Inferring gene correlation networks from transcription factor binding sites
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- Mahdevar Ghasem
- Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran
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- Nowzari-Dalini Abbas
- Department of Computer Science, School of Mathematics, Statistics, and Computer Science, University of Tehran
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- Sadeghi Mehdi
- National Institute of Genetic Engineering and Biotechnology School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM)
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Abstract
Gene expression is a highly regulated biological process that is fundamental to the existence of phenotypes of any living organism. The regulatory relations are usually modeled as a network; simply, every gene is modeled as a node and relations are shown as edges between two related genes. This paper presents a novel method for inferring correlation networks, networks constructed by connecting co-expressed genes, through predicting co-expression level from genes promoter’s sequences. According to the results, this method works well on biological data and its outcome is comparable to the methods that use microarray as input. The method is written in C++ language and is available upon request from the corresponding author.
Journal
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- Genes & Genetic Systems
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Genes & Genetic Systems 88 (5), 301-309, 2013
The Genetics Society of Japan
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Details 詳細情報について
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- CRID
- 1390001205472927872
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- NII Article ID
- 130003390811
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- NII Book ID
- AA11077421
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- COI
- 1:STN:280:DC%2BC2cngtVyjsg%3D%3D
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- ISSN
- 18805779
- 13417568
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- NDL BIB ID
- 025366268
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- PubMed
- 24694393
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
- PubMed
- CiNii Articles
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- Abstract License Flag
- Disallowed