دورية أكاديمية
Application of coincidence index in the discovery of co-expressed metabolic pathways.
| العنوان: | Application of coincidence index in the discovery of co-expressed metabolic pathways. |
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| المؤلفون: | Cassucci Dos Santos JP; Scientific Computing Group, São Carlos institute of Physics, São Carlos, São Paulo, Brazil., Bruno OM; Scientific Computing Group, São Carlos institute of Physics, São Carlos, São Paulo, Brazil. |
| المصدر: | Physical biology [Phys Biol] 2024 Aug 29; Vol. 21 (5). Date of Electronic Publication: 2024 Aug 29. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Institute of Physics Pub Country of Publication: England NLM ID: 101197454 Publication Model: Electronic Cited Medium: Internet ISSN: 1478-3975 (Electronic) Linking ISSN: 14783967 NLM ISO Abbreviation: Phys Biol Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Bristol, UK : Institute of Physics Pub., c2004- |
| مواضيع طبية MeSH: | Escherichia coli*/genetics , Escherichia coli*/metabolism , Metabolic Networks and Pathways* , Halobacterium salinarum*/metabolism , Halobacterium salinarum*/genetics, Gene Expression Profiling/methods ; Computational Biology ; Transcriptome ; Algorithms ; RNA-Seq |
| مستخلص: | Analyzing transcription data requires intensive statistical analysis to obtain useful biological information and knowledge. A significant portion of this data is affected by random noise or even noise intrinsic to the modeling of the experiment. Without robust treatment, the data might not be explored thoroughly, and incorrect conclusions could be drawn. Examining the correlation between gene expression profiles is one way bioinformaticians extract information from transcriptomic experiments. However, the correlation measurements traditionally used have worrisome shortcomings that need to be addressed. This paper compares five already published and experimented-with correlation measurements to the newly developed coincidence index, a similarity measurement that combines Jaccard and interiority indexes and generalizes them to be applied to vectors containing real values. We used microarray and RNA-Seq data from the archaeon Halobacterium salinarum and the bacterium Escherichia coli , respectively, to evaluate the capacity of each correlation/similarity measurement. The utilized method explores the co-expressed metabolic pathways by measuring the correlations between the expression levels of enzymes that share metabolites, represented in the form of a weighted graph. It then searches for local maxima in this graph using a simulated annealing algorithm. We demonstrate that the coincidence index extracts larger, more comprehensive, and more statistically significant pathways for microarray experiments. In RNA-Seq experiments, the results are more limited, but the coincidence index managed the largest percentage of significant components in the graph. (© 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.) |
| فهرسة مساهمة: | Keywords: coincidence index; graph theory; halobacterium salinarum; systems biology |
| تواريخ الأحداث: | Date Created: 20240729 Date Completed: 20240829 Latest Revision: 20240829 |
| رمز التحديث: | 20240831 |
| DOI: | 10.1088/1478-3975/ad68b6 |
| PMID: | 39074502 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1478-3975 |
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| DOI: | 10.1088/1478-3975/ad68b6 |