METHODS: We introduce a new node representation method based on initial information fusion, called FFANE, which amalgamates PPI networks and protein sequence data to enhance the precision of PPIs' prediction. A Gaussian kernel similarity matrix is initially established by leveraging protein structural resemblances. Concurrently, protein sequence similarities are gauged using the Levenshtein distance, enabling the capture of diverse protein attributes. Subsequently, to construct an initial information matrix, these two feature matrices are merged by employing weighted fusion to achieve an organic amalgamation of structural and sequence details. To gain a more profound understanding of the amalgamated features, a Stacked Autoencoder (SAE) is employed for encoding learning, thereby yielding more representative feature representations. Ultimately, classification models are trained to predict PPIs by using the well-learned fusion feature.
RESULTS: When employing 5-fold cross-validation experiments on SVM, our proposed method achieved average accuracies of 94.28%, 97.69%, and 84.05% in terms of Saccharomyces cerevisiae, Homo sapiens, and Helicobacter pylori datasets, respectively.
CONCLUSION: Experimental findings across various authentic datasets validate the efficacy and superiority of this fusion feature representation approach, underscoring its potential value in bioinformatics.
METHODS: H. pylori infections were determined by in-house rapid urease test (iRUT), culture, histology and multiplex PCR.
RESULTS: A total of 140 (60.9%) from 230 patients were positive for H. pylori infection. H. pylori were detected in 9.6% (22/230), 17% (39/230), 12.6% (29/230) and 60% (138/230) of biopsy specimens by culture, iRUT, histology and mPCR, respectively. mPCR identified H. pylori infection in 100% of biopsies with positive histology and culture. All biopsies with positive iRUT yielded positive PCR except two cases. mPCR also detected H. pylori in additional 116, 101 and 109 biopsies that were negative by culture, iRUT and histology, respectively. Positive samples by mPCR showed lower average in H. pylori density, activity and inflammation scores. The Indians showed the highest prevalence of H. pylori infection compared to the Chinese and the Malays. In addition, Chinese patients with older age were significantly infected compared to other ethnicities.
CONCLUSION: PCR was able to detect the highest numbers of positive cases although the lowest average scores were recorded in the activity, inflammatory and H. pylori density.