Protein-protein interactions(PPIs)are of great importance to understand genetic mechanisms,delineate disease pathogenesis,and guide drug design.With the increase of PPI data and development of machine learning technol...Protein-protein interactions(PPIs)are of great importance to understand genetic mechanisms,delineate disease pathogenesis,and guide drug design.With the increase of PPI data and development of machine learning technologies,prediction and identification of PPIs have become a research hotspot in proteomics.In this study,we propose a new prediction pipeline for PPIs based on gradient tree boosting(GTB).First,the initial feature vector is extracted by fusing pseudo amino acid composition(Pse AAC),pseudo position-specific scoring matrix(Pse PSSM),reduced sequence and index-vectors(RSIV),and autocorrelation descriptor(AD).Second,to remove redundancy and noise,we employ L1-regularized logistic regression(L1-RLR)to select an optimal feature subset.Finally,GTB-PPI model is constructed.Five-fold cross-validation showed that GTB-PPI achieved the accuracies of 95.15% and 90.47% on Saccharomyces cerevisiae and Helicobacter pylori datasets,respectively.In addition,GTB-PPI could be applied to predict the independent test datasets for Caenorhabditis elegans,Escherichia coli,Homo sapiens,and Mus musculus,the one-core PPI network for CD9,and the crossover PPI network for the Wnt-related signaling pathways.The results show that GTB-PPI can significantly improve accuracy of PPI prediction.The code and datasets of GTB-PPI can be downloaded from https://github.com/QUST-AIBBDRC/GTB-PPI/.展开更多
Fig(Ficus carica L.)with purple-red peel cultivars are popular among consumers and exhibit better storability.While DNA methylation influences fruit ripening and color development,its specific role in fig fruit remain...Fig(Ficus carica L.)with purple-red peel cultivars are popular among consumers and exhibit better storability.While DNA methylation influences fruit ripening and color development,its specific role in fig fruit remains unclear.This study explores the impact of DNA methylation on the fig peel coloration.Enzymatic colorimetric detection revealed that the level of‘Purple Peel’fig DNA methylation decreases with fig fruit ripening and coloring.Treatment of young fruit with the DNA-methylation inhibitor azacytidine induced peel coloration,suggesting that a decrease in DNA-methylation level promotes fig peel coloration.Seven members of DNA methyltransferases and three members of DNA demethylases were identified from a high-level fig genome,highlighting FcMET1 and FcDRM2 as stable proteins,ensuring functional expression.Reference to the Arabidopsis protein interaction network map predicted that FcMET1 is in a central position,suggesting a crucial regulatory role in multiple biological processes.Correlation analysis revealed a positive correlation between FcMET1 expression during peel development and the level of total DNA methylation.Weighted gene co-expression network analysis identified co-expression of FcMET1 with the color-related transcription factors MYB,bHLH and WD40,as well as with eight structural genes in the flavonoid-biosynthesis pathway.The expression of FcUFGT3 was negatively correlated with that of FcMET1.McrBC-PCR and Bisulfite Sequencing detection showed that a low methylation level of the FcUFGT3 promoter corresponds with its high expression in colored fig.This investigation of the mechanism of DNA methylation provides a theoretical basis for understanding the role of DNA-methylation modifications in fig ripening and coloring.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.61863010)the Key Research and Development Program of Shandong Province of China(Grant No.2019GGX101001)the Natural Science Foundation of Shandong Province of China(Grant No.ZR2018MC007)。
文摘Protein-protein interactions(PPIs)are of great importance to understand genetic mechanisms,delineate disease pathogenesis,and guide drug design.With the increase of PPI data and development of machine learning technologies,prediction and identification of PPIs have become a research hotspot in proteomics.In this study,we propose a new prediction pipeline for PPIs based on gradient tree boosting(GTB).First,the initial feature vector is extracted by fusing pseudo amino acid composition(Pse AAC),pseudo position-specific scoring matrix(Pse PSSM),reduced sequence and index-vectors(RSIV),and autocorrelation descriptor(AD).Second,to remove redundancy and noise,we employ L1-regularized logistic regression(L1-RLR)to select an optimal feature subset.Finally,GTB-PPI model is constructed.Five-fold cross-validation showed that GTB-PPI achieved the accuracies of 95.15% and 90.47% on Saccharomyces cerevisiae and Helicobacter pylori datasets,respectively.In addition,GTB-PPI could be applied to predict the independent test datasets for Caenorhabditis elegans,Escherichia coli,Homo sapiens,and Mus musculus,the one-core PPI network for CD9,and the crossover PPI network for the Wnt-related signaling pathways.The results show that GTB-PPI can significantly improve accuracy of PPI prediction.The code and datasets of GTB-PPI can be downloaded from https://github.com/QUST-AIBBDRC/GTB-PPI/.
基金supported by 111 Project(Grant No.B17043)China Postdoctoral Science Foundation(Grant No.2022M723425).
文摘Fig(Ficus carica L.)with purple-red peel cultivars are popular among consumers and exhibit better storability.While DNA methylation influences fruit ripening and color development,its specific role in fig fruit remains unclear.This study explores the impact of DNA methylation on the fig peel coloration.Enzymatic colorimetric detection revealed that the level of‘Purple Peel’fig DNA methylation decreases with fig fruit ripening and coloring.Treatment of young fruit with the DNA-methylation inhibitor azacytidine induced peel coloration,suggesting that a decrease in DNA-methylation level promotes fig peel coloration.Seven members of DNA methyltransferases and three members of DNA demethylases were identified from a high-level fig genome,highlighting FcMET1 and FcDRM2 as stable proteins,ensuring functional expression.Reference to the Arabidopsis protein interaction network map predicted that FcMET1 is in a central position,suggesting a crucial regulatory role in multiple biological processes.Correlation analysis revealed a positive correlation between FcMET1 expression during peel development and the level of total DNA methylation.Weighted gene co-expression network analysis identified co-expression of FcMET1 with the color-related transcription factors MYB,bHLH and WD40,as well as with eight structural genes in the flavonoid-biosynthesis pathway.The expression of FcUFGT3 was negatively correlated with that of FcMET1.McrBC-PCR and Bisulfite Sequencing detection showed that a low methylation level of the FcUFGT3 promoter corresponds with its high expression in colored fig.This investigation of the mechanism of DNA methylation provides a theoretical basis for understanding the role of DNA-methylation modifications in fig ripening and coloring.
