-
1
-
-
3042799574
-
A computational algebra approach to the reverse engineering of gene regulatory networks
-
10.1016/j.jtbi.2004.04.037, 15246788
-
Laubenbacher R, Stigler B. A computational algebra approach to the reverse engineering of gene regulatory networks. J Theor Biol 2004, 229(4):523-537. 10.1016/j.jtbi.2004.04.037, 15246788.
-
(2004)
J Theor Biol
, vol.229
, Issue.4
, pp. 523-537
-
-
Laubenbacher, R.1
Stigler, B.2
-
2
-
-
0002054202
-
Modeling the complexity of genetic networks: Understanding multigenic and pleiotropic regulation
-
Somogyi R, Sniegoski C. Modeling the complexity of genetic networks: Understanding multigenic and pleiotropic regulation. Complexity 1996, 1:45-63.
-
(1996)
Complexity
, vol.1
, pp. 45-63
-
-
Somogyi, R.1
Sniegoski, C.2
-
3
-
-
0032616683
-
Identification of genetic networks from a small number of gene expression patterns under the Boolean network model
-
Akutsu T, Miyano S, Kuhara S. Identification of genetic networks from a small number of gene expression patterns under the Boolean network model. Pac Symp Biocomput 1999, 17-28.
-
(1999)
Pac Symp Biocomput
, pp. 17-28
-
-
Akutsu, T.1
Miyano, S.2
Kuhara, S.3
-
4
-
-
22044448669
-
Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana
-
10.1186/gb-2004-5-11-r92, 545783, 15535868
-
Wille A, Zimmermann P, Vranova E, Furholz A, Laule O, Bleuler S, Hennig L, Prelic A, von Rohr P, Thiele L, et al. Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana. Genome Biol 2004, 5(11):R92. 10.1186/gb-2004-5-11-r92, 545783, 15535868.
-
(2004)
Genome Biol
, vol.5
, Issue.11
-
-
Wille, A.1
Zimmermann, P.2
Vranova, E.3
Furholz, A.4
Laule, O.5
Bleuler, S.6
Hennig, L.7
Prelic, A.8
von Rohr, P.9
Thiele, L.10
-
5
-
-
0033707946
-
Using Bayesian networks to analyze expression data
-
10.1089/106652700750050961, 11108481
-
Friedman N, Linial M, Nachman I, Pe'er D. Using Bayesian networks to analyze expression data. J Comput Biol 2000, 7(3-4):601-620. 10.1089/106652700750050961, 11108481.
-
(2000)
J Comput Biol
, vol.7
, Issue.3-4
, pp. 601-620
-
-
Friedman, N.1
Linial, M.2
Nachman, I.3
Pe'er, D.4
-
6
-
-
0036366689
-
Combining location and expression data for principled discovery of genetic regulatory network models
-
Hartemink AJ, Gifford DK, Jaakkola TS, Young RA. Combining location and expression data for principled discovery of genetic regulatory network models. Pac Symp Biocomput 2002, 437-449.
-
(2002)
Pac Symp Biocomput
, pp. 437-449
-
-
Hartemink, A.J.1
Gifford, D.K.2
Jaakkola, T.S.3
Young, R.A.4
-
7
-
-
0004158155
-
Modeling gene expression data using dynamic Bayesian networks. Technical report
-
Murphy K, Mian S. Modeling gene expression data using dynamic Bayesian networks. Technical report. Computer Science Division, University of California, Berkeley, CA 1999, http://www.cs.ubc.ca/~murphyk/Papers/ismb99.pdf
-
(1999)
Computer Science Division, University of California, Berkeley, CA
-
-
Murphy, K.1
Mian, S.2
-
8
-
-
76849109141
-
Identification of Regulatory Modules in Time Series Gene Expression Data Using a Linear Time Biclustering Algorithm
-
Madeira SC, Teixeira MC, Sa-Correia I, Oliveira AL. Identification of Regulatory Modules in Time Series Gene Expression Data Using a Linear Time Biclustering Algorithm. IEEE/ACM Trans Comput Biol Bioinformatics 2010, 7(1):153-165.
-
(2010)
IEEE/ACM Trans Comput Biol Bioinformatics
, vol.7
, Issue.1
, pp. 153-165
-
-
Madeira, S.C.1
Teixeira, M.C.2
Sa-Correia, I.3
Oliveira, A.L.4
-
9
-
-
26944497301
-
Assessment of discretization techniques for relevant pattern discovery from gene expression data
-
BIOKDD'04, ACM
-
Pensa R, Leschi C, Besson J, Boulicaut JF. Assessment of discretization techniques for relevant pattern discovery from gene expression data. 4th ACM SIGKDD Workshop on Data Mining in Bioinformatics 2004, 24-30. BIOKDD'04, ACM.
-
(2004)
4th ACM SIGKDD Workshop on Data Mining in Bioinformatics
, pp. 24-30
-
-
Pensa, R.1
Leschi, C.2
Besson, J.3
Boulicaut, J.F.4
-
10
-
-
37749034335
-
On changing continuous attributes into ordered discrete attributes
-
Porto, Portugal: Springer-Verlag New York, Inc
-
Catlett J. On changing continuous attributes into ordered discrete attributes. Proceedings of the European working session on learning on Machine learning 1991, 164-178. Porto, Portugal: Springer-Verlag New York, Inc.
-
(1991)
Proceedings of the European working session on learning on Machine learning
, pp. 164-178
-
-
Catlett, J.1
-
11
-
-
85139983802
-
Supervised and Unsupervised Discretization of Continuous Features
-
Dougherty J, Kohavi R, Sahami M. Supervised and Unsupervised Discretization of Continuous Features. Proceedings of the Twelfth International Conference on Machine Learning: 1995; Tahoe City, California, USA 1995, 194-202.
-
(1995)
Proceedings of the Twelfth International Conference on Machine Learning: 1995; Tahoe City, California, USA
, pp. 194-202
-
-
Dougherty, J.1
Kohavi, R.2
Sahami, M.3
-
13
-
-
0001457509
-
Some Methods for Classification and Analysis of MultiVariate Observations
-
University of California Press, Cam LML, Neyman J
-
MacQueen JB. Some Methods for Classification and Analysis of MultiVariate Observations. Proc of the fifth Berkeley Symposium on Mathematical Statistics and Probability 1967, 1:281-297. University of California Press, Cam LML, Neyman J.
-
(1967)
Proc of the fifth Berkeley Symposium on Mathematical Statistics and Probability
, vol.1
, pp. 281-297
-
-
MacQueen, J.B.1
-
14
-
-
70349971935
-
ReTRN: A retriever of real transcriptional regulatory network and expression data for evaluating structure learning algorithm
-
10.1016/j.ygeno.2009.08.009, 19712740
-
Li Y, Zhu Y, Bai X, Cai H, Ji W, Guo D. ReTRN: A retriever of real transcriptional regulatory network and expression data for evaluating structure learning algorithm. Genomics 2009, 94(5):349-354. 10.1016/j.ygeno.2009.08.009, 19712740.
-
(2009)
Genomics
, vol.94
, Issue.5
, pp. 349-354
-
-
Li, Y.1
Zhu, Y.2
Bai, X.3
Cai, H.4
Ji, W.5
Guo, D.6
-
15
-
-
33747379083
-
The Forkhead transcription factor Hcm1 regulates chromosome segregation genes and fills the S-phase gap in the transcriptional circuitry of the cell cycle
-
10.1101/gad.1450606, 1553209, 16912276
-
Pramila T, Wu W, Miles S, Noble WS, Breeden LL. The Forkhead transcription factor Hcm1 regulates chromosome segregation genes and fills the S-phase gap in the transcriptional circuitry of the cell cycle. Genes Dev 2006, 20(16):2266-2278. 10.1101/gad.1450606, 1553209, 16912276.
-
(2006)
Genes Dev
, vol.20
, Issue.16
, pp. 2266-2278
-
-
Pramila, T.1
Wu, W.2
Miles, S.3
Noble, W.S.4
Breeden, L.L.5
-
16
-
-
38549135468
-
YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in Saccharomyces cerevisiae
-
2238916, 18032429
-
Monteiro PT, Mendes ND, Teixeira MC, d'Orey S, Tenreiro S, Mira NP, Pais H, Francisco AP, Carvalho AM, Lourenco AB, et al. YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in Saccharomyces cerevisiae. Nucleic Acids Res 2008, (36 Database):D132-136. 2238916, 18032429.
-
(2008)
Nucleic Acids Res
, Issue.36 DATABASE
-
-
Monteiro, P.T.1
Mendes, N.D.2
Teixeira, M.C.3
d'Orey, S.4
Tenreiro, S.5
Mira, N.P.6
Pais, H.7
Francisco, A.P.8
Carvalho, A.M.9
Lourenco, A.B.10
-
17
-
-
33644873683
-
The YEASTRACT database: a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae
-
10.1093/nar/gkj013, 1347376, 16381908
-
Teixeira MC, Monteiro P, Jain P, Tenreiro S, Fernandes AR, Mira NP, Alenquer M, Freitas AT, Oliveira AL, Sa-Correia I. The YEASTRACT database: a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae. Nucleic Acids Res 2006, (34 Database):D446-451. 10.1093/nar/gkj013, 1347376, 16381908.
-
(2006)
Nucleic Acids Res
, Issue.34 DATABASE
-
-
Teixeira, M.C.1
Monteiro, P.2
Jain, P.3
Tenreiro, S.4
Fernandes, A.R.5
Mira, N.P.6
Alenquer, M.7
Freitas, A.T.8
Oliveira, A.L.9
Sa-Correia, I.10
-
18
-
-
34249832377
-
A Bayesian method for the induction of probabilistic networks from data
-
Cooper GF, Herskovits E. A Bayesian method for the induction of probabilistic networks from data. Machine Learning 1992, 9(4):309-347.
-
(1992)
Machine Learning
, vol.9
, Issue.4
, pp. 309-347
-
-
Cooper, G.F.1
Herskovits, E.2
-
19
-
-
33947305781
-
ARACNE: an algorithm for the reconstruction of gene regulatory 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 the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics 2006, 7(Suppl 1):S7. 10.1186/1471-2105-7-S1-S7, 1810318, 16723010.
-
(2006)
BMC Bioinformatics
, vol.7
, Issue.SUPPL 1
-
-
Margolin, A.A.1
Nemenman, I.2
Basso, K.3
Wiggins, C.4
Stolovitzky, G.5
Dalla Favera, R.6
Califano, A.7
-
20
-
-
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
-
22
-
-
36248944068
-
Inference of genetic regulatory networks with recurrent neural network models using particle swarm optimization
-
10.1109/TCBB.2007.1057, 17975278
-
Xu R, Wunsch Ii D, Frank R. Inference of genetic regulatory networks with recurrent neural network models using particle swarm optimization. IEEE/ACM Trans Comput Biol Bioinform 2007, 4(4):681-692. 10.1109/TCBB.2007.1057, 17975278.
-
(2007)
IEEE/ACM Trans Comput Biol Bioinform
, vol.4
, Issue.4
, pp. 681-692
-
-
Xu, R.1
Wunsch Ii, D.2
Frank, R.3
|