-
1
-
-
0032616683
-
Identification of genetic networks from a small number of gene expression patterns under the boolean network model
-
K. S.
-
T. Akutsu, S. Miyano, and K. S. Identification of genetic networks from a small number of gene expression patterns under the boolean network model. In Proceedings of the Pacific Symposium on Biocomputing, pages 17-28, 1999.
-
(1999)
Proceedings of the Pacific Symposium on Biocomputing
, pp. 17-28
-
-
Akutsu, T.1
Miyano, S.2
-
3
-
-
0033707946
-
Using Bayesian networks to analyse expression data
-
Mary Ann Liebert, Inc.
-
N. Friedman, M. Linial, I. Nachman, and D. Pe'er. Using bayesian networks to analyse expression data. In Journal of Computational Biology, volume 7, pages 601-620. Mary Ann Liebert, Inc., 2000.
-
(2000)
Journal of Computational Biology
, vol.7
, pp. 601-620
-
-
Friedman, N.1
Linial, M.2
Nachman, I.3
Pe'er, D.4
-
4
-
-
68349161006
-
Reverse engineering of gene regulatory networks: A comparative study
-
Hindawi Publishing Corp.
-
H. Hache, H. Lehrach, and R. Herwig. Reverse engineering of gene regulatory networks: A comparative study. In EURASIP Journal on Bioinformatics and Systems Biology, volume 2009, pages 8:1-8:12. Hindawi Publishing Corp., 2009.
-
(2009)
EURASIP Journal on Bioinformatics and Systems Biology
, vol.2009
, pp. 81-812
-
-
Hache, H.1
Lehrach, H.2
Herwig, R.3
-
5
-
-
0014489272
-
Metabolic stability and epigenesis in randomly constructed genetic nets
-
March
-
S. A. Kauffman. Metabolic stability and epigenesis in randomly constructed genetic nets. J Theor Biol, 22(3):437-467, March 1969.
-
(1969)
J Theor Biol
, vol.22
, Issue.3
, pp. 437-467
-
-
Kauffman, S.A.1
-
8
-
-
0038047901
-
On learning gene regulatory networks under the boolean network model
-
Kluwer Academic Publishers
-
H. Lähdesmäki, I. Shmulevich, and O. Yli-Harja. On learning gene regulatory networks under the boolean network model. In Machine Learning, volume 52, pages 147-167. Kluwer Academic Publishers, 2003.
-
(2003)
Machine Learning
, vol.52
, pp. 147-167
-
-
Lähdesmäki, H.1
Shmulevich, I.2
Yli-Harja, O.3
-
9
-
-
0031616241
-
REVEAL, a general reverse engineering algorithm for inference of genetic network architectures
-
S. Liang, S. Fuhrman, and R. Somogyi. REVEAL, a general reverse engineering algorithm for inference of genetic network architectures. In Proceedings of the Pacific Symposium on Biocomputing, volume 1998, pages 18-29, 1998.
-
(1998)
Proceedings of the Pacific Symposium on Biocomputing
, vol.1998
, pp. 18-29
-
-
Liang, S.1
Fuhrman, S.2
Somogyi, R.3
-
11
-
-
33749005690
-
An efficient top-down search algorithm for learning Boolean networks of gene expression
-
DOI 10.1007/s10994-006-9014-z
-
D. Nam, S. Seo, and S. Kim. An efficient top-down search algorithm for learning boolean networks of gene expression. In Machine Learning, volume 65, pages 229-245. Springer Science, 2006. (Pubitemid 44451199)
-
(2006)
Machine Learning
, vol.65
, Issue.1
, pp. 229-245
-
-
Nam, D.1
Seo, S.2
Kim, S.3
-
12
-
-
10244244945
-
Single-layer artificial neural networks for gene expression analysis
-
DOI 10.1016/j.neucom.2003.10.017, PII S0925231203005277
-
A. Narayanan, E. C. Keedwell, J. Gamalielsson, and S. Tatineni. Single-layer artificial neural networks for gene expression analysis. In Neurocomputing, volume 61, pages 217-240. Elsevier, 2004. (Pubitemid 39618378)
-
(2004)
Neurocomputing
, vol.61
, Issue.1-4
, pp. 217-240
-
-
Narayanan, A.1
Keedwell, E.C.2
Gamalielsson, J.3
Tatineni, S.4
-
13
-
-
32444432616
-
Inference of gene regulatory networks using S-system and Differential Evolution
-
DOI 10.1145/1068009.1068079, GECCO 2005 - Genetic and Evolutionary Computation Conference
-
N. Noman and H. Iba. Inference of gene regulatory networks using s-system and differential evolution. In Proceedings of the 2005 Genetic and Evolutionary Computation Congress, pages 439-446. ACM, 2005. (Pubitemid 43226322)
-
(2005)
GECCO 2005 - Genetic and Evolutionary Computation Conference
, pp. 439-446
-
-
Noman, N.1
Iba, H.2
-
14
-
-
33947107404
-
Evolutionary computation in bioinformatics: A review
-
DOI 10.1109/TSMCC.2005.855515
-
S. K. Pal, S. Bandyopadhyay, and S. S. Ray. Evolutionary computation in bioinformatics: A review. In IEEE Transactions on Systems, Man, And Cybernetics, volume 36, pages 601-615. IEEE CS, 2006. (Pubitemid 46405283)
-
(2006)
IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
, vol.36
, Issue.5
, pp. 601-615
-
-
Pal, S.K.1
Bandyopadhyay, S.2
Ray, S.S.3
-
15
-
-
0036627676
-
Reverse engineering of regulatory networks: Simulation studies on a genetic algorithm approach for ranking hypotheses
-
DOI 10.1016/S0303-2647(02)00019-9, PII S0303264702000199
-
D. Repsilber, H. Liljenstrom, and A. S. G. E. Reverse engineering of regulatory networks: simulation studies on a genetic algorithm approach for ranking hypotheses. In BioSystems, volume 66, pages 31-41. Elsevier, 2002. (Pubitemid 36169922)
-
(2002)
BioSystems
, vol.66
, Issue.1-2
, pp. 31-41
-
-
Repsilber, D.1
Liljenstrom, H.2
Andersson, S.G.E.3
-
16
-
-
17644427718
-
Causal protein-signaling networks derived from multiparameter single-cell data
-
DOI 10.1126/science.1105809
-
K. Sachs, O. Perez, D. Pe'er, D. A. Lauffenburger, and G. P. Nolan. Causal protein-signaling networks derived from multiparameter single-celldata. In Science, volume 308, pages 523-529. April 2005. (Pubitemid 40570578)
-
(2005)
Science
, vol.308
, Issue.5721
, pp. 523-529
-
-
Sachs, K.1
Perez, O.2
Pe'er, D.3
Lauffenburger, D.A.4
Nolan, G.P.5
-
17
-
-
77649176945
-
Comparison of evolutionary algorithms in gene regulatory network model inference
-
BioMed Central
-
A. Sîrbu, H. J. Ruskin, and M. Crane. Comparison of evolutionary algorithms in gene regulatory network model inference. In BMC Bioinformatics, volume 11, page 59. BioMed Central, 2010.
-
(2010)
BMC Bioinformatics
, vol.11
, pp. 59
-
-
Sîrbu, A.1
Ruskin, H.J.2
Crane, M.3
-
18
-
-
35048877156
-
Optimizing topology and parameters of gene regulatory network models from time-series experiments
-
C. Spieth, F. Streichert, N. Speer, and A. Zell. Optimizing topology and parameters of gene regulatory network models from time-series experiments. In Proceedings of the 2004 Genetic and Evolutionary Computation Congress, pages 461-470. Springer-Verlag, 2004. (Pubitemid 39747238)
-
(2004)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
, vol.3102
, pp. 461-470
-
-
Spieth, C.1
Streichert, F.2
Speer, N.3
Zell, A.4
-
19
-
-
33750016109
-
Inferring gene regulatory networks from multiple microarray datasets
-
DOI 10.1093/bioinformatics/btl396
-
Y. Wang, T. Joshi, X. Zhang, D. Xu, and L. Chen. Inferring gene regulatory networks from multiple microarray datasets. In Bioinformatics, volume 22, pages 2413-2420. Oxford University Press, 2006. (Pubitemid 44566971)
-
(2006)
Bioinformatics
, vol.22
, Issue.19
, pp. 2413-2420
-
-
Wang, Y.1
Joshi, T.2
Zhang, X.-S.3
Xu, D.4
Chen, L.5
-
20
-
-
46049101810
-
Gene regulatory network reconstruction by bayesian integration of prior knowledge and/or different experimental conditions
-
DOI 10.1142/S0219720008003539, PII S0219720008003539
-
A. V. Werhli and D. Husmeier. Gene regulatory network reconstruction by bayesian integration of prior knowledge and/or different experimental conditions. In Journal of Bioinformatics and Computational Biology, volume 6, pages 543-572. 2008. (Pubitemid 351895193)
-
(2008)
Journal of Bioinformatics and Computational Biology
, vol.6
, Issue.3
, pp. 543-572
-
-
Werhli, A.V.1
Husmeier, D.2
-
21
-
-
33748654580
-
Inferring gene regulatory networks from time series data using the minimum description length principle
-
DOI 10.1093/bioinformatics/btl364
-
W. Zhao, S. Erchin, and E. R. Dougherty. Inferring gene regulatory networks from time series data using the minimum description length principle. In Bioinformatics, volume 22, pages 2129-2135. 2006. (Pubitemid 44390904)
-
(2006)
Bioinformatics
, vol.22
, Issue.17
, pp. 2129-2135
-
-
Zhao, W.1
Serpedin, E.2
Dougherty, E.R.3
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