-
1
-
-
65249094824
-
Analysis of biological networks
-
Wiley-Interscience
-
Björn JH, Schreiber F. Analysis of biological networks. 2008, Wiley-Interscience.
-
(2008)
-
-
Björn, J.H.1
Schreiber, F.2
-
2
-
-
84889418078
-
Biomolecular Networks: Methods and Applications in Systems Biology
-
John Wiley and Sons
-
Chen L, Wang RS, Zhang XS. Biomolecular Networks: Methods and Applications in Systems Biology. 2009, John Wiley and Sons.
-
(2009)
-
-
Chen, L.1
Wang, R.S.2
Zhang, X.S.3
-
3
-
-
43849084374
-
Inferring connectivity of genetic regulatory networks using information-theoretic criteria
-
Zhao W, Serpedin E, Dougherty ER. Inferring connectivity of genetic regulatory networks using information-theoretic criteria. IEEE, Transactions on Computational Biology and Bioinformatics 2008, 5(2):262-274.
-
(2008)
IEEE, Transactions on Computational Biology and Bioinformatics
, vol.5
, Issue.2
, pp. 262-274
-
-
Zhao, W.1
Serpedin, E.2
Dougherty, E.R.3
-
4
-
-
61349180117
-
Gene regulatory network inference: Data integration in dynamic models - A review.
-
Hecker M, Lambeck S, Toepfer S, Someren EV, Guthke R. Gene regulatory network inference: Data integration in dynamic models - A review. Bio Systems 2009, 96(1):86-103.
-
(2009)
Bio Systems
, vol.96
, Issue.1
, pp. 86-103
-
-
Hecker, M.1
Lambeck, S.2
Toepfer, S.3
Someren, E.V.4
Guthke, R.5
-
5
-
-
34249761849
-
Learning Bayesian networks: The combination of knowledge and statistical data
-
Heckerman D, Geiger D, Chickering DM. Learning Bayesian networks: The combination of knowledge and statistical data. Machine Learning 1995, 20:197-243.
-
(1995)
Machine Learning
, vol.20
, pp. 197-243
-
-
Heckerman, D.1
Geiger, D.2
Chickering, D.M.3
-
7
-
-
0004158155
-
Modelling gene expression data using dynamic Bayesian networks.
-
Murphy K, Mian S. Modelling gene expression data using dynamic Bayesian networks. In Technical report, Computer Science Division University of California, Berkeley, CA 1999,
-
(1999)
In Technical report, Computer Science Division University of California, Berkeley, CA
-
-
Murphy, K.1
Mian, S.2
-
8
-
-
0014489272
-
Metabolic stability and epigenesis in randomly constructed genetic nets.
-
10.1016/0022-5193(69)90015-0, 5803332
-
Kauffman SA. Metabolic stability and epigenesis in randomly constructed genetic nets. J Theor Biol 1969, 22:437-467. 10.1016/0022-5193(69)90015-0, 5803332.
-
(1969)
J Theor Biol
, vol.22
, pp. 437-467
-
-
Kauffman, S.A.1
-
9
-
-
0036184629
-
Probabilistic Boolean Networks: A rule-based uncertainty model for gene regulatory networks.
-
10.1093/bioinformatics/18.2.261, 11847074
-
Schmulevich I, Dougherty ER, Kim S, Zhang W. Probabilistic Boolean Networks: A rule-based uncertainty model for gene regulatory networks. Bioinformatics 2002, 18(2):261-274. 10.1093/bioinformatics/18.2.261, 11847074.
-
(2002)
Bioinformatics
, vol.18
, Issue.2
, pp. 261-274
-
-
Schmulevich, I.1
Dougherty, E.R.2
Kim, S.3
Zhang, W.4
-
10
-
-
0345983657
-
From boolean to probabilistic boolean networks as models of genetic regulatory networks.
-
Shmulevich I, Dougherty ER, Zhang W. From boolean to probabilistic boolean networks as models of genetic regulatory networks. Proceedings of the IEEE 2002, 90(11):1778-1792.
-
(2002)
Proceedings of the IEEE
, vol.90
, Issue.11
, pp. 1778-1792
-
-
Shmulevich, I.1
Dougherty, E.R.2
Zhang, W.3
-
12
-
-
33748654580
-
Inferring gene regulatory networks from time series data using the minimum description length principle.
-
10.1093/bioinformatics/btl364, 16845143
-
Zhao W, Serpedin E, Dougherty ER. Inferring gene regulatory networks from time series data using the minimum description length principle. Bioinformatics 2006, 22(17):2129-2135. 10.1093/bioinformatics/btl364, 16845143.
-
(2006)
Bioinformatics
, vol.22
, Issue.17
, pp. 2129-2135
-
-
Zhao, W.1
Serpedin, E.2
Dougherty, E.R.3
-
13
-
-
45749124003
-
Inference of gene regulatory networks based on a universal minimum description length.
-
Article ID: 482090, 11 pages, 2329739, 18437238
-
Dougherty J, Tabus I, Astola J. Inference of gene regulatory networks based on a universal minimum description length. EURASIP Journal on Bioinformatics and Systems Biology 2008, Article ID: 482090, 11 pages, 2329739, 18437238.
-
(2008)
EURASIP Journal on Bioinformatics and Systems Biology
-
-
Dougherty, J.1
Tabus, I.2
Astola, J.3
-
14
-
-
33947305781
-
ARACNE: An algorithm for reconstruction of genetic networks in a mammalian cellular context.
-
10.1186/1471-2105-7-S1-S7, 1810318, 16723010
-
Margolin AA, Nemenman I, Basso K, Wiggins C, Stolovitzky G, Dalla Favera R, Califano A. ARACNE: An algorithm for reconstruction of genetic networks in a mammalian cellular context. BMC Bioinformatics 2006, 7:S7. 10.1186/1471-2105-7-S1-S7, 1810318, 16723010.
-
(2006)
BMC Bioinformatics
, vol.7
-
-
Margolin, A.A.1
Nemenman, I.2
Basso, K.3
Wiggins, C.4
Stolovitzky, G.5
Dalla Favera, R.6
Califano, A.7
-
15
-
-
0031616241
-
REVEAL: A general reverse engineering algorithm for inference of genetic network architectures
-
Shoudan L. REVEAL: A general reverse engineering algorithm for inference of genetic network architectures. Pacific Symposium on Biocomputing 1998, 3:18-29.
-
(1998)
Pacific Symposium on Biocomputing
, vol.3
, pp. 18-29
-
-
Shoudan, L.1
-
16
-
-
0141879236
-
Model Selection and the Principle of Minimum Description Length.
-
Hansen MH, Yu B. Model Selection and the Principle of Minimum Description Length. Journal of the American Statistical Association 2001, 96(454):746-774.
-
(2001)
Journal of the American Statistical Association
, vol.96
, Issue.454
, pp. 746-774
-
-
Hansen, M.H.1
Yu, B.2
-
17
-
-
70450169069
-
Gene Regulatory Network Inference Using Predictive Minimum Description Length Principle and Conditional Mutual Information
-
Chaitankar V, Zhang C, Ghosh P, Perkins EJ, Gong P, Deng Y. Gene Regulatory Network Inference Using Predictive Minimum Description Length Principle and Conditional Mutual Information. Proceedings of International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing 2009, 487-490.
-
(2009)
Proceedings of International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing
, pp. 487-490
-
-
Chaitankar, V.1
Zhang, C.2
Ghosh, P.3
Perkins, E.J.4
Gong, P.5
Deng, Y.6
-
18
-
-
12744261506
-
A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data
-
10.1093/bioinformatics/bth463, 15308537
-
Zou M, Conzen SD. A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data. Bioinformatics 2005, 21(1):71-79. 10.1093/bioinformatics/bth463, 15308537.
-
(2005)
Bioinformatics
, vol.21
, Issue.1
, pp. 71-79
-
-
Zou, M.1
Conzen, S.D.2
-
20
-
-
26944457320
-
An Algorithm to Learn Causal Relations Between Genes from Steady State Data: Simulation and Its Application to Melanoma Dataset.
-
Zhang X, Baral C, Kim S. An Algorithm to Learn Causal Relations Between Genes from Steady State Data: Simulation and Its Application to Melanoma Dataset. Proceedings of 10th Conference on Artificial Intelligence in Medicine 2005, 524-534.
-
(2005)
Proceedings of 10th Conference on Artificial Intelligence in Medicine
, pp. 524-534
-
-
Zhang, X.1
Baral, C.2
Kim, S.3
-
21
-
-
84888285184
-
Revealing strengths and weaknesses of methods for gene network inference
-
Marbach D, Prill RJ, Schaffter T, Mattiussi C, Floreano D, Stolovitzky G. Revealing strengths and weaknesses of methods for gene network inference. PNAS
-
PNAS
-
-
Marbach, D.1
Prill, R.J.2
Schaffter, T.3
Mattiussi, C.4
Floreano, D.5
Stolovitzky, G.6
-
22
-
-
77949644952
-
Towards a rigorous assessment of systems biology models: the DREAM3 challenges
-
10.1371/journal.pone.0009202, 2826397, 20186320
-
Prill RJ, Marbach D, Saez-Rodriguez J, Sorger PK, Alexopoulos LG, Xue X, Clarke ND, Altan-Bonnet G, Stolovitzky G. Towards a rigorous assessment of systems biology models: the DREAM3 challenges. PLoS ONE 2010, 5(2):e9202. 10.1371/journal.pone.0009202, 2826397, 20186320.
-
(2010)
PLoS ONE
, vol.5
, Issue.2
-
-
Prill, R.J.1
Marbach, D.2
Saez-Rodriguez, J.3
Sorger, P.K.4
Alexopoulos, L.G.5
Xue, X.6
Clarke, N.D.7
Altan-Bonnet, G.8
Stolovitzky, G.9
-
23
-
-
59649110273
-
Generating realistic in silico gene networks for performance assessment of reverse engineering methods
-
10.1089/cmb.2008.09TT, 19183003
-
Marbach D, Schaffter T, Mattiussi C, Floreano D. Generating realistic in silico gene networks for performance assessment of reverse engineering methods. Journal of Computational Biology 2009, 16(2):229-239. 10.1089/cmb.2008.09TT, 19183003.
-
(2009)
Journal of Computational Biology
, vol.16
, Issue.2
, pp. 229-239
-
-
Marbach, D.1
Schaffter, T.2
Mattiussi, C.3
Floreano, D.4
-
24
-
-
33947626576
-
Inference of Biologically Relevant Gene Influence Networks Using the Directed Information Criterion
-
II-II
-
Rao A, Hero AO, States DJ, Engel JD. Inference of Biologically Relevant Gene Influence Networks Using the Directed Information Criterion. ICASSP Proceedings 2006, 2(II-II).
-
(2006)
ICASSP Proceedings
, vol.2
-
-
Rao, A.1
Hero, A.O.2
States, D.J.3
Engel, J.D.4
-
25
-
-
0031742022
-
Comprehensive Identification of Cell Cycle-regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization.
-
25624, 9843569
-
Spellman PT, Sherlock G, Zhang MQ, Iyer VR, Anders K, Eisen MB, Brown PO, Botstein D, Futcher B. Comprehensive Identification of Cell Cycle-regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization. Molecular Biology of the Cell 1998, 9:3273-3297. 25624, 9843569.
-
(1998)
Molecular Biology of the Cell
, vol.9
, pp. 3273-3297
-
-
Spellman, P.T.1
Sherlock, G.2
Zhang, M.Q.3
Iyer, V.R.4
Anders, K.5
Eisen, M.B.6
Brown, P.O.7
Botstein, D.8
Futcher, B.9
-
26
-
-
38549126643
-
KEGG for linking genomes to life and the environment.
-
10.1093/nar/gkm882, 2238879, 18077471
-
Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T, Yamanishi Y. KEGG for linking genomes to life and the environment. Nucleic Acids Res 2008, 36:D480-D484. 10.1093/nar/gkm882, 2238879, 18077471.
-
(2008)
Nucleic Acids Res
, vol.36
-
-
Kanehisa, M.1
Araki, M.2
Goto, S.3
Hattori, M.4
Hirakawa, M.5
Itoh, M.6
Katayama, T.7
Kawashima, S.8
Okuda, S.9
Tokimatsu, T.10
Yamanishi, Y.11
-
27
-
-
33644874819
-
From genomics to chemical genomics: new developments in KEGG.
-
10.1093/nar/gkj102, 1347464, 16381885
-
Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki M, Hirakawa M. From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res 2006, 34:D354-357. 10.1093/nar/gkj102, 1347464, 16381885.
-
(2006)
Nucleic Acids Res
, vol.34
-
-
Kanehisa, M.1
Goto, S.2
Hattori, M.3
Aoki-Kinoshita, K.F.4
Itoh, M.5
Kawashima, S.6
Katayama, T.7
Araki, M.8
Hirakawa, M.9
-
28
-
-
0033982936
-
KEGG: Kyoto Encyclopedia of Genes and Genomes.
-
10.1093/nar/28.1.27, 102409, 10592173
-
Kanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 2000, 28:27-30. 10.1093/nar/28.1.27, 102409, 10592173.
-
(2000)
Nucleic Acids Res
, vol.28
, pp. 27-30
-
-
Kanehisa, M.1
Goto, S.2
|