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Constraint based modeling

Liliana Ironi, Ettore Lanzarone
Computational and mathematical models have significantly contributed to the rapid progress in the study of gene regulatory networks (GRN), but researchers still lack a reliable model-based framework for computer-aided analysis and design. Such tool should both reveal the relation between network structure and dynamics and find parameter values and/or constraints that enable the simulated dynamics to reproduce specific behaviors. This paper addresses these issues and proposes a computational framework that facilitates network analysis or design...
June 19, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Martin Storath, Dennis Rickert, Michael Unser, Andreas Weinmann
We develop a fast algorithm for segmenting 3D images from linear measurements based on the Potts model (or piecewise constant Mumford-Shah model). To that end, we first derive suitable space discretizations of the 3D Potts model which are capable of dealing with 3D images defined on non-cubic grids. Our discretization allows us to utilize a specific splitting approach which results in decoupled subproblems of moderate size. The crucial point in the 3D setup is that the number of independent subproblems is so large that we can reasonably exploit the parallel processing capabilities of the graphics processing units (GPU)...
June 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Tao Wang, Haibin Ling
Matching-based algorithms have been commonly used in planar object tracking. They often model a planar object as a set of keypoints, and then find correspondences between keypoint sets via descriptor matching. In previous work, unary constraints on appearances or locations are usually used to guide the matching. However, these approaches rarely utilize structure information of the object, and are thus suffering from various perturbation factors. In this paper, we proposed a graph-based tracker, named Gracker, which is able to fully explore the structure information of the object to enhance tracking performance...
June 16, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Tingting Mu, Yannis John Goulermas, Sophia Ananiadou
A typical objective of data visualization is to generate low-dimensional plots that maximally convey the information within the data. The visualization output should help the user to not only identify the local neighborhood structure of individual samples, but also obtain a global view of the relative positioning and separation between cohorts. Here, we propose a very novel visualization framework designed to satisfy these needs. By incorporating additional cohort positioning and discriminative constraints into local neighbor preservation models through the use of computed cohort prototypes, effective control over the arrangements and proximities of data cohorts can be obtained...
June 15, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Mingai Li, Jia Xu, Alberto Algarra Alarcon, Silvia Carlin, Enrico Barbaro, Luca Cappellin, Violeta Velikova, Urska Vrhovsek, Francesco Loreto, Claudio Varotto
Isoprene is the most abundant biogenic volatile hydrocarbon compound naturally emitted by plants and plays a major role in atmospheric chemistry. It has been proposed that isoprene synthases (IspS) may readily evolve from other terpene synthases, but this hypothesis has not been experimentally investigated.We isolated and functionally validated in Arabidopsis the first isoprene synthase gene, AdoIspS, from a monocotyledonous species (Arundo donax L., Poaceae). Phylogenetic reconstruction indicates that AdoIspS and dicots isoprene synthases most likely originated by parallel evolution from TPS-b monoterpene synthases...
June 16, 2017: Molecular Biology and Evolution
Yusuke Azuma, Shuichi Onami
BACKGROUND: Recent advances in bioimaging and automated analysis methods have enabled the large-scale systematic analysis of cellular dynamics during the embryonic development of Caenorhabditis elegans. Most of these analyses have focused on cell lineage tracing rather than cell shape dynamics. Cell shape analysis requires cell membrane segmentation, which is challenging because of insufficient resolution and image quality. This problem is currently solved by complicated segmentation methods requiring laborious and time consuming parameter adjustments...
June 19, 2017: BMC Bioinformatics
Jane H Burridge, Alan Chong W Lee, Ruth Turk, Maria Stokes, Jill Whitall, Ravi Vaidyanathan, Phil Clatworthy, Ann-Marie Hughes, Claire Meagher, Enrico Franco, Lucy Yardley
BACKGROUND AND PURPOSE: Stroke, predominantly a condition of older age, is a major cause of acquired disability in the global population and puts an increasing burden on health care resources. Clear evidence for the importance of intensity of therapy in optimizing functional outcomes is found in animal models, supported by neuroimaging and behavioral research, and strengthened by recent meta-analyses from multiple clinical trials. However, providing intensive therapy using conventional treatment paradigms is expensive and sometimes not feasible because of social and environmental factors...
July 2017: Journal of Neurologic Physical Therapy: JNPT
Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, Bettina Grün
The use of a finite mixture of normal distributions in model-based clustering allows us to capture non-Gaussian data clusters. However, identifying the clusters from the normal components is challenging and in general either achieved by imposing constraints on the model or by using post-processing procedures. Within the Bayesian framework, we propose a different approach based on sparse finite mixtures to achieve identifiability. We specify a hierarchical prior, where the hyperparameters are carefully selected such that they are reflective of the cluster structure aimed at...
April 3, 2017: Journal of Computational and Graphical Statistics
I Bobevski, A Rosen, G Meadows
AIMS: While epidemiological surveys worldwide have found a considerable proportion of people using mental health services not to have a diagnosis of a mental disorder, with possible implications of service overuse, other work has suggested that most people without a current diagnosis who used services exhibited other indicators of need. The aims of the present study were, using somewhat different categorisations than previous work, to investigate whether: (1) Australians without a diagnosis of a mental disorder who used mental health services had other indicators of need; and (2) how rate and frequency of service use in Australia related to level of need, then to discuss the findings in light of recent developments in Australian Mental Health Policy and other epidemiological and services research findings...
June 19, 2017: Epidemiology and Psychiatric Sciences
Xiaofeng Zhu, Heung-Il Suk, Seong-Whan Lee, Dinggang Shen
In this paper, we propose a novel feature selection method by jointly considering (1) 'task-specific' relations between response variables (e.g., clinical labels in this work) and neuroimaging features and (2) 'self-representation' relations among neuroimaging features in a sparse regression framework. Specifically, the task-specific relation is devised to learn the relative importance of features for representation of response variables by a linear combination of the input features in a supervised manner, while the self-representation relation is used to take into account the inherent information among neuroimaging features such that any feature can be represented by a weighted sum of the other features, regardless of the label information, in an unsupervised manner...
June 17, 2017: Brain Imaging and Behavior
Luana Presta, Emanuele Bosi, Leila Mansouri, Lenie Dijkshoorn, Renato Fani, Marco Fondi
Acinetobacter baumannii is a clinical threat to human health, causing major infection outbreaks worldwide. As new drugs against Gram-negative bacteria do not seem to be forthcoming, and due to the microbial capability of acquiring multi-resistance, there is an urgent need for novel therapeutic targets. Here we have derived a list of new potential targets by means of metabolic reconstruction and modelling of A. baumannii ATCC 19606. By integrating constraint-based modelling with gene expression data, we simulated microbial growth in normal and stressful conditions (i...
June 16, 2017: Scientific Reports
Anna Vassall, Mariana Siapka, Nicola Foster, Lucy Cunnama, Lebogang Ramma, Katherine Fielding, Kerrigan McCarthy, Gavin Churchyard, Alison Grant, Edina Sinanovic
BACKGROUND: In 2010 a new diagnostic test for tuberculosis, Xpert MTB/RIF, received a conditional programmatic recommendation from WHO. Several model-based economic evaluations predicted that Xpert would be cost-effective across sub-Saharan Africa. We investigated the cost-effectiveness of Xpert in the real world during national roll-out in South Africa. METHODS: For this real-world cost analysis and economic evaluation, we applied extensive primary cost and patient event data from the XTEND study, a pragmatic trial examining Xpert introduction for people investigated for tuberculosis in 40 primary health facilities (20 clusters) in South Africa enrolled between June 8, and Nov 16, 2012, to estimate the costs and cost per disability-adjusted life-year averted of introducing Xpert as the initial diagnostic test for tuberculosis, compared with sputum smear microscopy (the standard of care)...
July 2017: Lancet Global Health
Tatiana Villacrés, Ana Cristina Mena
Objective: Analyze the proposal by the Ministry of Public Health to reform the public financing model in Ecuador with regard to pooling of funds and payment mechanisms. Method: A literature review was done of the financing model, the current legal framework, and the budgetary bases in Pubmed, SciELO, LILACS Ecuador, and regional LILACS using the key words health financing, health financing systems, capitation, pooling of funds, health system reform Ecuador, health system Ecuador, and health payment mechanisms...
June 8, 2017: Revista Panamericana de Salud Pública, Pan American Journal of Public Health
Chenping Hou, Yuanyuan Jiao, Feiping Nie, Tingjin Luo, Zhi-Hua Zhou
For many image processing and computer vision problems, data points are in matrix form. Traditional methods often convert a matrix to a vector and then use vector based approaches. They will ignore the location of matrix elements and the converted vector often has high dimensionality. How to select features for two dimensional matrix data directly is still an uninvestigated important issue. In this paper, we propose an algorithm named as Sparse Matrix Regression (SMR) for direct feature selection on matrix data...
June 8, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Yan Zhang, Guoqing Xu, Rachel M Lee, Zijie Zhu, Jiandong Wu, Simon Liao, Gong Zhang, Yaohui Sun, Alex Mogilner, Wolfgang Losert, Tingrui Pan, Francis Lin, Zhengping Xu, Min Zhao
When a constraint is removed, confluent cells migrate directionally into the available space. How the migration directionality and speed increase are initiated at the leading edge and propagate into neighboring cells are not well understood. Using a quantitative visualization technique-Particle Image Velocimetry (PIV)-we revealed that migration directionality and speed had strikingly different dynamics. Migration directionality increases as a wave propagating from the leading edge into the cell sheet, while the increase in cell migration speed is maintained only at the leading edge...
June 13, 2017: Cellular and Molecular Life Sciences: CMLS
Dennis Hebbelmann, Momme von Sydow
Causal reasoning is crucial to people's decision making in probabilistic environments. It may rely directly on data about covariation between variables (correspondence) or on inferences based on reasonable constraints if larger causal models are constructed based on local relations (coherence). For causal chains an often assumed constraint is transitivity. For probabilistic causal relations, mismatches between such transitive inferences and direct empirical evidence may lead to distortions of empirical evidence...
June 13, 2017: Cognitive Processing
Michael Öllinger, Albrecht von Müller
Coherence-building is a key concept for a better understanding of the underlying mechanisms of intuition and insight problem solving. There are several accounts that address certain aspects of coherence-building. However, there is still no proper framework defining the general principles of coherence-building. We propose a four-stage model of coherence-building. The first stage starts with spreading activation restricted by constraints. This dynamic is a well-defined rule based process. The second stage is characterized by detecting a coherent state...
2017: Frontiers in Psychology
Borja Esteve-Altava, Toni Vallès-Català, Roger Guimerà, Marta Sales-Pardo, Diego Rasskin-Gutman
Craniosynostosis, the premature fusion of cranial bones, affects the correct development of the skull producing morphological malformations in newborns. To assess the susceptibility of each craniofacial articulation to close prematurely, we used a network model of the skull to quantify the link reliability (an index based on stochastic block models and Bayesian inference) of each articulation. We show that, of the 93 human skull articulations at birth, the few articulations that are associated with non-syndromic craniosynostosis conditions have statistically significant lower reliability scores than the others...
June 13, 2017: Scientific Reports
A M A Maddi, Ch Eslahchi
Detecting known protein complexes and predicting undiscovered protein complexes from protein-protein interaction (PPI) networks help us to understand principles of cell organization and its functions. Nevertheless, the discovery of protein complexes based on experiment still needs to be explored. Therefore, computational methods are useful approaches to overcome the experimental limitations. Nevertheless, extraction of protein complexes from PPI network is often nontrivial. Two major constraints are large amount of noise and ignorance of occurrence time of different interactions in PPI network...
June 12, 2017: Scientific Reports
Xiaoqing Wang, Volkert Roeloffs, Jakob Klosowski, Zhengguo Tan, Dirk Voit, Martin Uecker, Jens Frahm
PURPOSE: To develop a model-based reconstruction technique for single-shot T1 mapping with high spatial resolution, accuracy, and precision using an inversion-recovery (IR) fast low-angle shot (FLASH) acquisition with radial encoding. METHODS: The proposed model-based reconstruction jointly estimates all model parameters, that is, the equilibrium magnetization, steady-state magnetization, 1/ T1*, and all coil sensitivities from the data of a single-shot IR FLASH acquisition with a small golden-angle radial trajectory...
June 11, 2017: Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine
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