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Keywords
(12)
Biological Network
Boolean Function
Computational Molecular Biology
Dna Microarray
Efficient Algorithm
Gene Expression Data
Gene Expression Profile
Genetic Network
Matrix Multiplication
Monte Carlo
Randomized Algorithm
Boolean Network
Related Publications
(24)
Identification of Genetic Networks from a Small Number of Gene Expression Patterns Under the Boolean Network Model
Algorithms For Inferring Qualitative Models Of Biological Networks
Modeling Gene Expression with Differential Equations
Modeling Regulatory Networks with Weight Matrices
Genetic network inference: from coexpression clustering to reverse engineering
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Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function
Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function,10.1145/332306.332
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Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function
(
Citations: 82
)
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Tatsuya Akutsu
,
Satoru Miyano
,
Satoru Kuhara
Due to the recent progress of the
DNA microarray
technology, a large number of
gene expression profile
data are being produced. How to analyze
gene expression data
is an important topic in
computational molecular biology
Several studies have been done using the
Boolean network
as a model of a
genetic network
This paper proposes efficient algorithms for identifying Boolean networks of bounded indegree and related biological networks, where identification of a
Boolean network
can be formalized as a problem of identifying many Boolean functions simultaneously. For the identification of a Boolean network, an O(mnD+1) time naive algorithm and a simple O(mnD) time algorithm are known, where n denotes the number of nodes, m denotes the number of examples, and D denotes the maximum indegree. This paper presents an improved O(mw2nD + mnD+w3) time MonteCarlo type randomized algorithm, where w is the exponent of
matrix multiplication
(currently, w
Conference:
Research in Computational Molecular Biology  RECOMB
, vol. 7, no. 34, pp. 814, 2000
DOI:
10.1145/332306.332317
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Citation Context
(43)
...Then another identification algorithm based on matrix multiplication and fingerprint function was proposed by them [
17
]...
Daizhan Cheng
,
et al.
Model Construction of Boolean Network via Observed Data
...Genetic networks can, in principle, be described by a directed graph. Such modeling invokes a Boolean relationships among the nodes of a network; that is, if gene A is connected with gene B by a logical relationship, then if A is ON, B is also ON (if the relationship is positive) or OFF (if the relationship is negative). For these networks, it is quite easy to calculate terminal states as attractors or basins of attraction, and from this point of view, they have been extensively studied
...
Eliska Vohradska
,
et al.
Virtual Mutagenesis of the Yeast Cyclins Genetic Network Reveals Compl...
...networks [29, 4, 5]; (ii) identification of Boolean networks [34, 1,
2
]; (iii) control of Boolean networks, [3, 7, 26]; (iv) stochastic Boolean networks, [48, 27, 43], (v) applications to Systems Biology, [49, 40, 32]...
Daizhan Cheng
,
et al.
Synthesis of Boolean networks via semitensor product
...Present methods of learning Regulatory Network (RN) based on microarray expressions mainly comprise Boolean network[
2
, 3], Bayesian network[4, 5] and differential equations (DE) model, among them DE describes the cell...
Qiang Bo
,
et al.
Application of Unscented Particle Filtering for Estimating Parameters ...
...Several mathematical methods for modelling the genetic networks have been proposed such as Boolean networks [
3
], differential equations [4], Bayesian networks [5], and Petri Net [6]...
HsiangYuan Yeh
,
et al.
Identifying significant genetic regulatory networks in the prostate ca...
References
(22)
On the Complexity of Inferring Functional Dependencies
(
Citations: 46
)
Heikki Mannila
,
Karijouko Räihä
Journal:
Discrete Applied Mathematics  DAM
, vol. 40, no. 2, pp. 237243, 1992
Identification of Genetic Networks from a Small Number of Gene Expression Patterns Under the Boolean Network Model
(
Citations: 342
)
Tatsuya Akutsu
,
Satoru Miyano
,
Satoru Kuhara
Conference:
Pacific Symposium on Biocomputing
, pp. 1728, 1999
A Qualitative Physics Based on Confluences
(
Citations: 728
)
Johan De Kleer
,
John Seely Brown
Journal:
Artificial Intelligence  AI
, vol. 24, no. 13, pp. 783, 1984
Efficient randomized patternmatching algorithms
(
Citations: 390
)
Richard M. Karp
,
Michael O. Rabin
Published in 1987.
Qualitative analysis of gene networks
(
Citations: 73
)
D. Thieffry
,
R. Thomas
Conference:
Pacific Symposium on Biocomputing
, 1998
Sort by:
Citations
(82)
Model Construction of Boolean Network via Observed Data
(
Citations: 1
)
Daizhan Cheng
,
Hongsheng Qi
,
Zhiqiang Li
Journal:
IEEE Transactions on Neural Networks
, vol. 22, no. 4, pp. 525536, 2011
Virtual Mutagenesis of the Yeast Cyclins Genetic Network Reveals Complex Dynamics of Transcriptional Control Networks
Eliska Vohradska
,
Jiri Vohradsky
,
Christina Chan
Journal:
PLOS One
, vol. 6, no. 4, 2011
Synthesis of Boolean networks via semitensor product
Daizhan Cheng
,
Hongsheng Qi
,
Yin Zhao
Published in 2011.
Identification of genetic network dynamics with unate structure
(
Citations: 1
)
Riccardo Porreca
,
Eugenio Cinquemani
,
John Lygeros
,
Giancarlo FerrariTrecate
Journal:
Bioinformatics/computer Applications in The Biosciences  BIOINFORMATICS
, vol. 26, no. 9, pp. 12391245, 2010
Application of Unscented Particle Filtering for Estimating Parameters and Hidden Variables in Gene Regulatory Network
Qiang Bo
,
Wang ZhengZhi
Conference:
International Conference on Bioinformatics and Biomedical Engineering  ICBBE
, pp. 14, 2010