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network inference

Adrien Rougny, Pauline Gloaguen, Nathalie Langonné, Eric Reiter, Pascale Crépieux, Anne Poupon, Christine Froidevaux
With the dramatic increase of the diversity and the sheer quantity of biological data generated, the construction of comprehensive signaling networks that include precise mechanisms cannot be carried out manually anymore. In this context, we propose a logic-based method that allows building large signaling networks automatically. Our method is based on a set of expert rules that make explicit the reasoning made by biologists when interpreting experimental results coming from a wide variety of experiment types...
May 18, 2018: Scientific Reports
Zachary P Kilpatrick
Information from preceding trials of cognitive tasks can bias performance in the current trial, a phenomenon referred to as interference. Subjects performing visual working memory tasks exhibit interference in their responses: the recalled target location is biased in the direction of the target presented on the previous trial. We present modeling work that develops a probabilistic inference model of this history-dependent bias, and links our probabilistic model to computations of a recurrent network wherein short-term facilitation accounts for the observed bias...
May 18, 2018: Scientific Reports
Paula J Griffin, Yuqing Zhang, William Evan Johnson, Eric D Kolaczyk
Cellular mechanism-of-action is of fundamental concern in many biological studies. It is of particular interest for identifying the cause of disease and learning the way in which treatments act against disease. However, pinpointing such mechanisms is difficult, due to the fact that small perturbations to the cell can have wide-ranging downstream effects. Given a snapshot of cellular activity, it can be challenging to tell where a disturbance originated. The presence of an ever-greater variety of high-throughput biological data offers an opportunity to examine cellular behavior from multiple angles, but also presents the statistical challenge of how to effectively analyze data from multiple sources...
May 17, 2018: Biometrics
David Hallac, Youngsuk Park, Stephen Boyd, Jure Leskovec
Many important problems can be modeled as a system of interconnected entities, where each entity is recording time-dependent observations or measurements. In order to spot trends, detect anomalies, and interpret the temporal dynamics of such data, it is essential to understand the relationships between the different entities and how these relationships evolve over time. In this paper, we introduce the time-varying graphical lasso (TVGL) , a method of inferring time-varying networks from raw time series data...
August 2017: KDD: Proceedings
Mingzhe Zhu, Qianlei Wang, Wenjun Zhou, Tao Liu, Lili Yang, Peiyong Zheng, Li Zhang, Guang Ji
To enhance our understanding of molecular mechanisms and mine novel biomarkers of non-alcoholic fatty liver disease (NAFLD), RNA sequencing was performed to gain hepatic expression profiles of mRNAs and miRNAs in NAFLD and normal rats. Using DESeq with thresholds of a two-fold change and a false discovery rate (FDR) less than 0.05, 336 mRNAs and 21 miRNAs were identified as differentially expressed. Among those, 17 miRNAs (e.g., miR-144-3p, miR-99a-3p, miR-200b-3p, miR-200b-5p, miR-200c-3p, etc.) might serve as novel biomarkers of NAFLD...
May 16, 2018: Scientific Reports
Kranthi Varala, Amy Marshall-Colón, Jacopo Cirrone, Matthew D Brooks, Angelo V Pasquino, Sophie Léran, Shipra Mittal, Tara M Rock, Molly B Edwards, Grace J Kim, Sandrine Ruffel, W Richard McCombie, Dennis Shasha, Gloria M Coruzzi
This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our "just-in-time" analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes. We experimentally determined a network precision cutoff, using TF-regulated genome-wide targets of three TF hubs (CRF4, SNZ, and CDF1), used to "prune" the network to 155 TFs and 608 targets...
May 16, 2018: Proceedings of the National Academy of Sciences of the United States of America
Kevin Faust, Quin Xie, Dominick Han, Kartikay Goyle, Zoya Volynskaya, Ugljesa Djuric, Phedias Diamandis
BACKGROUND: There is growing interest in utilizing artificial intelligence, and particularly deep learning, for computer vision in histopathology. While accumulating studies highlight expert-level performance of convolutional neural networks (CNNs) on focused classification tasks, most studies rely on probability distribution scores with empirically defined cutoff values based on post-hoc analysis. More generalizable tools that allow humans to visualize histology-based deep learning inferences and decision making are scarce...
May 16, 2018: BMC Bioinformatics
C Caranica, A Al-Omari, Z Deng, J Griffith, R Nilsen, L Mao, J Arnold, H-B Schüttler
A major challenge in systems biology is to infer the parameters of regulatory networks that operate in a noisy environment, such as in a single cell. In a stochastic regime it is hard to distinguish noise from the real signal and to infer the noise contribution to the dynamical behavior. When the genetic network displays oscillatory dynamics, it is even harder to infer the parameters that produce the oscillations. To address this issue we introduce a new estimation method built on a combination of stochastic simulations, mass action kinetics and ensemble network simulations in which we match the average periodogram and phase of the model to that of the data...
2018: PloS One
Jiyang Yu, Jose M Silva
The Connectivity Map (CMAP) project profiled human cancer cell lines exposed to a library of anticancer compounds with the goal of connecting cancer with underlying genes and potential treatments. As most targeted anticancer therapeutics aim to induce tumor-selective apoptosis, it is critical to understand the specific cell death pathways triggered by drugs. This can help to better understand the mechanism of how cancer cells respond to chemical stimulations and improve the treatment of human tumors. In this study, using Connectivity MAP microarray-based gene expression data, we applied a Bayesian network modeling approach and identified apoptosis as a major drug-induced cellular pathway...
2018: Methods in Molecular Biology
D Okada, S Endo, H Matsuda, S Ogawa, Y Taniguchi, T Katsuta, T Watanabe, H Iwaisaki
Genome-wide association studies (GWAS) of quantitative traits have detected numerous genetic associations, but they encounter difficulties in pinpointing prominent candidate genes and inferring gene networks. The present study used a systems genetics approach integrating GWAS results with external RNA-expression data to detect candidate gene networks in feed utilization and growth traits of Japanese Black cattle, which are matters of concern. A SNP co-association network was derived from significant correlations between SNPs with effects estimated by GWAS across seven phenotypic traits...
May 12, 2018: Journal of Animal Science
Yongjiu Feng, Qianqian Yang, Xiaohua Tong, Lijuan Chen
Land ecological security (LES) refers to the environmental health and sustainability of the land resources and ecosystems, which are substantially affected by biophysical and socio-economic factors. We assess the spatiotemporal patterns of LES in Ningbo city on the southeast coast of China from 1975 to 2015 and explore the effects of driving factors. Expert evaluation is used to estimate the LES score for each 2×2km grid and map the patterns by Kriging. Five levels of LES are used: very secure, secure, neutral, insecure and very insecure...
August 15, 2018: Science of the Total Environment
Takumi Matsumoto, Takahiro Sagawa
A sufficient statistic is a significant concept in statistics, which means a probability variable that has sufficient information required for an inference task. We investigate the roles of sufficient statistics and related quantities in stochastic thermodynamics. Specifically, we prove that for general continuous-time bipartite networks, the existence of a sufficient statistic implies that an informational quantity called the sensory capacity takes the maximum. Since the maximal sensory capacity imposes a constraint that the energetic efficiency cannot exceed one-half, our result implies that the existence of a sufficient statistic is inevitably accompanied by energetic dissipation...
April 2018: Physical Review. E
Duc-Hau Le, Lan T M Dao
Recently, many long non-coding RNAs (lncRNAs) have been identified and their biological function has been characterized; however, our understanding of their underlying molecular mechanisms related to disease is still limited. To overcome the limitation in experimentally identifying disease-lncRNA associations, computational methods have been proposed as a powerful tool to predict such associations. These methods are usually based on the similarities between diseases or lncRNAs since it was reported that similar diseases are associated with functionally similar lncRNAs...
May 11, 2018: Journal of Molecular Biology
William W Macfarlane, Jordan T Gilbert, Joshua D Gilbert, William C Saunders, Nate Hough-Snee, Chalese Hafen, Joseph M Wheaton, Stephen N Bennett
Environmental stressors associated with human land and water-use activities have degraded many riparian ecosystems across the western United States. These stressors include (i) the widespread expansion of invasive plant species that displace native vegetation and exacerbate streamflow and sediment regime alteration; (ii) agricultural and urban development in valley bottoms that decouple streams and rivers from their floodplains and reduce instream wood recruitment and retention; and (iii) flow modification that reduces water quantity and quality, degrading aquatic habitats...
May 11, 2018: Environmental Management
P Hima Kumari, S Anil Kumar, Katam Ramesh, Palakolanu Sudhakar Reddy, M Nagaraju, A Bhanu Prakash, Trushar Shah, Ashley Henderson, Rakesh K Srivastava, G Rajasheker, A Chitikineni, Rajeev K Varshney, P Rathnagiri, M Lakshmi Narasu, P B Kavi Kishor
Na⁺ transporters play an important role during salt stress and development. The present study is aimed at genome-wide identification, in silico analysis of sodium-proton antiporter (NHX) and sodium-proton exchanger (NHE)-type transporters in Sorghum bicolor and their expression patterns under varied abiotic stress conditions. In Sorghum , seven NHX and nine NHE homologs were identified. Amiloride (a known inhibitor of Na⁺/H⁺ exchanger activity) binding motif was noticed in both types of the transporters...
May 3, 2018: Genes
Kerry Geiler-Samerotte, Federica M O Sartori, Mark L Siegal
The concept of genetic canalization has had an abiding influence on views of complex-trait evolution. A genetically canalized system has evolved to become less sensitive to the effects of mutation. When a gene product that supports canalization is compromised, the phenotypic impacts of a mutation should be more pronounced. This expected increase in mutational effects not only has important consequences for evolution, but has also motivated strategies to treat disease. However, recent studies demonstrate that, when putative agents of genetic canalization are impaired, systems do not behave as expected...
May 8, 2018: Seminars in Cell & Developmental Biology
Chuanlei Liu, Weihua Zhang, Kurt Ungar, Ed Korpach, Brian White, Mike Benotto, Eric Pellerin
This work explores the application of Health Canada's Fixed Point Surveillance (FPS) network for cosmic ray monitoring and dose estimation purposes. This network is comprised of RS250 3 inch by 3 inch Sodium Iodide (NaI) spectroscopic dosimeters distributed throughout Canada. The RS250's high channel count rate responds to the electromagnetic and muonic components of cosmic ray shower. These count rates are used to infer cosmic ray doses throughout FPS locations. The derived dose was found to have an accuracy within 6...
May 7, 2018: Journal of Environmental Radioactivity
Giles L Colclough, Mark W Woolrich, Samuel J Harrison, Pedro A Rojas López, Pedro A Valdes-Sosa, Stephen M Smith
A Bayesian model for sparse, hierarchical inverse covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fmri, meg and eeg data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions...
May 7, 2018: NeuroImage
Mathias Foo, Iulia Gherman, Peijun Zhang, Declan G Bates, Katherine Denby
Crop disease leads to significant waste world-wide, both pre- and post-harvest, with subsequent economic and sustainability consequences. Disease outcome is determined both by the plants' response to the pathogen and by the ability of the pathogen to suppress defense responses and manipulate the plant to enhance colonization. The defense response of a plant is characterized by significant transcriptional reprogramming mediated by underlying gene regulatory networks and components of these networks are often targeted by attacking pathogens...
May 10, 2018: ACS Synthetic Biology
Kai Chen, Hai Yan Yu, Ji Wei Zhang, Bei Xin Wang, Qiu Wen Chen
Improving the stability of integrity of biotic index (IBI; i.e., multi-metric indices, MMI) across temporal and spatial scales is one of the most important issues in water ecosystem integrity bioassessment and water environment management. Using datasets of field-based macroinvertebrate and physicochemical variables and GIS-based natural predictors (e.g., geomorphology and climate) and land use variables collected at 227 river sites from 2004 to 2011 across the Zhejiang Province, China, we used random forests (RF) to adjust the effects of natural variations at temporal and spatial scales on macroinvertebrate metrics...
June 18, 2017: Ying Yong Sheng Tai Xue Bao, the Journal of Applied Ecology
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