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Two FCA-Based Methods for Mining Gene Expression Data
[chapter]
2009
Lecture Notes in Computer Science
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Two methods based on FCA (Formal Concept Analysis) are considered for clustering gene expression data. ...
Gene expression data are numerical and describe the level of expression of genes in different situations, thus featuring behaviour of the genes. ...
Acknowledgments The third author was supported by the project of the Russian Foundation for Basic Research, grant no. 08-07-92497-NTsNIL a. ...
doi:10.1007/978-3-642-01815-2_19
fatcat:wbma4fxsuvav5nxp66266wr6mu
Formal concept analysis for knowledge discovery from biological data
2017
International Journal of Data Mining and Bioinformatics
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2015 pre-print arXiv:1506.00366v1 fatcat:s72jqpzjtndb7jmvxmdlsmprh4
This review paper presents the applications of formal concept analysis for the analysis and knowledge discovery from biological data, including gene expression discretization, gene co-expression mining ...
It also presents a list of FCA-based software tools applied in biological domain and covers the challenges faced so far. ...
To overcome these problems, Kaytoue-Uberall et al. (2009) [6] introduced two FCA-based methods for clustering gene expression data. ...
doi:10.1504/ijdmb.2017.10009312
fatcat:wdopyvkr4jh63loxlsv6z6dmie
Formal concept analysis in knowledge processing: A survey on applications
2013
Expert systems with applications
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In this second part, we zoom in on and give an extensive overview of the papers published between 2003 and 2011 which applied FCA-based methods for knowledge discovery and ontology engineering in various ...
These domains include software mining, web analytics, medicine, biology and chemistry data. ...
Acknowledgements We are grateful to Paul Elzinga for his help in composing the concept lattices. ...
doi:10.1016/j.eswa.2013.05.009
fatcat:axr4d7jylbbvzlh5sclfiqkxaa
USING FORMAL CONCEPT ANALYSIS FOR MICROARRAY DATA COMPARISON
2007
Proceedings of the 5th Asia-Pacific Bioinformatics Conference
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Microarray technologies, which can measure tens of thousands of gene expression values simultaneously in a single experiment, have become a common research method for biomedical researchers. ...
For microarray data, each vertex of the lattice corresponds to a subset of genes that are grouped together according to their expression values and some biological information related to gene function. ...
Background on FCA Formal Concept Analysis (FCA) [6] is a method that is based on lattice theory for the analysis of binary relational data. It was introduced by Rudolf Wille in 1980s. ...
doi:10.1142/9781860947995_0009
fatcat:obz5sniz65bbnorvoxaa5tojkq
USING FORMAL CONCEPT ANALYSIS FOR MICROARRAY DATA COMPARISON
2008
Journal of Bioinformatics and Computational Biology
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Microarray technologies, which can measure tens of thousands of gene expression values simultaneously in a single experiment, have become a common research method for biomedical researchers. ...
For microarray data, each vertex of the lattice corresponds to a subset of genes that are grouped together according to their expression values and some biological information related to gene function. ...
Background on FCA Formal Concept Analysis (FCA) [6] is a method that is based on lattice theory for the analysis of binary relational data. It was introduced by Rudolf Wille in 1980s. ...
doi:10.1142/s021972000800328x
pmid:18324746
fatcat:lvatisajgfazhnt52agcam4hxi
Formal Concept Analysis and Knowledge Integration for Highlighting Statistically Enriched Functions from Microarrays Data
2014
International Work-Conference on Bioinformatics and Biomedical Engineering
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After that, Formal Concept Analysis (FCA) is applied for extracting formal concepts regrouping genes having similar transcriptomic profiles and functional behaviors. ...
knowledge bases. ...
Discussions and Conclusion We presented in this paper a method for data mining and knowledge discovery from gene expression data. ...
dblp:conf/iwbbio/Benabderrahmane14
fatcat:tbe4fx7lfjbujgjlckflxuw7ii
Mining gene expression data with pattern structures in formal concept analysis
2011
Information Sciences
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In the context of gene expression data analysis, we propose and compare two FCA-based methods for mining numerical data and we show that they are equivalent. ...
Experiments with real-world gene expression data are discussed and give a practical basis for the comparison and evaluation of the methods. ...
Acknowledgements The second author was supported by the project of the Russian Foundation for Basic Research, grant no. 08-07-92497-NTsNIL a. ...
doi:10.1016/j.ins.2010.07.007
fatcat:gqxivxkecnbtfohxfagsuzqas4
Contributions to Biclustering of Microarray Data Using Formal Concept Analysis
[article]
2018
arXiv
pre-print
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Biclustering is an unsupervised data mining technique that aims to unveil patterns (biclusters) from gene expression data matrices. ...
In the framework of this thesis, we propose new biclustering algorithms for microarray data. The latter is done using data mining techniques. ...
Discussion A new FCA-based biclustering method for gene expression data has been proposed. ...
arXiv:1811.09562v1
fatcat:koql6oifrvgsnk6j56bpne6jvm
Gene Co-Expression in Mouse Embryo Tissues
2013
International Journal of Intelligent Information Technologies
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This paper develops some existing ideas in FCA to provide an analysis of a large data set of mouse embryo gene expressions. ...
It develops new techniques for managing complexity and visualisation in FCA to identify and approximate large groups of co-expressed genes. ...
In particular it demonstrated how FCA can be used to analyse in situ gene expression data for the developmental mouse. ...
doi:10.4018/ijiit.2013100104
fatcat:lbc5lyxhvrfmtm34w3agor55f4
A formal concept analysis approach to consensus clustering of multi-experiment expression data
2014
BMC Bioinformatics
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Conclusions: The proposed FCA-enhanced consensus clustering technique is a general approach to the combination of clustering algorithms with FCA for deriving clustering solutions from multiple gene expression ...
Their performance is evaluated on gene expression data from multi-experiment study examining the global cell-cycle control of fission yeast. ...
Thus the authors further propose and compare two FCA-based methods for mining gene expression data and show that they are equivalent [31] . ...
doi:10.1186/1471-2105-15-151
pmid:24885407
pmcid:PMC4033618
fatcat:asv4es4ujnfnfcmbu3yhckqv4q
Interactive knowledge discovery and data mining on genomic expression data with numeric formal concept analysis
2016
BMC Bioinformatics
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Gene Expression Data (GED) analysis poses a great challenge to the scientific community that can be framed into the Knowledge Discovery in Databases (KDD) and Data Mining (DM) paradigm. ...
The ability of FCA-based bi-clustering methods to index external databases such as GO allows us to obtain a quality measure of the biclusters, to observe the evolution of a gene throughout the different ...
Availability of data and materials The dataset supporting the conclusions of this article is available in the Gene Expression Omnibus (GEO) repository http://www.ncbi.nlm.nih.gov/geo/ query/acc.cgi? ...
doi:10.1186/s12859-016-1234-z
pmid:27628041
pmcid:PMC5024470
fatcat:lievmaecvzegvdxsmr7vwohbbi
Formal Concept Analysis in Knowledge Discovery: A Survey
[chapter]
2010
Lecture Notes in Computer Science
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As a case study, we zoom in on the 140 papers on using FCA in knowledge discovery and data mining and give an extensive overview of the contents of this literature. ...
We use the visualization capabilities of FCA to explore the literature, to discover and conceptually represent the main research topics in the FCA community. ...
In Kaytone et al. (2009) , FCA is used for mining and clustering gene expression data. Fu (2006) applies FCA as a tool for analysis and visualization of data in a digital ecosystem. ...
doi:10.1007/978-3-642-14197-3_15
fatcat:e2d6pofivza6pcyn72m3tjrbda
Preface to the special issue on "Concept Lattice and their Applications" (CLA-2011)
2013
Annals of Mathematics and Artificial Intelligence
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Biclustering numerical data is a popular data-mining task aimed at several applications, e.g., gene expression data analysis and recommendation. ...
The two last papers are more related to applications of FCA. ...
doi:10.1007/s10472-013-9390-6
fatcat:2h5cspzoyvayjbibafs457zd2a
The CUBIST Project
2013
International Journal of Intelligent Information Technologies
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how strongly they are expressed -in tissues for genes and in cells for proteins). ...
An original attribute for Gender, for example, with the possible values Male and Female, is scaled in FCA as two formal attributes, Gender-Male and Gender-Female. ...
doi:10.4018/ijiit.2013100101
fatcat:z645pjxovra2ngsnmii3qbwfnu
Supporting scientific knowledge discovery with extended, generalized Formal Concept Analysis
2016
Expert systems with applications
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expression data analysis. ...
In this paper we fuse together the Landscapes of Knowledge of Wille's and Exploratory Data Analysis by leveraging Formal Concept Analysis (FCA) to support data-induced scientific enquiry and discovery. ...
Acknowledgments FJVA and AP were partially supported by EU FP7 project LiMo-SINe (contract 288024) for this research. ...
doi:10.1016/j.eswa.2015.09.022
fatcat:l7fequzx65hkxkrota5umcgtoa
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