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Algorithm for the Construction of a Global Enzymatic Network to be Used for Gene Network Reconstruction.

ABSTRACT: Relationships between genes are best represented using networks constructed from information of different types, with metabolic information being the most valuable and widely used for genetic network reconstruction. Other types of information are usually also available, and it would be desirable to systematically include them in algorithms for network reconstruction. Here, we present an algorithm to construct a global metabolic network that uses all available enzymatic and metabolic information about the organism. We construct a global enzymatic network (GEN) with a total of 4226 nodes (EC numbers) and 42723 edges representing all known metabolic reactions. As an example we use microarray data for Arabidopsis thaliana and combine it with the metabolic network constructing a final gene interaction network for this organism with 8212 nodes (genes) and 4606,901 edges. All scripts are available to be used for any organism for which genomic data is available.

SUBMITTER: Quintero A

PROVIDER: S-EPMC4245699 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Algorithm for the Construction of a Global Enzymatic Network to be Used for Gene Network Reconstruction.

Quintero Andrés A Ramírez Jorge J Leal Luis Guillermo LG López-Kleine Liliana L

Current genomics 20141001 5

Relationships between genes are best represented using networks constructed from information of different types, with metabolic information being the most valuable and widely used for genetic network reconstruction. Other types of information are usually also available, and it would be desirable to systematically include them in algorithms for network reconstruction. Here, we present an algorithm to construct a global metabolic network that uses all available enzymatic and metabolic information ...[more]

PMID: 25435802

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Project description:Gene sequencing technology has been playing an important role in many aspects, such as life science, disease medicine and health medicine, particularly in the extremely tough process of fighting against 2019-novel coronavirus. Drawing DNA restriction map is a particularly important technology in genetic biology. The simplified partial digestion method (SPDP), a biological method, has been widely used to cut DNA molecules into DNA fragments and obtain the biological information of each fragment. In this work, we propose an algorithm based on 0-1 planning for the location of restriction sites on a DNA molecule, which is able to solve the problem of DNA fragment reconstruction just based on data of fragments' length. Two specific examples are presented in detail. Furthermore, based on 1000 groups of original DNA sequences randomly generated, we define the coincidence rate and unique coincidence rate between the reconstructed DNA sequence and the original DNA sequence, and then analyze separately the effect of the number of fragments and the maximum length of DNA fragments on the coincidence rate and unique coincidence rate as defined. The effectiveness of the algorithm is proved. Besides, based on the existing optimization solution obtained, we simulate and discuss the influence of the error by computation method. It turns out that the error of position of one restriction site does not affect other restriction sites and errors of most restriction sites may lead to the failure of sequence reconstruction. Matlab 7.1 program is used to solve feasible solutions of the location of restriction sites, derive DNA fragment sequence and carry out the statistical analysis and error analysis. This paper focuses on basic computer algorithm implementation of rearrangement and sequencing rather than biochemical technology. The innovative application of the mathematical idea of 0-1 planning to DNA sequence mapping construction, to a certain extent, greatly simplifies the difficulty and complexity of calculation and accelerates the process of 'jigsaw' of DNA fragments.

Dataset Information

Algorithm for the Construction of a Global Enzymatic Network to be Used for Gene Network Reconstruction.

Publications

Algorithm for the Construction of a Global Enzymatic Network to be Used for Gene Network Reconstruction.

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