Read by QxMD icon Read

Stochastic modeling

Seydou Traoré, David Allouche, Isabelle André, Thomas Schiex, Sophie Barbe
One main challenge in Computational Protein Design (CPD) lies in the exploration of the amino-acid sequence space, while considering, to some extent, side chain flexibility. The exorbitant size of the search space urges for the development of efficient exact deterministic search methods enabling identification of low-energy sequence-conformation models, corresponding either to the global minimum energy conformation (GMEC) or an ensemble of guaranteed near-optimal solutions. In contrast to stochastic local search methods that are not guaranteed to find the GMEC, exact deterministic approaches always identify the GMEC and prove its optimality in finite but exponential worst-case time...
2017: Methods in Molecular Biology
Marc D Ryser, Walter T Lee, Neal E Ready, Kevin Z Leder, Jasmine Foo
High rates of local recurrence in tobacco-related head and neck squamous cell carcinoma (HNSCC) are commonly attributed to unresected fields of precancerous tissue. Because they are not easily detectable at the time of surgery without additional biopsies, there is a need for noninvasive methods to predict the extent and dynamics of these fields. Here, we developed a spatial stochastic model of tobacco-related HNSCC at the tissue level and calibrated the model using a Bayesian framework and population-level incidence data from the Surveillance, Epidemiology, and End Results (SEER) registry...
October 20, 2016: Cancer Research
Filipe Alves Neto Verri, Paulo Roberto Urio, Liang Zhao
The emergence of collective dynamics in neural networks is a mechanism of the animal and human brain for information processing. In this paper, we develop a computational technique using distributed processing elements in a complex network, which are called particles, to solve semisupervised learning problems. Three actions govern the particles' dynamics: generation, walking, and absorption. Labeled vertices generate new particles that compete against rival particles for edge domination. Active particles randomly walk in the network until they are absorbed by either a rival vertex or an edge currently dominated by rival particles...
November 29, 2016: IEEE Transactions on Neural Networks and Learning Systems
Vajiheh Akbarzadeh, Ghina R Mumtaz, Susanne F Awad, Helen A Weiss, Laith J Abu-Raddad
BACKGROUND: Hepatitis C virus (HCV) and HIV are both transmitted through percutaneous exposures among people who inject drugs (PWID). Ecological analyses on global epidemiological data have identified a positive association between HCV and HIV prevalence among PWID. Our objective was to demonstrate how HCV prevalence can be used to predict HIV epidemic potential among PWID. METHODS: Two population-level models were constructed to simulate the evolution of HCV and HIV epidemics among PWID...
December 3, 2016: BMC Public Health
Stuart A Sevier, David A Kessler, Herbert Levine
Over the past several decades it has been increasingly recognized that stochastic processes play a central role in transcription. Although many stochastic effects have been explained, the source of transcriptional bursting (one of the most well-known sources of stochasticity) has continued to evade understanding. Recent results have pointed to mechanical feedback as the source of transcriptional bursting, but a reconciliation of this perspective with preexisting views of transcriptional regulation is lacking...
November 22, 2016: Proceedings of the National Academy of Sciences of the United States of America
Huan Lei, Nathan A Baker, Xiantao Li
We present a data-driven approach to determine the memory kernel and random noise in generalized Langevin equations. To facilitate practical implementations, we parameterize the kernel function in the Laplace domain by a rational function, with coefficients directly linked to the equilibrium statistics of the coarse-grain variables. We show that such an approximation can be constructed to arbitrarily high order and the resulting generalized Langevin dynamics can be embedded in an extended stochastic model without explicit memory...
November 29, 2016: Proceedings of the National Academy of Sciences of the United States of America
Antonia Godoy-Lorite, Roger Guimerà, Cristopher Moore, Marta Sales-Pardo
With increasing amounts of information available, modeling and predicting user preferences-for books or articles, for example-are becoming more important. We present a collaborative filtering model, with an associated scalable algorithm, that makes accurate predictions of users' ratings. Like previous approaches, we assume that there are groups of users and of items and that the rating a user gives an item is determined by their respective group memberships. However, we allow each user and each item to belong simultaneously to mixtures of different groups and, unlike many popular approaches such as matrix factorization, we do not assume that users in each group prefer a single group of items...
November 23, 2016: Proceedings of the National Academy of Sciences of the United States of America
Mehmet Can Uçar, Reinhard Lipowsky
Intracellular transport is performed by molecular motors that pull cargos along cytoskeletal filaments. Many cellular cargos are observed to move bidirectionally, with fast transport in both directions. This behaviour can be understood as a stochastic tug-of-war between two teams of antagonistic motors. The first theoretical model for such a tug-of-war, the Müller-Klumpp-Lipowsky (MKL) model, was based on two simplifying assumptions: (i) both motor teams move with the same velocity in the direction of the stronger team, and (ii) this velocity matching and the associated force balance arise immediately after the rebinding of an unbound motor to the filament...
December 2, 2016: Soft Matter
A Shabbir, G Hornung, G Verdoolaege
We present here an automated classification scheme which is particularly well suited to scenarios where the parameters have significant uncertainties or are stochastic quantities. To this end, the parameters are modeled with probability distributions in a metric space and classification is conducted using the notion of nearest neighbors. The presented framework is then applied to the classification of type I and type III edge-localized modes (ELMs) from a set of carbon-wall plasmas at JET. This provides a fast, standardized classification of ELM types which is expected to significantly reduce the effort of ELM experts in identifying ELM types...
November 2016: Review of Scientific Instruments
Michael W Klymkowsky, Jeremy D Rentsch, Emina Begovic, Melanie M Cooper
Many introductory biology courses amount to superficial surveys of disconnected topics. Often, foundational observations and the concepts derived from them and students' ability to use these ideas appropriately are overlooked, leading to unrealistic expectations and unrecognized learning obstacles. The result can be a focus on memorization at the expense of the development of a meaningful framework within which to consider biological phenomena. About a decade ago, we began a reconsideration of what an introductory course should present to students and the skills they need to master...
2016: CBE Life Sciences Education
K Kuritz, D Stöhr, N Pollak, F Allgöwer
Cyclic processes, in particular the cell cycle, are of great importance in cell biology. Continued improvement in cell population analysis methods like fluorescence microscopy, flow cytometry, CyTOF or single-cell omics made mathematical methods based on ergodic principles a powerful tool in studying these processes. In this paper, we establish the relationship between cell cycle analysis with ergodic principles and age structured population models. To this end, we describe the progression of a single cell through the cell cycle by a stochastic differential equation on a one dimensional manifold in the high dimensional dataspace of cell cycle markers...
November 28, 2016: Journal of Theoretical Biology
Yun-An Yan
Over decades, the theoretical study of the quantum dissipative dynamics was mainly based on the linear dissipation model. The study of the nonlinear dissipative dynamics in condensed phases, where there exist an infinite number of bath modes, is extremely difficult even if not impossible. This work put forward a stochastic scheme for the simulation of the nonlinear dissipative dynamics. In the linear response regime, the second-order cumulant expansion becomes exact to reproduce the effect of the bath on the evolution of the reduced system...
November 28, 2016: Journal of Chemical Physics
Subhradeep Roy, Nicole Abaid
In this work, we study leader-follower consensus and synchronization protocols over a stochastically switching network. The agents representing the followers can communicate with any other agent, whereas the agents serving as leaders are restricted to interact only with the other leaders. The model incorporates the phenomenon of numerosity, which limits the perceptual capacity of the agents while allowing for shuffling with whom each individual interacts at each time step. We derive closed form expressions for necessary and sufficient conditions for consensus, the rate of convergence to consensus, and conditions for stochastic synchronization in terms of the asymptotic convergence factor...
November 2016: Chaos
Xin Yang, Zhenxiang Zeng, Ruidong Wang, Xueshan Sun
This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration of the completion time and the total energy consumption under stochastic processing times. The case study on GM Corporation verifies that the NSGA-II used in this paper is effective and has advantages to solve the proposed model comparing with HPSO and PSO+SA...
2016: PloS One
Isao Yamada
A one-dimensional stochastic model is proposed to analyze the characteristics of quantum noise in flat-panel detectors (FPD) for medical imaging applications. The number of x-ray photons is modeled as a Poisson process, and explicit expressions for the autocorrelation function and noise power spectrum density (NPSD) are obtained in terms of the exposure dose, blur shape in the capture element, and pixel size. The results from the proposed model are validated with numerical simulations, and it is shown that this model can be used for the analysis of the noise properties of the FPD...
December 1, 2016: Journal of the Optical Society of America. A, Optics, Image Science, and Vision
J M Charbois, V Devlaminck
We show the existence of different regimes in spatial evolution of depolarization in turbid media characterized by a diagonal Mueller matrix (pure depolarizer). Experimental results previously published already established the existence of a first regime, where the depolarization follows a parabolic law with the thickness of stationary medium traveled by light. New experiments first confirm the existence of a second regime, which we have previously demonstrated, where the depolarization follows a linear law on a large scale...
December 1, 2016: Journal of the Optical Society of America. A, Optics, Image Science, and Vision
Eran Bendavid, David Stauffer, Eric Remera, Sabin Nsanzimana, Steve Kanters, Edward J Mills
BACKGROUND: HIV is the leading cause of death among adults in sub-Saharan Africa. However, mortality along the HIV care continuum is poorly described. We combine demographic, epidemiologic, and health services data to estimate where are people with HIV dying along Rwanda's care continuum. METHODS: We calibrated an age-structured HIV disease and transmission stochastic simulation model to the epidemic in Rwanda. We estimate mortality among HIV-infected individuals in the following states: untested, tested without establishing care in an antiretroviral therapy (ART) program (unlinked), in care before initiating ART (pre-ART), lost to follow-up (LTFU) following ART initiation, and retained in active ART care...
December 1, 2016: BMC Infectious Diseases
K Storey, M D Ryser, K Leder, J Foo
In this work we explore the temporal dynamics of spatial heterogeneity during the process of tumorigenesis from healthy tissue. We utilize a spatial stochastic model of mutation accumulation and clonal expansion in a structured tissue to describe this process. Under a two-step tumorigenesis model, we first derive estimates of a non-spatial measure of diversity: Simpson's Index, which is the probability that two individuals sampled at random from the population are identical, in the premalignant population. We next analyze two new measures of spatial population heterogeneity...
November 30, 2016: Bulletin of Mathematical Biology
R Hermsen
The spatial range of a species habitat is generally determined by the ability of the species to cope with biotic and abiotic variables that vary in space. Therefore, the species range is itself an evolvable property. Indeed, environmental gradients permit a mode of evolution in which range expansion and adaptation go hand in hand. This process can contribute to rapid evolution of drug resistant bacteria and viruses, because drug concentrations in humans and livestock treated with antibiotics are far from uniform...
November 30, 2016: Physical Biology
Alan Veliz-Cuba, Chinmaya Gupta, Matthew R Bennett, Krešimir Josić, William Ott
We assess the impact of cell cycle noise on gene circuit dynamics. For bistable genetic switches and excitable circuits, we find that transitions between metastable states most likely occur just after cell division and that this concentration effect intensifies in the presence of transcriptional delay. We explain this concentration effect with a three-states stochastic model. For genetic oscillators, we quantify the temporal correlations between daughter cells induced by cell division. Temporal correlations must be captured properly in order to accurately quantify noise sources within gene networks...
November 30, 2016: Physical Biology
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"