain generating giant oscillations with tunable frequencies, a process that the brain could exploit to enhance, and eventually encode, different signals...
December 2017: Physical Review. E
Paul C Bressloff, Sean D Lawley
A fundamental issue in the theory of continuous stochastic process is the interpretation of multiplicative white noise, which is often referred to as the Itô-Stratonovich dilemma. From a physical perspective, this reflects the need to introduce additional constraints in order to specify the nature of the noise, whereas from a mathematical perspective it reflects an ambiguity in the formulation of stochastic differential equations (SDEs). Recently, we have identified a mechanism for obtaining an Itô SDE based on a form of temporal disorder...
July 2017: Physical Review. E
Himadri S Samanta, Michael Hinczewski, D Thirumalai
Signaling in enzymatic networks is typically triggered by environmental fluctuations, resulting in a series of stochastic chemical reactions, leading to corruption of the signal by noise. For example, information flow is initiated by binding of extracellular ligands to receptors, which is transmitted through a cascade involving kinase-phosphatase stochastic chemical reactions. For a class of such networks, we develop a general field-theoretic approach to calculate the error in signal transmission as a function of an appropriate control variable...
July 2017: Physical Review. E
J Stritzel, O Melchert, M Wollweber, B Roth
The direct problem of optoacoustic signal generation in biological media consists of solving an inhomogeneous three-dimensional (3D) wave equation for an initial acoustic stress profile. In contrast, the more defiant inverse problem requires the reconstruction of the initial stress profile from a proper set of observed signals. In this article, we consider an effectively 1D approach, based on the assumption of a Gaussian transverse irradiation source profile and plane acoustic waves, in which the effects of acoustic diffraction are described in terms of a linear integral equation...
September 2017: Physical Review. E
Brendan P Marsh, Nagaraju Chada, Raghavendar Reddy Sanganna Gari, Krishna P Sigdel, Gavin M King
Imaging by atomic force microscopy (AFM) offers high-resolution descriptions of many biological systems; however, regardless of resolution, conclusions drawn from AFM images are only as robust as the analysis leading to those conclusions. Vital to the analysis of biomolecules in AFM imagery is the initial detection of individual particles from large-scale images. Threshold and watershed algorithms are conventional for automatic particle detection but demand manual image preprocessing and produce particle boundaries which deform as a function of user-defined parameters, producing imprecise results subject to bias...
January 17, 2018: Scientific Reports
Christopher J Hillar, Ngoc M Tran
The Hopfield recurrent neural network is a classical auto-associative model of memory, in which collections of symmetrically coupled McCulloch-Pitts binary neurons interact to perform emergent computation. Although previous researchers have explored the potential of this network to solve combinatorial optimization problems or store reoccurring activity patterns as attractors of its deterministic dynamics, a basic open problem is to design a family of Hopfield networks with a number of noise-tolerant memories that grows exponentially with neural population size...
January 16, 2018: Journal of Mathematical Neuroscience
Chunhe Li
Landscape approaches have been exploited to study the stochastic dynamics of gene networks. However, how to calculate the landscape with a wide range of parameter variations and how to investigate the influence of the network topology on the global properties of gene networks remain to be elucidated. Here, I developed an approach for the landscape of random parameter perturbation (LRPP) to address this issue. Based on a self-consistent approximation approach, by making perturbations to parameters in a given range, I obtained the landscape for gene network systems...
January 17, 2018: Integrative Biology: Quantitative Biosciences From Nano to Macro
Roxana Jalili, Joe Horecka, James R Swartz, Ronald W Davis, Henrik H J Persson
Proximity ligation assay (PLA) is a powerful tool for quantitative detection of protein biomarkers in biological fluids and tissues. Here, we present the circular proximity ligation assay (c-PLA), a highly specific protein detection method that outperforms traditional PLA in stringency, ease of use, and compatibility with low-affinity reagents. In c-PLA, two proximity probes bind to an analyte, providing a scaffolding that positions two free oligonucleotides such that they can be ligated into a circular DNA molecule...
January 16, 2018: Proceedings of the National Academy of Sciences of the United States of America
Di Jin, Renjie Zhou, Zahid Yaqoob, Peter T C So
Optical diffraction tomography (ODT) is an emerging microscopy technique for three-dimensional (3D) refractive index (RI) mapping of transparent specimens. Recently, the digital micromirror device (DMD) based scheme for angle-controlled plane wave illumination has been proposed to improve the imaging speed and stability of ODT. However, undesired diffraction noise always exists in the reported DMD-based illumination scheme, which leads to a limited contrast ratio of the measurement fringe and hence inaccurate RI mapping...
January 8, 2018: Optics Express
Qilai Zhao, Kaijun Zhou, Zisheng Wu, Changsheng Yang, Zhouming Feng, Huihui Cheng, Jiulin Gan, Mingying Peng, Zhongmin Yang, Shanhui Xu
The Earth's magnetic field has significant effects that protect us from cosmic radiation and provide navigation for biological migration. However, slow temporal variations originating in the liquid outer core invariably exist. To understand the working mechanism of the geomagnetic field and improve accuracy of navigation systems, a high-precision magnetometer is essential to measure the absolute magnetic field. A helium optically pumping magnetometer is an advanced approach, but its sensitivity and accuracy are directly limited by the low-frequency relative intensity noise and frequency stability characteristics of a light source...
January 1, 2018: Optics Letters
Melinda T Owens, Gloriana Trujillo, Shannon B Seidel, Colin D Harrison, Katherine M Farrar, Hilary P Benton, J R Blair, Katharyn E Boyer, Jennifer L Breckler, Laura W Burrus, Dana T Byrd, Natalia Caporale, Edward J Carpenter, Yee-Hung M Chan, Joseph C Chen, Lily Chen, Linda H Chen, Diana S Chu, William P Cochlan, Robyn J Crook, Karen D Crow, José R de la Torre, Wilfred F Denetclaw, Lynne M Dowdy, Darleen Franklin, Megumi Fuse, Michael A Goldman, Brinda Govindan, Michael Green, Holly E Harris, Zheng-Hui He, Stephen B Ingalls, Peter Ingmire, Amber R B Johnson, Jonathan D Knight, Gretchen LeBuhn, Terrye L Light, Candace Low, Lance Lund, Leticia M Márquez-Magaña, Vanessa C Miller-Sims, Christopher A Moffatt, Heather Murdock, Gloria L Nusse, V Thomas Parker, Sally G Pasion, Robert Patterson, Pleuni S Pennings, Julio C Ramirez, Robert M Ramirez, Blake Riggs, Rori V Rohlfs, Joseph M Romeo, Barry S Rothman, Scott W Roy, Tatiane Russo-Tait, Ravinder N M Sehgal, Kevin A Simonin, Greg S Spicer, Jonathon H Stillman, Andrea Swei, Leslie C Tempe, Vance T Vredenburg, Steven L Weinstein, Andrew G Zink, Loretta A Kelley, Carmen R Domingo, Kimberly D Tanner
Many efforts to improve science teaching in higher education focus on a few faculty members at an institution at a time, with limited published evidence on attempts to engage faculty across entire departments. We created a long-term, department-wide collaborative professional development program, Biology Faculty Explorations in Scientific Teaching (Biology FEST). Across 3 years of Biology FEST, 89% of the department's faculty completed a weeklong scientific teaching institute, and 83% of eligible instructors participated in additional semester-long follow-up programs...
2018: CBE Life Sciences Education
Daniel Trejo Banos, Pauline Trébulle, Mohamed Elati
BACKGROUND: Genome-scale metabolic models provide an opportunity for rational approaches to studies of the different reactions taking place inside the cell. The integration of these models with gene regulatory networks is a hot topic in systems biology. The methods developed to date focus mostly on resolving the metabolic elements and use fairly straightforward approaches to assess the impact of genome expression on the metabolic phenotype. RESULTS: We present here a method for integrating the reverse engineering of gene regulatory networks into these metabolic models...
December 21, 2017: BMC Systems Biology
Yuta Sakurai, Yutaka Hori
Model-guided design has become a standard approach to engineering biomolecular circuits in synthetic biology. However, the stochastic nature of biomolecular reactions is often overlooked in the design process. As a result, cell-cell heterogeneity causes unexpected deviation of biocircuit behaviours from model predictions and requires additional iterations of design-build-test cycles. To enhance the design process of stochastic biocircuits, this paper presents a computational framework to systematically specify the level of intrinsic noise using well-defined metrics of statistics and design highly heterogeneous biocircuits based on the specifications...
January 2018: Journal of the Royal Society, Interface
Anthony Turner, Michael Fischer, Joseph Tzanopoulos
Acoustic diversity indices have been proposed as low-cost biodiversity monitoring tools. The acoustic diversity of a soundscape can be indicative of the richness of an acoustic community and the structural/vegetation characteristics of a habitat. There is a need to apply these methods to landscapes that are ecologically and/or economically important. We investigate the relationship between the acoustic properties of a coniferous forest with stand-age and structure. We sampled a 73 point grid in part of the UK's largest man-made lowland coniferous plantation forest, covering a 320ha mosaic of different aged stands...
2018: PloS One
Zhutian Ding, James M Stubbs, Danielle McRae, Johanna M Blacquiere, François Lagugné-Labarthet, Silvia Mittler
A plasmonic sensing system that allows the excitation of localized surface plasmon resonance (LSPR) by individual waveguide modes is presented conceptually and experimentally. Any change in the local environment of the gold nanoparticles (AuNPs) alters the degree of coupling between LSPR and a polymer slab waveguide, which then modulates the transmission-output signal. In comparison to conventional LSPR sensors, this system is less susceptible to optical noise and positional variation of signals. Moreover, it enables more freedom in the exploitation of plasmonic hot spots with both transverse electric (TE) and transverse magnetic (TM) modes...
January 10, 2018: ACS Sensors
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