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Modelling gene and protein regulatory networks with Answer Set Programming

Timur Fayruzov, Jeroen Janssen, Dirk Vermeir, Chris Cornelis, Martine De Cock
2011 International Journal of Data Mining and Bioinformatics  
In this paper we propose an answer set programming (ASP) based approach to model interaction networks.  ...  We build a general ASP framework that describes the network semantics and allows to model specific networks with little effort.  ...  Conclusions and future work In this paper, we have proposed a modelling and simulation tool for gene and protein regulatory networks based on answer set programming.  ... 
doi:10.1504/ijdmb.2011.039178 pmid:21544955 fatcat:beo22vcca5gjpbs5nkg2jqdmry

Extending boolean regulatory network models with answer set programming

Timur Fayruzov, Jeroen Janssen, Chris Cornelis, Dirk Vermeir, Martine De Cock
2010 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)  
In this paper we develop an answer set programming (ASP) framework that supports threshold boolean network semantics and extends it with the capability to model meta interactions.  ...  Because of their simplicity, boolean networks are a popular formalism to model gene regulatory networks.  ...  In particular, we propose to represent gene and protein regulatory networks by answer set programs, as an extension of our previous work presented in [4] .  ... 
doi:10.1109/bibmw.2010.5703800 fatcat:z4hqjoscvbd7xiwkloj3wx47we

Learning Regulatory Programs That Accurately Predict Differential Expression with MEDUSA

A. KUNDAJE, S. LIANOGLOU, X. LI, D. QUIGLEY, M. ARIAS, C. H. WIGGINS, L. ZHANG, C. LESLIE
2007 Annals of the New York Academy of Sciences  
MEDUSA integrates promoter sequence, mRNA expression, and transcription factor occupancy data to learn gene regulatory programs that predict the differential expression of target genes.  ...  Inferring gene regulatory networks from high-throughput genomic data is one of the central problems in computational biology and a principal focus of the DREAM initiative.  ...  We present algorithmic methods for learning and interpreting predictive models of gene regulation, which we call "regulatory programs".  ... 
doi:10.1196/annals.1407.020 pmid:17934055 fatcat:ccmlsydlgrcfjnz2xaawxf5mvm

Learning module networks from genome-wide location and expression data

Xiaojiang Xu, Lianshui Wang, Dafu Ding
2004 FEBS Letters  
We develop a systematic algorithm for discovering network of regulatory modules, which identifies regulatory modules and their regulation program by integrating genome-wide location and expression data  ...  Previous work identified regulatory modules from genomewide expression data by clustering [2] and the model of module networks [4] .  ...  Friedman and his co-workers constructed a probabilistic model that use expression data to link genes with their regulators [4, 8, 9] .  ... 
doi:10.1016/j.febslet.2004.11.019 pmid:15589836 fatcat:umqjnszbsff7ledilf4r5id34e

CytoASP: a Cytoscape app for qualitative consistency reasoning, prediction and repair in biological networks

Aristotelis Kittas, Amélie Barozet, Jekaterina Sereshti, Niels Grabe, Sophia Tsoka
2015 BMC Systems Biology  
It allows easy integration of qualitative modelling, combining the functionality of BioASP with the visualisation and processing capability in Cytoscape, and thereby greatly simplifying qualitative network  ...  We demonstrate its usage in a case study of a yeast genetic network, and highlight its capabilities in reasoning over regulatory networks.  ...  The BioASP software collection 1 implements methods for modelling metabolic and gene regulatory networks [3] , using logical rules with Answer Set Programming (ASP) [4] .  ... 
doi:10.1186/s12918-015-0179-6 pmid:26163265 pmcid:PMC4499222 fatcat:dj2jhvwgrvcifamqb7j37gfeoi

Genome-wide analysis of the context-dependence of regulatory networks

Balázs Papp, Stephen Oliver
2005 Genome Biology  
Genome-wide analytical tools are now allowing the discovery of the design rules that govern regulatory networks.  ...  Two recent studies in yeast have helped reveal the relatively small number of transcription-factor control strategies that cells employ to maximize their regulatory options using only a small number of  ...  What are the main functional differences between the underlying regulatory networks of the endogenous (developmental) and exogenous (sensory) gene-expression programs?  ... 
doi:10.1186/gb-2005-6-2-206 pmid:15693953 pmcid:PMC551525 fatcat:jzwgzninrndzzpyjiqcovjs7me

Introduction to Network Analysis in Systems Biology

A. Ma'ayan
2011 Science Signaling  
This Teaching Resource provides lecture notes, slides, and a problem set for a set of three lectures from a course entitled "Systems Biology: Biomedical Modeling."  ...  The first lecture describes different types of intracellular networks, methods for constructing biological networks, and different types of graphs used to represent regulatory intracellular networks.  ...  Familiarity with the following programs is also required for the problem set: Cytoscape, Pajek, Genes2Networks, and FANMOD.  ... 
doi:10.1126/scisignal.2001965 pmid:21917719 pmcid:PMC3196357 fatcat:uohhuzayo5cftkyapp3sueglui

Unanswered Questions in Bioinformatics

Mohankumara J. Megh
2013 Journal of Proteomics & Bioinformatics  
Few other questions include: How the gene regulatory networks exactly work? Can we model these networks and simulate the biological pathways?  ...  Another set of challenges include, understanding how speciation occurs at molecular level, knowing how gene network regulates to form organs out of embryo, variation of gene regulatory network in different  ... 
doi:10.4172/jpb.1000257 fatcat:sn7a53ptlzbidpqelchpuienku

Modularity and Dynamics of Cellular Networks

Yuan Qi, Hui Ge
2006 PLoS Computational Biology  
Traditionally, focus has been given to the characterization of individual genes/proteins or individual interactions during cellular events.  ...  We review the recent progress on analyzing the architecture and dynamics of cellular networks. We also summarize how computational modeling yields insight about cell signaling pathways.  ...  Vyas, and J. Zhang for critical reading of the manuscript. We also thank two anonymous reviewers for their invaluable inputs. We thank T. S. Jaakkola and D. K. Gifford for their support.  ... 
doi:10.1371/journal.pcbi.0020174 pmid:17196032 pmcid:PMC1761653 fatcat:lbh3p667kbhubegexlnfmglw24

Towards Using Probabilities and Logic to Model Regulatory Networks

Antonio Goncalves, Irene Ong, Jeffrey A. Lewis, Vitor Santos Costa
2014 2014 IEEE 27th International Symposium on Computer-Based Medical Systems  
Our results show that plausible regulatory networks can be learned from time series gene expression data using a probabilistic logical model.  ...  We introduce logic-based regulation models based on state-of-the-art work on statistical relational learning, and validate our approach by using it to analyze time-series gene expression data of the Hog1  ...  Despite the challenge of inferring genetic regulatory networks from gene expression data, various computational models have been developed for regulatory network analysis.  ... 
doi:10.1109/cbms.2014.9 dblp:conf/cbms/GoncalvesOLC14 fatcat:jrnt6dtqkffi3b6mnfsk4d7voe

A survey of application: Genomics and genetic programming, a new frontier

Mohammad Wahab Khan, Mansaf Alam
2012 Genomics  
This is followed by a review of applications in the areas of gene network inference, gene expression data analysis, SNP analysis, epistasis analysis and gene annotation.  ...  Finally this paper concluded by suggesting potential avenues of possible future research on genetic programming, opportunities to extend the technique, and areas for possible practical applications.  ...  Danishuddin for their valuable assistant to me in drafting and reviewing the manuscript. I am thankful for his courageous motivation to me for exploring the research.  ... 
doi:10.1016/j.ygeno.2012.05.014 pmid:22683715 fatcat:xlq5ilckr5fdjgo4ia4k7b6rz4

MetNet: Software to Build and Model the Biogenetic Lattice ofArabidopsis

Eve Syrkin Wurtele, Jie Li, Lixia Diao, Hailong Zhang, Carol M. Foster, Beth Fatland, Julie Dickerson, Andrew Brown, Zach Cox, Dianne Cook, Eun-Kyung Lee, Heike Hofmann
2003 Comparative and Functional Genomics  
The software is designed to enable the biologist to visualize, statistically analyse and model a metabolic and regulatory network map ofArabidopsis, combined with gene expression profiling data.  ...  regulatory networks that control plant composition and development.  ...  Acknowledgements We thank Lucas Mueller and TAIR for helpful advice and Aracyc data.  ... 
doi:10.1002/cfg.285 pmid:18629120 pmcid:PMC2447407 fatcat:fx32ghasijgklhfowqqguacqqq

Evolving Genes to Balance a Pole [chapter]

Miguel Nicolau, Marc Schoenauer, Wolfgang Banzhaf
2010 Lecture Notes in Computer Science  
The network is a modified version of an Artificial Regulatory Network proposed a few years ago, and the task could be solved only by finding a proper way of connecting inputs and outputs to the network  ...  We show that the representation is able to generalize well over the problem domain, and discuss the performance of different models of this kind.  ...  Artificial Gene Regulatory Model Representation and Dynamics The model used in this work [6] is composed of a genome, represented as a binary string, and mobile proteins, which interact with the genome  ... 
doi:10.1007/978-3-642-12148-7_17 fatcat:nizuul4jkfcmbl2k322ea65ewe

Evolving Genes to Balance a Pole [article]

Miguel Nicolau, Marc Schoenauer, W. Banzhaf
2010 arXiv   pre-print
The network is a modified version of an Artificial Regulatory Network proposed a few years ago, and the task could be solved only by finding a proper way of connecting inputs and outputs to the network  ...  We show that the representation is able to generalize well over the problem domain, and discuss the performance of different models of this kind.  ...  Artificial Gene Regulatory Model Representation and dynamics The model used in this work [6] is composed of a genome, represented as a binary string, and mobile proteins, which interact with the genome  ... 
arXiv:1005.2815v1 fatcat:iyjue3z55rbl5fvatdzealpvbe

Toward the dynamic interactome: it's about time

T. M. Przytycka, M. Singh, D. K. Slonim
2010 Briefings in Bioinformatics  
The availability of experimentally determined large-scale cellular networks, along with other high-throughput experimental data sets that provide snapshots of biological systems at different times and  ...  This burgeoning research area, which entails a shift from static to dynamic network analysis, promises to be a major step forward in our ability to model and reason about cellular function and behavior  ...  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
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