Gene clustering by using query-based self-organizing maps

Chang, Ray-I; Chu, Chih-Chun; Wu, Yuying; Chen, Yen-Liang

doi:10.1016/j.eswa.2010.03.050

Cited by 13 publications

(2 citation statements)

References 24 publications

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“…From this analysis, a total of 4802 DEGs were identified between TeQing and Lemont leaves. We used self-organizing maps (SOMs) to analyze patterns in gene expression ( Chang et al, 2010 ). A matrix of expression values for genes vs. samples was used as input data.…”

Section: Methodsmentioning

confidence: 99%

Comparative Transcriptome Analyses of Gene Expression Changes Triggered by Rhizoctonia solani AG1 IA Infection in Resistant and Susceptible Rice Varieties

Zhang

Chen

et al. 2017

Front. Plant Sci.

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Rice sheath blight, caused by Rhizoctonia solani, is one of the most devastating diseases for stable rice production in most rice-growing regions of the world. Currently, studies of the molecular mechanism of rice sheath blight resistance are scarce. Here, we used an RNA-seq approach to analyze the gene expression changes induced by the AG1 IA strain of R. solani in rice at 12, 24, 36, 48, and 72 h. By comparing the transcriptomes of TeQing (a moderately resistant cultivar) and Lemont (a susceptible cultivar) leaves, variable transcriptional responses under control and infection conditions were revealed. From these data, 4,802 differentially expressed genes (DEGs) were identified. Gene ontology and pathway enrichment analyses suggested that most DEGs and related metabolic pathways in both rice genotypes were common and spanned most biological activities after AG1 IA inoculation. The main difference between the resistant and susceptible plants was a difference in the timing of the response to AG1 IA infection. Photosynthesis, photorespiration, and jasmonic acid and phenylpropanoid metabolism play important roles in disease resistance, and the relative response of disease resistance-related pathways in TeQing leaves was more rapid than that of Lemont leaves at 12 h. Here, the transcription data include the most comprehensive list of genes and pathway candidates induced by AG1 IA that is available for rice and will serve as a resource for future studies into the molecular mechanisms of the responses of rice to AG1 IA.

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Section: Methodsmentioning

confidence: 99%

Comparative Transcriptome Analyses of Gene Expression Changes Triggered by Rhizoctonia solani AG1 IA Infection in Resistant and Susceptible Rice Varieties

Zhang

Chen

et al. 2017

Front. Plant Sci.

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“…21305 DEGs (Table S1) was normalized by using R language _scale, which is beneficial for the next step of SOM cluster analysis. The SOM approach was used to find a set of central points and map each object in the dataset to the corresponding central point under the most similar principle [24].…”

Section: Self-organizing Feature Mapanalysismentioning

confidence: 99%

Comparative Transcriptome Analysis of Gene Expression and Regulatory Characteristics Associated with Different Vernalization Periods in Brassica rapa

Dai

Zhang

Sun

et al. 2020

Genes

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Brassica rapa is an important Chinese vegetable crop that is beneficial to human health. The primary factor affecting B. rapa yield is low temperature, which promotes bolting and flowering, thereby lowering its commercial value. However, quickened bolting and flowering can be used for rapid breeding. Therefore, studying the underlying molecular mechanism of vernalization in B. rapa is crucial for solving production-related problems. Here, the transcriptome of two B. rapa accessions were comprehensively analyzed during different vernalization periods. During vernalization, a total of 974,584,022 clean reads and 291.28 Gb of clean data were obtained. Compared to the reference genome of B. rapa, 44,799 known genes and 2280 new genes were identified. A self-organizing feature map analysis of 21,035 differentially expressed genes was screened in two B. rapa accessions, ‘Jin Wawa’ and ‘Xiao Baojian’. The analysis indicated that transcripts related to the plant hormone signal transduction, starch and sucrose metabolism, photoperiod and circadian clock, and vernalization pathways changed notably at different vernalization periods. Moreover, different expression patterns of TPS, UGP, CDF, VIN1, and seven hormone pathway genes were observed during vernalization between the two accessions. The transcriptome results of this study provide a new perspective on the changes that occur during B. rapa vernalization, as well as serve as an excellent reference for B. rapa breeding.

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Free alignment classification of dikarya fungi using some machine learning methods

Rohani

Mamarabadi

2018

Neural Comput & Applic

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Gene clustering by using query-based self-organizing maps

Cited by 13 publications

References 24 publications

Comparative Transcriptome Analyses of Gene Expression Changes Triggered by Rhizoctonia solani AG1 IA Infection in Resistant and Susceptible Rice Varieties

Comparative Transcriptome Analyses of Gene Expression Changes Triggered by Rhizoctonia solani AG1 IA Infection in Resistant and Susceptible Rice Varieties

Comparative Transcriptome Analysis of Gene Expression and Regulatory Characteristics Associated with Different Vernalization Periods in Brassica rapa

Free alignment classification of dikarya fungi using some machine learning methods

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