Computational Systems Biology
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Roger E. Bumgarner | Ram Samudrala | Jason E. McDermott | Kristina Montgomery | Rene Ireton | Roger E Bumgarner | R. Samudrala | J. Mcdermott | R. Ireton | K. Montgomery
[1] D. Landsman,et al. Multiple independent evolutionary solutions to core histone gene regulation , 2006, Genome Biology.
[2] Michael Ruogu Zhang,et al. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. , 1998, Molecular biology of the cell.
[3] Petri Auvinen,et al. Bayesian Hierarchical Model for Correcting Signal Saturation in Microarrays Using Pixel Intensities , 2006, Statistical applications in genetics and molecular biology.
[4] J. Collins,et al. Size matters: network inference tackles the genome scale , 2007, Molecular systems biology.
[5] M. Wall,et al. Design of gene circuits: lessons from bacteria , 2004, Nature Reviews Genetics.
[6] R. Young,et al. Rapid analysis of the DNA-binding specificities of transcription factors with DNA microarrays , 2004, Nature Genetics.
[7] Fang-Xiang Wu,et al. Modeling Gene Expression from Microarray Expression Data with State-Space Equations , 2003, Pacific Symposium on Biocomputing.
[8] K. F. Tipton,et al. Biochemical systems analysis: A study of function and design in molecular biology , 1978 .
[9] Brian D. Dynlacht,et al. Regulation of transcription by proteins that control the cell cycle , 1997, Nature.
[10] M. Vidal,et al. Yeast forward and reverse 'n'-hybrid systems. , 1999, Nucleic acids research.
[11] R. Tibshirani,et al. Least angle regression , 2004, math/0406456.
[12] T. D. Schneider,et al. Sequence logos: a new way to display consensus sequences. , 1990, Nucleic acids research.
[13] P. Shannon,et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.
[14] E. Klipp,et al. Biochemical networks with uncertain parameters. , 2005, Systems biology.
[15] H. Iba,et al. Inference of gene regulatory networks by means of dynamic differential Bayesian networks and nonparametric regression. , 2004, Genome informatics. International Conference on Genome Informatics.
[16] Eric H. Davidson,et al. Gene activity in early development , 1968 .
[17] H Niemann,et al. Identification and analysis of eukaryotic promoters: recent computational approaches. , 2001, Trends in genetics : TIG.
[18] K. Kinzler,et al. Serial Analysis of Gene Expression , 1995, Science.
[19] Martha L Bulyk,et al. DNA microarray technologies for measuring protein-DNA interactions. , 2006, Current opinion in biotechnology.
[20] Martin Kuiper,et al. BiNGO: a Cytoscape plugin to assess overrepresentation of Gene Ontology categories in Biological Networks , 2005, Bioinform..
[21] Xin Chen,et al. TRANSFAC: an integrated system for gene expression regulation , 2000, Nucleic Acids Res..
[22] William Stafford Noble,et al. Assessing computational tools for the discovery of transcription factor binding sites , 2005, Nature Biotechnology.
[23] Kathleen Marchal,et al. SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms , 2006, BMC Bioinformatics.
[24] Rachel B. Brem,et al. The landscape of genetic complexity across 5,700 gene expression traits in yeast. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[25] Maria Jesus Martin,et al. The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003 , 2003, Nucleic Acids Res..
[26] Arpad Kelemen,et al. Differential and trajectory methods for time course gene expression data , 2005, Bioinform..
[27] Jens Timmer,et al. Reconstructing gene-regulatory networks from time series, knock-out data, and prior knowledge , 2007, BMC Systems Biology.
[28] Gustavo Stolovitzky,et al. Reconstructing biological networks using conditional correlation analysis , 2005, Bioinform..
[29] Martha L Bulyk,et al. Analysis of sequence specificities of DNA-binding proteins with protein binding microarrays. , 2006, Methods in enzymology.
[30] A. Hartemink. Reverse engineering gene regulatory networks , 2005, Nature Biotechnology.
[31] R. Durbin,et al. The Sequence Ontology: a tool for the unification of genome annotations , 2005, Genome Biology.
[32] John J. Tyson,et al. Classification of instabilities in chemical reaction systems , 1975 .
[33] Gary D. Bader,et al. An automated method for finding molecular complexes in large protein interaction networks , 2003, BMC Bioinformatics.
[34] Chris Wiggins,et al. ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context , 2004, BMC Bioinformatics.
[35] Olivier Bodenreider,et al. Global similarity and local divergence in human and mouse gene co-expression networks , 2006, BMC Evolutionary Biology.
[36] Xinkun Wang,et al. An effective structure learning method for constructing gene networks , 2006, Bioinform..
[37] H. Sauro,et al. Conservation analysis in biochemical networks: computational issues for software writers. , 2004, Biophysical chemistry.
[38] Amy K. Schmid,et al. A Predictive Model for Transcriptional Control of Physiology in a Free Living Cell , 2007, Cell.
[39] Balth van der Pol Jun Docts. Sc.,et al. LXXII. The heartbeat considered as a relaxation oscillation, and an electrical model of the heart , 1928 .
[40] H. Sauro. Moiety-conserved cycles and metabolic control analysis: problems in sequestration and metabolic channelling. , 1994, Bio Systems.
[41] David Tuck,et al. Characterizing disease states from topological properties of transcriptional regulatory networks , 2006, BMC Bioinformatics.
[42] E. Koonin,et al. Conservation and coevolution in the scale-free human gene coexpression network. , 2004, Molecular biology and evolution.
[43] Paul P. Wang,et al. Advances to Bayesian network inference for generating causal networks from observational biological data , 2004, Bioinform..
[44] Dirk Drasdo,et al. Gene network inference from incomplete expression data: transcriptional control of hematopoietic commitment , 2006, Bioinform..
[45] Tomoyuki Higuchi,et al. Estimating time-dependent gene networks from time series microarray data by dynamic linear models with Markov switching , 2005, 2005 IEEE Computational Systems Bioinformatics Conference (CSB'05).
[46] Susumu Goto,et al. The KEGG resource for deciphering the genome , 2004, Nucleic Acids Res..
[47] Richard Bonneau,et al. The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo , 2006, Genome Biology.
[48] Jun S. Liu,et al. Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. , 1993, Science.
[49] Joseph T. Chang,et al. Spectral biclustering of microarray data: coclustering genes and conditions. , 2003, Genome research.
[50] Marc Vidal,et al. Predictive models of molecular machines involved in Caenorhabditis elegans early embryogenesis , 2005, Nature.
[51] Ram Samudrala,et al. Bioverse: functional, structural and contextual annotation of proteins and proteomes , 2003, Nucleic Acids Res..
[52] T. Wolfsberg,et al. Global Regulation by the Yeast Spt10 Protein Is Mediated through Chromatin Structure and the Histone Upstream Activating Sequence Elements , 2005, Molecular and Cellular Biology.
[53] C Reder,et al. Metabolic control theory: a structural approach. , 1988, Journal of theoretical biology.
[54] Megan F. Cole,et al. Core Transcriptional Regulatory Circuitry in Human Embryonic Stem Cells , 2005, Cell.
[55] Diego di Bernardo,et al. Inference of gene regulatory networks and compound mode of action from time course gene expression profiles , 2006, Bioinform..
[56] D A Fell,et al. Covalent modification and metabolic control analysis. Modification to the theorems and their application to metabolic systems containing covalently modifiable enzymes. , 1990, European journal of biochemistry.
[57] Herbert M. Sauro,et al. Conservation analysis of large biochemical networks , 2006, Bioinform..
[58] John J. Tyson,et al. The Dynamics of Feedback Control Circuits in Biochemical Pathways , 1978 .
[59] J. Stucki,et al. Stability analysis of biochemical systems--a practical guide. , 1978, Progress in biophysics and molecular biology.
[60] Bart De Moor,et al. Biclustering microarray data by Gibbs sampling , 2003, ECCB.
[61] Ronald W. Davis,et al. A genome-wide transcriptional analysis of the mitotic cell cycle. , 1998, Molecular cell.
[62] Roded Sharan,et al. Discovering statistically significant biclusters in gene expression data , 2002, ISMB.
[63] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[64] Ana Rute Neves,et al. The intricate side of systems biology. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[65] Edda Klipp,et al. Bringing metabolic networks to life: integration of kinetic, metabolic, and proteomic data , 2006, Theoretical Biology and Medical Modelling.
[66] Nicola J. Rinaldi,et al. Transcriptional Regulatory Networks in Saccharomyces cerevisiae , 2002, Science.
[67] J. Monod,et al. [Operon: a group of genes with the expression coordinated by an operator]. , 1960, Comptes rendus hebdomadaires des seances de l'Academie des sciences.
[68] Mark Bieda,et al. Unbiased location analysis of E2F1-binding sites suggests a widespread role for E2F1 in the human genome. , 2006, Genome research.
[69] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[70] Matteo Pellegrini,et al. Prolinks: a database of protein functional linkages derived from coevolution , 2004, Genome Biology.
[71] Eugene V Koonin,et al. Evolutionary significance of gene expression divergence. , 2005, Gene.
[72] A Vázquez,et al. The topological relationship between the large-scale attributes and local interaction patterns of complex networks , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[73] George M. Church,et al. Biclustering of Expression Data , 2000, ISMB.
[74] Rodger Staden,et al. Methods for calculating the probabilities of finding patterns in sequences , 1989, Comput. Appl. Biosci..
[75] Ka Yee Yeung,et al. Context-specific infinite mixtures for clustering gene expression profiles across diverse microarray dataset , 2006, Bioinform..
[76] Finn V. Jensen,et al. Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.
[77] Edward R. Dougherty,et al. Inferring gene regulatory networks from time series data using the minimum description length principle , 2006, Bioinform..
[78] Roger E Bumgarner,et al. From co-expression to co-regulation: how many microarray experiments do we need? , 2004, Genome Biology.
[79] Michael A. Savageau,et al. Design principles for elementary gene circuits: Elements, methods, and examples. , 2001, Chaos.
[80] D. Goodlett,et al. Proteomics without polyacrylamide: qualitative and quantitative uses of tandem mass spectrometry in proteome analysis , 2002, Functional & Integrative Genomics.
[81] Eric H Davidson,et al. The Transcriptome of the Sea Urchin Embryo , 2006, Science.
[82] Hulin Wu,et al. Hierarchical Bayesian Methods for Estimation of Parameters in a Longitudinal HIV Dynamic System , 2006, Biometrics.
[83] Charles DeLisi,et al. Predictome: a database of putative functional links between proteins , 2002, Nucleic Acids Res..
[84] D. Fell,et al. The small world inside large metabolic networks , 2000, Proceedings of the Royal Society of London. Series B: Biological Sciences.
[85] S. Cawley,et al. Unbiased Mapping of Transcription Factor Binding Sites along Human Chromosomes 21 and 22 Points to Widespread Regulation of Noncoding RNAs , 2004, Cell.
[86] Giacomo Finocchiaro,et al. Myc-binding-site recognition in the human genome is determined by chromatin context , 2006, Nature Cell Biology.
[87] L. Hood,et al. Systems approaches applied to the study of Saccharomyces cerevisiae and Halobacterium sp. , 2003, Cold Spring Harbor symposia on quantitative biology.
[88] Michael A. Savageau,et al. Optimal design of feedback control by inhibition , 1975, Journal of Molecular Evolution.
[89] Sydney Brenner,et al. Massively parallel signature sequencing (MPSS) as a tool for in-depth quantitative gene expression profiling in all organisms. , 2002, Briefings in functional genomics & proteomics.
[90] G. Crooks,et al. WebLogo: a sequence logo generator. , 2004, Genome research.
[91] Pedro Mendes,et al. Artificial gene networks for objective comparison of analysis algorithms , 2003, ECCB.
[92] Jean-Philippe Vert,et al. Extracting active pathways from gene expression data , 2003, ECCB.
[93] David Landsman,et al. Alignments anchored on genomic landmarks can aid in the identification of regulatory elements , 2005, ISMB.
[94] J. Collins,et al. Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles , 2007, PLoS biology.
[95] Nicola J. Rinaldi,et al. Transcriptional regulatory code of a eukaryotic genome , 2004, Nature.
[96] Sun-Chong Wang,et al. Reconstructing Genetic Networks from Time Ordered Gene Expression Data Using Bayesian Method with Global Search Algorithm , 2004, J. Bioinform. Comput. Biol..
[97] Zoubin Ghahramani,et al. A Bayesian approach to reconstructing genetic regulatory networks with hidden factors , 2005, Bioinform..
[98] H. McAdams,et al. Global analysis of the genetic network controlling a bacterial cell cycle. , 2000, Science.
[99] David J. Reiss,et al. Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks , 2006, BMC Bioinformatics.
[100] H. Westerhoff,et al. How do enzyme activities control metabolite concentrations? An additional theorem in the theory of metabolic control. , 1984, European journal of biochemistry.
[101] V. Thorsson,et al. Reverse Engineering Galactose Regulation in Yeast through Model Selection , 2005, Statistical applications in genetics and molecular biology.
[102] Riccardo Bellazzi,et al. Random Walk Models for Bayesian Clustering of Gene Expression Profiles , 2005, Applied bioinformatics.
[103] Darren J. Wilkinson,et al. Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models , 2006, J. Comput. Biol..
[104] Alberto de la Fuente,et al. Discovery of meaningful associations in genomic data using partial correlation coefficients , 2004, Bioinform..
[105] Katherine C. Chen,et al. Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell. , 2003, Current opinion in cell biology.
[106] Kannan Tharakaraman,et al. Scanning sequences after Gibbs sampling to find multiple occurrences of functional elements , 2006, BMC Bioinformatics.
[107] D. Landsman,et al. Statistical analysis of over-represented words in human promoter sequences. , 2004, Nucleic acids research.
[108] Peter D. Karp,et al. EcoCyc: a comprehensive database resource for Escherichia coli , 2004, Nucleic Acids Res..
[109] Carole A. Goble,et al. Investigating Semantic Similarity Measures Across the Gene Ontology: The Relationship Between Sequence and Annotation , 2003, Bioinform..
[110] Roded Sharan,et al. Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[111] Nir Friedman,et al. Inferring subnetworks from perturbed expression profiles , 2001, ISMB.
[112] Min Zou,et al. A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data , 2005, Bioinform..