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Inferring Regulatory Networks from Time Series Expression Data and Relational Data Via Inductive Logic Programming [chapter]

Irene M. Ong, Scott E. Topper, David Page, Vítor Santos Costa
Lecture Notes in Computer Science  
Following our previous work where we showed that time series gene expression data could potentially uncover causal effects, we describe an application of an inductive logic programming (ILP) system, to  ...  the task of identifying important regulatory relationships from discretized time series gene expression data, protein-protein interaction, protein phosphorylation and transcription factor data about the  ...  Irene Ong is supported by the BACTER institute (DOE-GTL award DE-FG02-04ER25627), support for Scott Topper was provided by the Predoctoral Training Program in Genetics, 5 T32 GM07133 and Vítor Santos Costa  ... 
doi:10.1007/978-3-540-73847-3_34 fatcat:6k5udwbm5bh7loignn5iyrjlti

Computational biology approaches for mapping transcriptional regulatory networks

Violaine Saint-André
2021 Computational and Structural Biotechnology Journal  
Transcriptional Regulatory Networks (TRNs) are mainly responsible for the cell-type or cell-state -specific expression of gene sets from the same DNA sequence.  ...  In this review, major approaches and tools to map TRNs from high-throughput data are presented, depending on the type of methods or data used to infer them, and their advantages and limitations are discussed  ...  It was made using DREM [29, 32] to model gene expression, which is a HMM-based approach to integrate static interaction data with time series gene expression.  ... 
doi:10.1016/j.csbj.2021.08.028 pmid:34522292 pmcid:PMC8426465 fatcat:radqgznjybfo7iey55vjd2ntwm

Eukaryotic gene regulation at equilibrium, or non? [article]

Benjamin Zoller, Thomas Gregor, Gašper Tkačik
2021 arXiv   pre-print
Theory should expand its remit beyond inferring models from data (by fitting), towards identifying non-equilibrium gene regulatory schemes (by optimizing) that may have been evolutionarily selected due  ...  This approach can help us navigate the expanding complexity of regulatory architectures, and refocus the questions about the observed biological mechanisms from how they work towards why they have evolved  ...  GT acknowledges the support of the Austrian Science Fund grant FWF P28844 and the Human Frontiers Science Program.  ... 
arXiv:2110.06214v1 fatcat:pzk4ofirr5eafpzq35bkmgehsu

Network Inference by Combining Biologically Motivated Regulatory Constraints with Penalized Regression

Fabio Parisi, Heinz Koeppl, Felix Naef
2009 Annals of the New York Academy of Sciences  
Reconstructing biomolecular networks from time series mRNA or protein abundance measurements is a central challenge in computational systems biology.  ...  Motivated by the five-gene challenge in the Dialogue for Reverse Engineering Assessments and Methods 2 (DREAM2) contest, we extend and test penalized regression schemes both on data from simulations and  ...  Here, we extend and compare previous penalized regression algorithms (RR and AR) for the reconstruction of genetic networks from time-series data.  ... 
doi:10.1111/j.1749-6632.2008.03751.x pmid:19348637 fatcat:pi73b7qdcvdexbseaix7txph5a

Synthetic Biology in Leishmaniasis: Design,simulation and validation of constructed Genetic circuit [article]

Dixita Limbachiya
2013 arXiv   pre-print
Building circuits and studying their behavior in cells is a major goal of systems and synthetic biology.  ...  To explore the dynamic nature of the circuit designed, simulation was done followed by circuit validation by qualitative and quantitative approaches.  ...  GRENITS and BoolNet are packages of Bioconductor. GRENITS: GRENITS is Gene regulatory network inference using time series data. Network inference using ODE time series data was done using GRENITS.  ... 
arXiv:1304.0342v1 fatcat:ch2ejpnmxvfpxkkwifocv2dlxe

Towards inferring causal gene regulatory networks from single cell expression measurements [article]

Xiaojie Qiu, Arman Rahimzamani, Li Wang, Qi Mao, Timothy Durham, Jose L McFaline-Figueroa, Lauren Saunders, Cole Trapnell, Sreeram Kannan
2018 bioRxiv   pre-print
single-cell data compared to true time series data.  ...  Single-cell transcriptome sequencing now routinely samples thousands of cells, potentially providing enough data to reconstruct causal gene regulatory networks from observational data.  ...  Acknowledgements We thank Robert Waterston and his lab for guidance in analyzing C. elegans early embryogenesis , Gioele La Manno for discussing causal network inference with RNAvelocity, Andysheh Mohajeri  ... 
doi:10.1101/426981 fatcat:em2eeuad6zabrogihvfa6g3ypq

Adapted Boolean network models for extracellular matrix formation

Johannes Wollbold, René Huber, Dirk Pohlers, Dirk Koczan, Reinhard Guthke, Raimund W Kinne, Ulrike Gausmann
2009 BMC Systems Biology  
Experimental gene expression data was obtained from SFB stimulated by TGFβ1 or by TNFα and discretised thereafter.  ...  Due to the rapid data accumulation on pathogenesis and progression of chronic inflammation, there is an increasing demand for approaches to analyse the underlying regulatory networks.  ...  Boolean networks are dynamic models and thus, they require time-series data as input ("reverse engineering") and generate such data as output ("simulation").  ... 
doi:10.1186/1752-0509-3-77 pmid:19622164 pmcid:PMC2734845 fatcat:szgburwsw5b2bacb5wqvq3abcy

Attribute Exploration of Gene Regulatory Processes [article]

Johannes Wollbold
2012 arXiv   pre-print
States, transitions and operators from temporal logics are expressed in the language of Formal Concept Analysis.  ...  This thesis aims at the logical analysis of discrete processes, in particular of such generated by gene regulatory networks.  ...  The data of all time series related to one stimulus was assembled in the transitive contexts (Definition 4.4.1) K obs tt and K sim tt .  ... 
arXiv:1204.1995v1 fatcat:dqymfce6l5caxkao7mm34yuphy

Optimization of logical networks for the modeling of cancer signaling pathways

Sébastien De Landtsheer
2019 Figshare  
PhD thesis about using logical models to infer actionable knowledge about deregulated signaling pathways in cancer  ...  Dr Dagmar Kulms, Greta del Mistro and Dr Thomas Pfau for the fruitful discussions and suggestions on the modeling and analytical pipelines.  ...  Acknowledgments We thank TUD, CRTD, FACS and imaging facilities for support, advice, and technical assistance.  ... 
doi:10.6084/m9.figshare.8191262 fatcat:pnk3svzclbgqxgbcnjd5fokzj4

From Boolean to probabilistic Boolean networks as models of genetic regulatory networks

I. Shmulevich, E.R. Dougherty, Wei Zhang
2002 Proceedings of the IEEE  
The inference of Boolean networks from real gene expression data is considered from the viewpoints of computational learning theory and nonlinear signal processing, touching on computational complexity  ...  Mathematical and computational modeling of genetic regulatory networks promises to uncover the fundamental principles governing biological systems in an integrative and holistic manner.  ...  ACKNOWLEDGMENT The authors would like to acknowledge the following colleagues for many useful discussions and invaluable contributions without which this work would not be possible: S. Kim  ... 
doi:10.1109/jproc.2002.804686 fatcat:zyt4rhnbfrcipjh6vlgruimoza

A Data-Driven Integrative Model of Sepal Primordium Polarity in Arabidopsis

C. La Rota, J. Chopard, P. Das, S. Paindavoine, F. Rozier, E. Farcot, C. Godin, J. Traas, F. Moneger
2011 The Plant Cell  
We constructed a digital atlas of gene expression and used it to build a dynamical molecular regulatory network model of sepal primordium development.  ...  This led to the construction of a coherent molecular network model for lateral organ polarity that fully recapitulates expression and interaction data.  ...  the development of the parameter inference methodology, and all our colleagues from the Reproduction et Dé veloppement des Plantes laboratory for helpful discussions and critical reading of the manuscript  ... 
doi:10.1105/tpc.111.092619 pmid:22198150 pmcid:PMC3269868 fatcat:z5cm4uzznjeonpejidimtfthty

Inferring intracellular signal transduction circuitry from molecular perturbation experiments [article]

Michelle L. Wynn, Megan Egbert, Nikita Consul, Jungsoo Chang, Zhi-Fen Wu, Sofia D. Meravjer, Santiago Schnell
2017 bioRxiv   pre-print
Accurately inferring an intracellular network from data remains a very challenging problem in molecular systems biology.  ...  This phenomenon allows us to introduce a network inference methodology that integrates measurements of protein activation from perturbation experiments.  ...  These and similar algorithms were largely designed to infer gene regulatory logic networks from gene expression data and assume that Boolean networks are subject to deterministic synchronous updating.  ... 
doi:10.1101/107730 fatcat:ry2veanrh5bp5jjase2upvdu7e

Synthesising Executable Gene Regulatory Networks from Single-Cell Gene Expression Data [chapter]

Jasmin Fisher, Ali Sinan Köksal, Nir Piterman, Steven Woodhouse
2015 Lecture Notes in Computer Science  
In this paper we introduce the idea of viewing single-cell gene expression profiles as states of an asynchronous Boolean network, and frame model inference as the problem of reconstructing a Boolean network  ...  We apply our technique to both simulated and real data. We first apply our technique to data simulated from a well established model of common myeloid progenitor differentiation.  ...  Moignard, and A. Wilkinson for sharing with us the biological data, discussing with us its biological significance, and for discussions on the resulting Boolean network, and its meaningfulness.  ... 
doi:10.1007/978-3-319-21690-4_38 fatcat:bup2362ud5ewvjev55kakvsk4u

Parameter inference for asynchronous logical networks using discrete time series

Hannes Klarner, Heike Siebert, Alexander Bockmayr
2011 Proceedings of the 9th International Conference on Computational Methods in Systems Biology - CMSB '11  
Available knowledge about the dynamics of a regulatory network is often limited to a sequence of snapshots in the form of a discrete time series.  ...  This paper is concerned with the dynamics of asynchronous logical models of regulatory networks as introduced by R. Thomas.  ...  In Section 2 we recall the logical framework for regulatory networks and temporal logic. In Section 3 we introduce the notion of discrete time series as an ordered sequence of partial states.  ... 
doi:10.1145/2037509.2037528 dblp:conf/cmsb/KlarnerSB11 fatcat:mh5vpbt63ng5hinpu6qqtvb2by

Systemic modeling myeloma-osteoclast interactions under normoxic/hypoxic condition using a novel computational approach

Zhiwei Ji, Dan Wu, Weiling Zhao, Huiming Peng, Shengjie Zhao, Deshuang Huang, Xiaobo Zhou
2015 Scientific Reports  
developed an Integer Linear Programming approach to infer OC-mediated myeloma cell-specific signaling pathways under normoxic and hypoxic conditions.  ...  cell proliferation by reducing the expression/activation of NF-κB, S6, c-Myc, and c-Jun under normoxic condition; (2) blocked myeloma cell migration and invasion by reducing the expression of FAK and  ...  Acknowledgments We thank Jing Su, Hua Tan, and Ruoying Chen at the Center for Bioinformatics and Systems Biology at Wake Forest School of Medicine to provide valuable discussions.  ... 
doi:10.1038/srep13291 pmid:26282073 pmcid:PMC4539608 fatcat:xbcwziweezbbrmkmjvh3sdhuwy
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