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Computational methods for discovering gene networks from expression data
2009
Briefings in Bioinformatics
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be used to identify modules and subnetworks, thereby reducing complexity and facilitating the generation of testable hypotheses. . ...
We review different kinds of computational methods biologists use to infer networks of varying levels of accuracy and complexity. ...
involved in cell cycle regulation, protein synthesis, catabolism, RNA processing and metabolism. ...
doi:10.1093/bib/bbp028
pmid:19505889
fatcat:l4z4t4pyyjdtdbhotfpenacp3a
Understanding biological functions through molecular networks
2008
Cell Research
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In similar scale networks, probability-based reverse-engineered network model can predict the qualitative instead of quantitative or dynamic outputs of networks [40] . ...
Cell cycle pathways, for example, have been beautifully delineated by yeast genetic analyses. However, no pathway is isolated. ...
doi:10.1038/cr.2008.16
pmid:18227860
fatcat:zskbcrtc6bbphovy344auhn4uu
Toward the dynamic interactome: it's about time
2010
Briefings in Bioinformatics
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Dynamic molecular interactions play a central role in regulating the functioning of cells and organisms. ...
Here we review the beginnings of a new subfield within computational biology, one focused on the global inference and analysis of the dynamic interactome. ...
Acknowledgements This article was inspired by our involvement in the Pacific Symposium on Biocomputing session 'Dynamics of Biological Networks', which we are co-organizing with Tanya Berger-Wolf (University ...
doi:10.1093/bib/bbp057
pmid:20061351
pmcid:PMC2810115
fatcat:xbj7ugs6nbed7guys2ie5z3efa
Network inference and network response identification: moving genome-scale data to the next level of biological discovery
2010
Molecular Biosystems
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Here we review two important steps in this workflow: network inference and network response identification, applied to transcriptional regulatory networks. ...
How can we utilize this deluge of information to better understand biology, cure diseases, or engage cells in bioremediation or biomaterial production for various purposes? ...
Veiga received his education in computer science at the Federal University of Santa Catarina, Brazil. During his undergraduate studies, he worked in the Genomics ...
doi:10.1039/b916989j
pmid:20174676
pmcid:PMC3087299
fatcat:cpk4z5epavgohczyrtpfsv5p64
Reconstructing gene regulatory networks from time-series microarray data
2005
Physica A: Statistical Mechanics and its Applications
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accuracy compared to dynamic Bayesian network. ...
Various computational approaches have been proposed for modeling gene regulatory networks, such as Boolean network, differential equations and Bayesian network. ...
We also compared the performance of dynamic Bayesian network and Bayesian network (R package) using the yeast cell cycle data sets. ...
doi:10.1016/j.physa.2004.11.032
fatcat:aomzan4jwrev5ahewxykccfjie
Reverse Engineering Gene Regulatory Networks by Integrating Multi-Source Biological Data
[chapter]
2012
Reverse Engineering - Recent Advances and Applications
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in number, thus suffering from curse of dimensionality (Wit and McClure 2006) . ...
These inherited properties create significant problems in analysis and interpretation of these data. ...
cell cycle dependent transcription factors in yeast cell cycle dataset. ...
doi:10.5772/33284
fatcat:msmyjh6bsnamxnrjfu3i6eou3q
Reverse engineering of gene regulatory networks
2007
IET Systems Biology
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In this regard, reconstructing gene regulatory networks (GRNs) forms the basis for the dynamical analysis of gene interactions and related effects on cellular control pathways. ...
In particular, the inference methods are classified according to the required input information, and the main idea of each method is elucidated by comparing its advantages and disadvantages with respect ...
[51] have constructed a Bayesian network structure using BNT and unravelled a transcriptional regulatory pathway through parameter learning. Kim et al. ...
doi:10.1049/iet-syb:20060075
pmid:17591174
fatcat:cdwoq3udmndalmd5yluxy4dx5y
Molecular Networks – Representation and Analysis
[chapter]
2014
Springer Handbook of Bio-/Neuroinformatics
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In particular, we review the study of transcriptional regulatory networks in prokaryotes and of protein interaction networks in human as prime examples for network-orientated approaches to complex systems ...
In fact, many insights into molecular networks and their functioning have been gained by the study of transcriptional regulation in prokaryotes. ...
(ii) Reverse engineering: Recently, reverse engineering has become an promising alternative given the rapid increase of available expression data. ...
doi:10.1007/978-3-642-30574-0_24
fatcat:lpiq5asj3rbfnezomasboptwu4
Systems-level insights into cellular regulation: inferring, analysing, and modelling intracellular networks
2007
IET Systems Biology
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Graph-theoretical measures and network models are more and more frequently used to discern functional and evolutionary constraints in the organisation of biological networks. ...
analysis of these networks, and the extension of static networks into various dynamic models capable of providing a new layer of insight into the functioning of cellular systems is discussed. ...
in a cell), metabolome (all the metabolites in a cell), and interactome (the totality of protein interactions). ...
doi:10.1049/iet-syb:20060071
pmid:17441550
fatcat:ttoq55gpxzaszbmjvctrtcitqe
A Glimpse to Background and Characteristics of Major Molecular Biological Networks
2015
BioMed Research International
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These huge datasets have paved the way for system-level analysis of the processes and subprocesses of the cell. ...
In this review, we briefly discuss both the biological background and topological properties of major types of omics networks to facilitate a comprehensive understanding and to conceptualize the foundation ...
Acknowledgments This work is partly supported by the National Bioscience Database Center in Japan and NAIST Big Data Project. ...
doi:10.1155/2015/540297
pmid:26491677
pmcid:PMC4605226
fatcat:lwzn2z7nzrh7np6at6twisrvem
Discovering functions and revealing mechanisms at molecular level from biological networks
2007
Proteomics
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The contents of the survey cover global topological properties and local structural characteristics, network motifs, network comparison and query, detection of functional modules and network motifs, function ...
With the increasingly accumulated data from high-throughput technologies, study on biomolecular networks has become one of key focuses in systems biology and bioinformatics. ...
As an important challenging problem of reverse engineering, a variety of models have been developed for this problem, such as the simple Boolean network model and dynamic Bayesian network model [100, ...
doi:10.1002/pmic.200700095
pmid:17703505
fatcat:spdclsqf4rdjxkxa7sts4c5u6q
Principles and Strategies for Developing Network Models in Cancer
2011
Cell
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For example, Bayesian networks were used to reconstruct detailed signaling pathway structures in human T cells using only the concentration of phosphoproteins simultaneously measured in individual cells ...
In the end, a "good" model of biological networks should be able to predict the behavior of the network under different conditions and perturbations and, ideally, even help us to engineer a desired response ...
D.P. holds a Career Award at the Scientific Interface from the Burroughs Wellcome Fund and Packard Fellowship for Science and Engineering. ...
doi:10.1016/j.cell.2011.03.001
pmid:21414479
pmcid:PMC3082135
fatcat:pfb4lxzgdzh5fjcd75uk5yyaui
Maps for when the living gets tough: Maneuvering through a hostile energy landscape
2016
IFAC-PapersOnLine
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This work has implications for the co-optimization of transcriptional and allosteric regulatory systems in metabolic networks and provides a framework for the design of allosteric regulation in engineered ...
Examples on the control of gene expression in yeast and mammalian cells will be shown. ...
doi:10.1016/j.ifacol.2017.03.002
fatcat:tmddfevk7ngd3p4wdpbq7xisb4
Separating the Drivers from the Driven: Integrative Network and Pathway Approaches Aid Identification of Disease Biomarkers from High-Throughput Data
2010
Disease Markers
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We provide a summary of some of the recent work in this area, focusing on how the integration of different kinds of complementary data, and analysis of biological networks and pathways can lead to discovery ...
of robust, specific and useful biomarkers of disease and how these methods can help shed light on the mechanisms and etiology of the diseases being studied. ...
The dialogue for reverse engineering assessments and methods (DREAM) provides a forum for evaluation of methods for inference of networks from HT data [74] . ...
doi:10.1155/2010/708932
pmid:20534910
pmcid:PMC3833603
fatcat:3cjkhyhzzfg5rfah4tadwqfw4y
Structure and dynamics of molecular networks: A novel paradigm of drug discovery
2013
Pharmacology and Therapeutics
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We give a comprehensive assessment of the analytical tools of network topology and dynamics. ...
The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. ...
Wang (Department of Biological Statistics and Computational Biology, Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca NY, USA) and Balázs Papp (Szeged Biological Centre, Hungarian ...
doi:10.1016/j.pharmthera.2013.01.016
pmid:23384594
pmcid:PMC3647006
fatcat:osjkz6kpr5gzxomqlyenla2fvq
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