Access the full text.
Sign up today, get DeepDyve free for 14 days.
Madhusudan Natarajan, Keng-mean Lin, R. Hsueh, P. Sternweis, R. Ranganathan (2006)
A global analysis of cross-talk in a mammalian cellular signalling networkNature Cell Biology, 8
Hao Xiong, Y. Choe (2008)
Structural systems identification of genetic regulatory networksBioinformatics, 24 4
M. Oti, H. Brunner (2006)
The modular nature of genetic diseasesClinical Genetics, 71
J. Ernst, O. Vainas, Christopher Harbison, I. Simon, Z. Bar-Joseph (2007)
Reconstructing dynamic regulatory mapsMolecular Systems Biology, 3
Derek Ruths, L. Nakhleh, M. Iyengar, S. Reddy, Prahlad Ram (2006)
Hypothesis Generation in Signaling NetworksJournal of computational biology : a journal of computational molecular cell biology, 13 9
K. Basso, Adam Margolin, G. Stolovitzky, U. Klein, R. Dalla-Favera, A. Califano (2005)
Reverse engineering of regulatory networks in human B cellsNature Genetics, 37
Y. Nikolsky, S. Ekins, T. Nikolskaya, A. Bugrim (2005)
A novel method for generation of signature networks as biomarkers from complex high throughput data.Toxicology letters, 158 1
Michael Cary, Gary Bader, C. Sander (2005)
Pathway information for systems biologyFEBS Letters, 579
D. Pe’er, N. Hacohen (2011)
Principles and Strategies for Developing Network Models in CancerCell, 144
Matteo Barberis, E. Klipp, M. Vanoni, L. Alberghina (2007)
Cell Size at S Phase Initiation: An Emergent Property of the G1/S NetworkPLoS Computational Biology, 3
Ting Chen, Hongyu He, G. Church (1998)
Modeling Gene Expression with Differential EquationsPacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
X. Lou, Guo-Bo Chen, Lei Yan, Jennie Ma, Jamie Mangold, Jun Zhu, R. Elston, Ming Li (2008)
A combinatorial approach to detecting gene-gene and gene-environment interactions in family studies.American journal of human genetics, 83 4
T. Nelson, A. Behfar, A. Terzic (2008)
Stem Cells: Biologics for RegenerationClinical Pharmacology & Therapeutics, 84
Richard Bonneau (2008)
Learning biological networks: from modules to dynamics.Nature chemical biology, 4 11
H. Barton (2005)
Computational Pharmacokinetics During Developmental Windows of SusceptibilityJournal of Toxicology and Environmental Health, Part A, 68
Yuequin Fang, Wan Wong, Yan Yap, Brendan Orner (2007)
Stem cells and combinatorial science.Combinatorial chemistry & high throughput screening, 10 8
G. Paolini, Richard Shapland, W. Hoorn, J. Mason, A. Hopkins (2006)
Global mapping of pharmacological spaceNature Biotechnology, 24
S. Rasmussen, N. Baas, B. Mayer, M. Nilsson (2002)
Defense of the Ansatz for Dynamical HierarchiesArtificial Life, 7
Yongliang Yang, S. Adelstein, A. Kassis (2012)
Target discovery from data mining approaches.Drug discovery today, 17 Suppl
Gir-Won Lee, Sangsoo Kim (2008)
Genome data mining for everyone.BMB reports, 41 11
P. Davies (2004)
Emergent biological principles and the computational properties of the universe: Explaining it or explaining it awayComplex., 10
A. Brakhage, J. Schuemann, Sebastian Bergmann, K. Scherlach, V. Schroeckh, C. Hertweck (2008)
Activation of fungal silent gene clusters: a new avenue to drug discovery.Progress in drug research. Fortschritte der Arzneimittelforschung. Progres des recherches pharmaceutiques, 66
Luisa Laureti, Lijiang Song, Sheng Huang, C. Corre, P. Leblond, G. Challis, B. Aigle (2011)
Identification of a bioactive 51-membered macrolide complex by activation of a silent polyketide synthase in Streptomyces ambofaciensProceedings of the National Academy of Sciences, 108
B. Kholodenko (2006)
Cell-signalling dynamics in time and spaceNature Reviews Molecular Cell Biology, 7
J. Greef (2005)
Systems biology, connectivity and the future of medicine., 152
E. Kunkel (2004)
Systems biology in drug discoveryNature Biotechnology, 22
Madhukar Dasika, A. Burgard, C. Maranas (2006)
A computational framework for the topological analysis and targeted disruption of signal transduction networks.Biophysical journal, 91 1
S. Ekins, Y. Nikolsky, A. Bugrim, E. Kirillov, T. Nikolskaya (2007)
Pathway mapping tools for analysis of high content data.Methods in molecular biology, 356
SunYong Kim, S. Imoto, S. Miyano (2003)
Inferring gene networks from time series microarray data using dynamic Bayesian networksBriefings in bioinformatics, 4 3
A. Kel, N. Voss, T. Valeev, P. Stegmaier, O. Kel-Margoulis, E. Wingender (2008)
ExPlain™: finding upstream drug targets in disease gene regulatory networksSAR and QSAR in Environmental Research, 19
Gang Liu, S. Neelamegham (2008)
In silico Biochemical Reaction Network Analysis (IBRENA): a package for simulation and analysis of reaction networksBioinformatics, 24 8
A. Marsh, Yujing Zeng, J. Garcia-Frías (2006)
The expansion of information in ecological systems: Emergence as a quantifiable stateEcol. Informatics, 1
R. Ashkenazi, Sara Gentry, T. Jackson (2008)
Pathways to tumorigenesis--modeling mutation acquisition in stem cells and their progeny.Neoplasia, 10 11
Sean Ekins, Jordi Mestres, B. Testa (2007)
In silico pharmacology for drug discovery: methods for virtual ligand screening and profilingBritish Journal of Pharmacology, 152
G. Lomberk, R. Urrutia (2008)
Primers on Molecular Pathways – NotchPancreatology, 8
J. Vilar, R.E.A. Jansen, C. Sander (2005)
Signal Processing in the TGF-β Superfamily Ligand-Receptor NetworkPLoS Computational Biology, 2
N. Lee (2005)
Genomic approaches for reconstructing gene networks.Pharmacogenomics, 6 3
A. Abdi, M. Tahoori, E. Emamian (2008)
Fault Diagnosis Engineering of Digital Circuits Can Identify Vulnerable Molecules in Complex Cellular PathwaysScience Signaling, 1
K. Richards, M. Bithell, M. Dove, R. Hodge (2004)
Discrete–element modelling: methods and applications in the environmental sciencesPhilosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 362
R. Araujo, E. Petricoin, L. Liotta (2005)
A mathematical model of combination therapy using the EGFR signaling network.Bio Systems, 80 1
Alexander Schliep, A. Schönhuth, C. Steinhoff (2003)
Using hidden Markov models to analyze gene expression time course dataBioinformatics, 19 Suppl 1
G. Tonon (2008)
From oncogene to network addiction: the new frontier of cancer genomics and therapeutics.Future oncology, 4 4
J. Wikswo, A. Prokop, F. Baudenbacher, D. Cliffel, B. Csukás, M. Velkovsky (2006)
Engineering challenges of BioNEMS: the integration of microfluidics, micro- and nanodevices, models and external control for systems biology.IEE proceedings. Nanobiotechnology, 153 4
D. Faratian, A. Goltsov, G. Lebedeva, A. Sorokin, S. Moodie, P. Mullen, Charlene Kay, I. Um, S. Langdon, I. Goryanin, D. Harrison (2009)
Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab.Cancer research, 69 16
Kai Wang, M. Saito, B. Bisikirska, Mariano Alvarez, W. Lim, Presha Rajbhandari, Qiong Shen, I. Nemenman, K. Basso, Adam Margolin, U. Klein, R. Dalla-Favera, A. Califano (2009)
Genome-wide Identification of Post-translational Modulators of Transcription Factor Activity in Human B-CellsNature biotechnology, 27
Nicole Morel, Joanne Holland, J. Greef, Edward Marple, C. Clish, J. Loscalzo, S. Naylor (2004)
Primer on medical genomics. Part XIV: Introduction to systems biology--a new approach to understanding disease and treatment.Mayo Clinic proceedings, 79 5
D. Camacho, Paola Licona, P. Mendes, R. Laubenbacher (2007)
Comparison of Reverse‐Engineering Methods Using an in Silico NetworkAnnals of the New York Academy of Sciences, 1115
A. Sol, R. Balling, L. Hood, D. Galas (2010)
Diseases as network perturbations.Current opinion in biotechnology, 21 4
Erwin Gianchandani, M. Oberhardt, A. Burgard, C. Maranas, J. Papin (2008)
Predicting biological system objectives de novo from internal state measurementsBMC Bioinformatics, 9
K. Csilléry, M. Blum, O. Gaggiotti, O. François (2010)
Approximate Bayesian Computation (ABC) in practice.Trends in ecology & evolution, 25 7
N. Jamshidi, B. Palsson (2008)
Top-Down Analysis of Temporal Hierarchy in Biochemical Reaction NetworksPLoS Computational Biology, 4
A. Barabási, N. Gulbahce, J. Loscalzo (2010)
Network medicine: a network-based approach to human diseaseNature Reviews Genetics, 12
G. Altay, F. Emmert-Streib (2010)
Inferring the conservative causal core of gene regulatory networksBMC Systems Biology, 4
Y. Nikolsky, T. Nikolskaya, A. Bugrim (2005)
Biological networks and analysis of experimental data in drug discovery.Drug discovery today, 10 9
C. Kim (2007)
Bayesian Orthogonal Least Squares (BOLS) algorithm for reverse engineering of gene regulatory networksBMC Bioinformatics, 8
K. Goh, M. Cusick, D. Valle, B. Childs, M. Vidal, A. Barabási (2007)
The human disease networkProceedings of the National Academy of Sciences, 104
R. Schugar, P. Robbins, B. Deasy, B. Deasy (2008)
Small molecules in stem cell self-renewal and differentiationGene Therapy, 15
Yanhua Chen, Ruiping Zhang, Yongmei Song, Jiuming He, Jianghao Sun, Jin-fa Bai, Zhuoling An, Li-jia Dong, Q. Zhan, Z. Abliz (2009)
RRLC-MS/MS-based metabonomics combined with in-depth analysis of metabolic correlation network: finding potential biomarkers for breast cancer.The Analyst, 134 10
Esti Yeger-Lotem, Shmuel Sattath, N. Kashtan, S. Itzkovitz, R. Milo, R. Pinter, U. Alon, H. Margalit (2004)
Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction.Proceedings of the National Academy of Sciences of the United States of America, 101 16
N. Emre, Ronald Coleman, Sheng Ding (2007)
A chemical approach to stem cell biology.Current opinion in chemical biology, 11 3
S. Ananiadou, D. Kell, Junichi Tsujii (2006)
Text mining and its potential applications in systems biology.Trends in biotechnology, 24 12
E. Ahmed, A. Hashish (2006)
On modelling the immune system as a complex systemTheory in Biosciences, 124
Abhishek Tripathi, Arto Klami, Samuel Kaski (2008)
Simple integrative preprocessing preserves what is shared in data sourcesBMC Bioinformatics, 9
J. Greef, Stephen Martin, P. Juhasz, A. Adourian, T. Plasterer, E. Verheij, R. McBurney (2007)
The art and practice of systems biology in medicine: mapping patterns of relationships.Journal of proteome research, 6 4
R. Christopher, A. Dhiman, J. Fox, R. Gendelman, T. Haberitcher, D. Kagle, G. Spizz, I. Khalil, C. Hill (2004)
Data‐Driven Computer Simulation of Human Cancer CellAnnals of the New York Academy of Sciences, 1020
J. Papin, B. Palsson (2004)
Topological analysis of mass-balanced signaling networks: a framework to obtain network properties including crosstalk.Journal of theoretical biology, 227 2
J. Fromm (2005)
Types and Forms of EmergencearXiv: Adaptation and Self-Organizing Systems
R. Milo, S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii, U. Alon (2002)
Network motifs: simple building blocks of complex networks.Science, 298 5594
M. Ramoni, P. Sebastiani, I. Kohane (2002)
Cluster analysis of gene expression dynamicsProceedings of the National Academy of Sciences of the United States of America, 99
S. Michelson, T. Schofield (1996)
The biostatistics cookbook : the most user-friendly guide for the bio/medical scientist
F. Bruggeman, H. Westerhoff (2007)
The nature of systems biology.Trends in microbiology, 15 1
K. Plaimas, Jan-Philipp Mallm, M. Oswald, Fabian Svara, V. Sourjik, R. Eils, R. König (2008)
Machine learning based analyses on metabolic networks supports high-throughput knockout screensBMC Systems Biology, 2
Neal Holter, A. Maritan, M. Cieplak, N. Fedoroff, J. Banavar (2001)
Dynamic modeling of gene expression data.Proceedings of the National Academy of Sciences of the United States of America, 98 4
Lang Li, Menggang Yu, R. Jason, Changyu Shen, F. Azzouz, H. McLeod, Silvana Borges-Gonzales, A. Nguyen, T. Skaar, Z. Desta, C. Sweeney, D. Flockhart (2008)
A Mixture Model Approach in Gene–Gene and Gene–Environmental Interactions for Binary PhenotypesJournal of Biopharmaceutical Statistics, 18
Lily Yan, I. Karatsoreos, J. LeSauter, David Welsh, S. Kay, D. Foley, R. Silver (2007)
Exploring spatiotemporal organization of SCN circuits.Cold Spring Harbor symposia on quantitative biology, 72
[To date, few cellular and gene networks have been reconstructed and analyzed in full. Examples include some prokaryotes and few eukaryotes for cellular networks. The methods currently used to analyze single database genomic sets are usually mature and refined. Network reconstruction is also enabled by analysing the molecular connectivity of a system by using correlation analysis. Additionally, monitoring the dynamics of the system and measuring the system’s responses to perturbations such as drug administration or challenge tests can yield insights into the dynamics of the system. Microbial cells are fairly well characterized, but the status of similar efforts for mammalian cells is rather poor. While emergence can be conveniently studied via computational tools, the phenomenon of emergence is the single most important benefit of CSB.]
Published: Jan 4, 2012
Keywords: Biological Network; Canonical Correlation Analysis; Emergent Property; Multifactor Dimensionality Reduction; Undesirable Output
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.