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Efficient Reverse-Engineering of a Developmental Gene Regulatory Network

Anton Crombach, Karl R. Wotton, Damjan Cicin-Sain, Maksat Ashyraliyev, Johannes Jaeger, Satoru Miyano
2012 PLoS Computational Biology  
Computational models can be used as tools to extract the regulatory structure and dynamics of such networks from gene expression data. This approach is called reverse engineering.  ...  Only the quantitative investigation of a large number of developmental gene regulatory networks will allow us to discover whether there are rules or regularities governing development and evolution of  ...  We thank Hilde Janssens for double-checking time classification of embryos.  ... 
doi:10.1371/journal.pcbi.1002589 pmid:22807664 pmcid:PMC3395622 fatcat:tahnowoh4navtpbwiiyssnglbu

Can biological complexity be reverse engineered?

Sara Green
2015 Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences  
I clarify how the notion of design principles can be more broadly conceived and argue that reverse engineering is compatible with a dynamic view of organisms.  ...  The diachronic underdetermination problem regards the problem of reverse engineering a system when the non-linear relations between system capacities and lower-level mechanisms are changing over time.  ...  The authors raise the possibility that design principles inferred in reverse engineering studies may reflect methodological biases rather than inherent features of the system: 'in the possible Acknowledgements  ... 
doi:10.1016/j.shpsc.2015.03.008 pmid:25903121 fatcat:27csshqk5zaxjh7nvjqkg52isu

SJARACNe: a scalable software tool for gene network reverse engineering from big data

Alireza Khatamian, Evan O Paull, Andrea Califano, Jiyang Yu, Jonathan Wren
2018 Bioinformatics  
resources to efficiently construct complex regulatory and signaling networks from thousands of gene expression profiles.  ...  Reverse engineering of biological networks from high-throughput gene expression profiles has been one of the grand challenges in systems biology.  ...  Conflict of Interest: Dr Califano is founder, equity holder, consultant and director of DarwinHealth Inc., a company that has licensed some of the algorithms used in this manuscript from Columbia University  ... 
doi:10.1093/bioinformatics/bty907 pmid:30388204 pmcid:PMC6581437 fatcat:tj6v6idlg5e7xis65mamgb3q5y

KELLER: estimating time-varying interactions between genes

L. Song, M. Kolar, E. P. Xing
2009 Bioinformatics  
Results: We introduce a kernel-reweighted logistic regression method (KELLER) for reverse engineering the dynamic interactions between genes based on their time series of expression values.  ...  Our results offer the first glimpse into the temporal evolution of gene networks in a living organism during its full developmental course.  ...  Conflict of Interest: none declared.  ... 
doi:10.1093/bioinformatics/btp192 pmid:19477978 pmcid:PMC2687946 fatcat:d6jwn657bvaivck6yg2uzrj3hm

Evo-Devo in the Era of Gene Regulatory Networks

A. H. L. Fischer, J. Smith
2012 Integrative and Comparative Biology  
This requires a capacity to go deep and broad, to analyze developmental gene regulatory networks in many organisms, especially nontraditional models.  ...  As we usher in a new era of next-generation GRN (gene regulatory network) analysis, it is important to ask how to evaluate the evolution of network interactions.  ...  Funding The author was supported by National Institutes of Health (5P30GM092374-02).  ... 
doi:10.1093/icb/ics112 pmid:22927135 pmcid:PMC3501101 fatcat:vgkpgbhs6fhm5iclb2ectmy6vu

Modeling transcriptional regulatory networks

Hamid Bolouri, Eric H. Davidson
2002 Bioessays  
The code specifies the gene regulatory networks (GRNs) that underlie all major developmental events.  ...  Developmental processes in complex animals are directed by a hardwired genomic regulatory code, the ultimate function of which is to set up a progression of transcriptional regulatory states in space and  ...  Mark Borisuk, Brian Ingalls, Herbert Sauro, Maria Schilstra, Denis Thieffry, Olaf Wolkenhauer, Adam Wilkins and Tau Mu Yi for helpful discussion and comments on early drafts of this manuscript.  ... 
doi:10.1002/bies.10189 pmid:12447977 fatcat:f6vlewhnxzgntmp7qcfm5xdmii

Gene network analysis: from heart development to cardiac therapy

Riccardo Bellazzi, Felix Engel, Fulvia Ferrazzi
2015 Thrombosis and Haemostasis  
In particular gene networks inferred from expression data can support the identification of novel hypotheses on regulatory processes.  ...  Collectively, our literature-based analysis indicates that gene network analysis constitutes a promising opportunity to infer therapy-relevant regulatory processes in heart development.  ...  A prototype approach to reverse engineer Boolean models from gene expression data is the algorithm REVEAL (REVerse Engineering ALgorithm) (41) .  ... 
doi:10.1160/th14-06-0483 pmid:25231088 fatcat:wj4acrws5jcibkhxt4zojwv7fy

DeGNServer: Deciphering Genome-Scale Gene Networks through High Performance Reverse Engineering Analysis

Jun Li, Hairong Wei, Patrick Xuechun Zhao
2013 BioMed Research International  
We developed a high performance web server, DeGNServer, to reverse engineering and decipher genome-scale networks.  ...  Analysis of genome-scale gene networks (GNs) using large-scale gene expression data provides unprecedented opportunities to uncover gene interactions and regulatory networks involved in various biological  ...  Therefore it is urgently called to develop a high performance reverse engineering system for large-scale gene network analysis through both innovations in efficient algorithm development and parallel computing  ... 
doi:10.1155/2013/856325 pmid:24328032 pmcid:PMC3847961 fatcat:3d2xpzav5jfa5fcmu6kcdx3piu

Gene regulatory network models for plant development

E ALVAREZBUYLLA, M BENITEZ, E DAVILA, A CHAOS, C ESPINOSASOTO, P PADILLALONGORIA
2007 Current opinion in plant biology  
Financial support in the form of grants to EAB was from PAPIIT (Programa de Apoyo a Proyectos de Investigació n e Innovación Tecnoló gica), UNAM (Universidad Nacional Autó noma de Mé xico; IN 230002, IN212995  ...  Acknowledgements We apologize to authors whose work has not been cited because of limited space.  ...  Efficient reverse engineering of GRN architectures depends on collecting data that guarantee a wide exploration of perturbation conditions [11] or phenotypic variations of a cell type [12 ] , so that  ... 
doi:10.1016/j.pbi.2006.11.008 pmid:17142086 fatcat:vqp5bpld4jcrhlmsebgyuyeqde

Understanding transcriptional regulatory networks using computational models

Bing He, Kai Tan
2016 Current Opinion in Genetics and Development  
Transcriptional regulatory networks (TRNs) encode instructions for animal development and physiological responses.  ...  Recent advances in genomic technologies and computational modeling have revolutionized our ability to construct models of TRNs.  ...  Acknowledgments B.H. was supported by National Institutes of Health grants HG006130. K.T. was supported by National Institutes of Health grants HG006130, GM104369, GM108716.  ... 
doi:10.1016/j.gde.2016.02.002 pmid:26950762 pmcid:PMC4943455 fatcat:zegj265jhffcrhznlbgefbdnre

Reverse-engineering of gene networks for regulating early blood development from single-cell measurements

Jiangyong Wei, Xiaohua Hu, Xiufen Zou, Tianhai Tian
2017 BMC Medical Genomics  
A graphic model is constructed for a regulatory network with forty genes and a dynamic model using differential equations is developed for a network of nine genes.  ...  Conclusion: The research results in this work shows that the developed approach is an efficient and effective method to reverse-engineer gene networks using single-cell experimental observations.  ...  Funding T.T. is supported by the Australian Research Council (ARC) Discovery Projects (DP120104460) which supports the publication cost of this paper. 1  ... 
doi:10.1186/s12920-017-0312-z pmid:29297370 pmcid:PMC5751697 fatcat:svftwclanfcozbv4vos2yzsqem

How Difficult Is Inference of Mammalian Causal Gene Regulatory Networks?

Djordje Djordjevic, Andrian Yang, Armella Zadoorian, Kevin Rungrugeecharoen, Joshua W. K. Ho, Frank Emmert-Streib
2014 PLoS ONE  
Gene regulatory networks (GRNs) play a central role in systems biology, especially in the study of mammalian organ development.  ...  Furthermore, we showed that causal gene regulatory relationship can be highly cell type or developmental stage specific, suggesting the importance of employing expression profiles from homogeneous cell  ...  A fundamental question arises, 'Can we reverse engineer mammalian developmental causal GRNs from a collection of gene expression profiles?'.  ... 
doi:10.1371/journal.pone.0111661 pmid:25369032 pmcid:PMC4219746 fatcat:q2lcsoz53bgndme4w2d2k7p2wq

Reverse Engineering: A Key Component of Systems Biology to Unravel Global Abiotic Stress Cross-Talk

Swetlana Friedel, Björn Usadel, Nicolaus von Wirén, Nese Sreenivasulu
2012 Frontiers in Plant Science  
In this review article, we discuss the recent advances of reverse engineering approaches that led to seminal discoveries of key candidate regulatory genes involved in cross-talk of abiotic stress responses  ...  and summarized the available tools of reverse engineering and its relevant application.  ...  In the case of microarray data it can be employed to reverse engineer a molecular regulatory network GeneReg Linear model fitting GeneReg is used to reconstruct time-course gene regulatory network.  ... 
doi:10.3389/fpls.2012.00294 pmid:23293646 pmcid:PMC3533172 fatcat:hhqvotht6jdnbpuwayxljdd5ya

TIGERi: modeling and visualizing the responses to perturbation of a transcription factor network

Namshik Han, Harry A. Noyes, Andy Brass
2017 BMC Bioinformatics  
Much progress has been made on understanding and reverse-engineering TF network topologies using a range of experimental and theoretical methodologies.  ...  Transcription factor (TF) networks play a key role in controlling the transfer of genetic information from gene to mRNA.  ...  Reverse-engineering of TF network and TFBS information A number of techniques are available to uncover the topology of the TF network-the networks of complex reactions and interactions in the cell that  ... 
doi:10.1186/s12859-017-1636-6 pmid:28617232 pmcid:PMC5471961 fatcat:4rgw2t2whvepdceo5cwpyi5e7e

Human brain evolution, theories of innovation, and lessons from the history of technology

Alfred Gierer
2004 Journal of Biosciences  
of regulatory proteins, leading to the developmental regulation of gene expression.  ...  This is one of the mechanisms of growth cone navigation that insures that a limited set of genes can organize network formation for a much larger number of fibers to a first approximation.  ... 
doi:10.1007/bf02702606 pmid:15381845 fatcat:dn5gci2f6jc3rm2asem5qdxaxu
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