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A large number of long non-coding RNAs (lncRNAs) have been identified over the past decades. Accumulating evidence proves that lncRNAs play key roles in various biological processes. However, the majority of the lncRNAs have not been functionally characterized. The annotation of lncRNA functions has become an area of focus in the fields of biology and bioinformatics. In this paper, we develop a global...
Heterogeneous data sources and multi-label are two important characteristics of protein function prediction. They describe protein data from two different aspects. However, it is of considerable challenge to integrate multiple data sources and multi-label simultaneously for predicting protein functions, especially when there are only a limited number of labeled proteins. In this paper, we propose...
In this paper, we propose algorithms for biomolecular docking sites selection problem by various machine learning approaches with selective features reduction. The proposed method can reduce the number of various amino acid features before constructing machine learning prediction models. Given frame boxes with features, the proposed method analyzes the important features by correlation coefficients...
Essential proteins play a crucial role in the survival and development process of life, as they provide all available nutrients to maintain life. Therefore, many researchers pay attention to the identification of essential proteins. As experiments methods are usually costly and time-consuming, more and more computational algorithms have been developed to discover essential proteins based on biological...
In general, the gap is broadening rapidly between the number of known protein sequences and the number of known protein structural classes. To overcome this crisis, it is essential to develop a computational prediction method for fast and precisely determining the protein structural class. Based on the predicted secondary structure information, the protein structural classes are predicted. To evaluate...
Network pharmacology has become the new approach for drug mechanism research and novel drug design. Drug target prediction based on computational approach became one of the primary approaches. However, due to the diversity and complexity of herbal chemical structures, the performance of herb target prediction based on chemical structure similarity is limited by the quality and the data availability...
Chloroplasts are organelles in most green plant and some algal cells. Identifying protein subchloroplast localization in chloroplast organelle is very helpful for understanding the function of chloroplast proteins. There have existed a few computational prediction methods for protein subchloroplast localization. However, these existing works have ignored proteins with multiple subchloroplast locations...
There is an important relationship between the stability of protein complex and hot region. Research has shown that in protein-protein interaction (PPI), residues are denser around the hot region. Therefore, this paper proposed an algorithm based on Gi statistics, regional division rule and regional amplification principle to form residue dense region (RDR); Then, according to the results of cascade...
Recent studies showed that protein-protein interaction network based features can significantly improve the prediction of protein subcellular localization. However, it is unclear whether network prediction models or other types of protein-protein correlation networks would also improve localization prediction. We present NetLoc, a novel diffusion kernel-based logistic regression (KLR) algorithm for...
In protein tertiary structure prediction, a crucial step is to select near-native structures from a large number of predicted structural models. Over the years, extensive research has been conducted for the protein structure selection problem with most approaches focusing on developing more accurate energy or scoring functions. Despite significant advances in this area, the discerning power of current...
Proteins function through interactions with other proteins, compounds, RNA and DNA. Prediction of protein interface sites is the key process for providing clues to the function of a protein, and is becoming increasing relevant to drug discovery. In this paper, combining the protein features with the theory of granular computing of quotient space based on protein-protein interaction sites classification...
Visible and near infrared spectroscopy (Vis/NIR) combined with chemometric methods was employed to classify rice wines with different ages. Spectra of 240 wine samples (80 for each year) were collected in the Vis/NIR region (325-1075nm) in the spectroradiometer in transmission mode. Partial least squares (PLS) analysis was applied to extract the principal components (PCs) as new eigenvectors to represent...
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