Current Bioinformatics - Volume 15, Issue 7, 2020

In the field of bioinformatics, the prediction of phage virion proteins helps us understand the interaction between phage and its host cells and promotes the development of new antibacterial drugs. However, traditional experimental methods to identify phage virion proteins are expensive and inefficient, more researchers are working to develop new computational methods. In this review, we summarized the machine learn Read More

Background: In the field of personalized health, it is often difficult for individuals to obtain professional knowledge to solve their practical problems timely and accurately. While there are some applications that can get targeted information, they often fail to function properly in nonideal environments, and they cannot achieve precise answers to individual users. Therefore, how to establish an information capture model b Read More

Background: Causal mediation analysis is conducted in biomedical research with the goal of investigating causal mechanisms that consist of both direct causal pathways between the treatment and outcome variables and intermediate causal pathways through mediators. Recently, this type of analysis has been applied in the context of bioinformatics; however, it encounters the obstacle of high-dimensional and semi-continuous Read More

Background: The evolutionary history of organisms can be described by phylogenetic trees. We need to compare the topologies of rooted phylogenetic trees when researching the evolution of a given set of species. Objective: Up to now, there are several metrics measuring the dissimilarity between rooted phylogenetic trees, and those metrics are defined by different ways. Methods: This paper analyzes those m Read More

Background: Cancer threatens human health seriously. Diagnosing cancer via gene expression analysis is a hot topic in cancer research. Objective: The study aimed to diagnose the accurate type of lung cancer and discover the pathogenic genes. Methods: In this study, Affinity Propagation (AP) clustering with similarity score was employed to each type of lung cancer and normal lung. After grouping genes, sparse group lasso wa Read More

Background: The Gene Regulatory Network (GRN) is a model for studying the function and behavior of genes by treating the genome as a whole, which can reveal the gene expression mechanism. However, due to the dynamics, nonlinearity, and complexity of gene expression data, it is a challenging task to construct a GRN precisely. And in the circulating cooling water system, the Slime-Forming Bacteria (SFB) is one of the Read More

Introduction: Neddylation is the process of ubiquitin-like protein NEDD8 attaching substrate lysine via isopeptide bonds. As a highly dynamic and reversible post-translational modification, lysine neddylation has been found to be involved in various biological processes and closely associated with many diseases. Objective: The accurate identification of neddylation sites is necessary to elucidate the underlying molecular mecha Read More

Background: The basic building block of a body is protein which is a complex system whose structure plays a key role in activation, catalysis, messaging and disease states. Therefore, careful investigation of protein structure is necessary for the diagnosis of diseases and for the drug designing. Protein structures are described at their different levels of complexity: primary (chain), secondary (helical), tertiary (3D), and Read More

Objective: This study proposed an innovative approach to simplify the multiple psychological scales for children and adolescents by integrating statistical methods and item reflection theory into a structural equation model. Methods: First, a psychological scale for adolescents to replace the existing scales optimized for adults with the Delphi method has been developed. Second, the number of items in the current group of sc Read More

Background: At present, using computer methods to predict drug-target interactions (DTIs) is a very important step in the discovery of new drugs and drug relocation processes. The potential DTIs identified by machine learning methods can provide guidance in biochemical or clinical experiments. Objective: The goal of this article is to combine the latest network representation learning methods for drug-target predicti Read More

Background: The comparison of the protein sequences is an important research filed in bioinformatics. Many alignment-free methods have been proposed. Objective: In order to mining the more information of the protein sequence, this study focus on a new alignment-free method based on physiochemical properties of amino acids. Methods: Average physiochemical value (Apv) has been defined. For a given protein sequenc Read More

Background: Protein secondary structure prediction (PSSP) is a fundamental task in bioinformatics that is helpful for understanding the three-dimensional structure and biological function of proteins. Many neural network-based prediction methods have been developed for protein secondary structures. Deep learning and multiple features are two obvious means to improve prediction accuracy. Objective: To promot Read More

Background: Systemic lupus erythematosus (SLE) is a complex autoimmune disease, which mainly affects childbearing-aged women. Although its pathogenesis is not fully clear yet, studies have shown that genetic factors are vital in exploring SLE pathogenic mechanisms. Objective: The purpose of this study is to predict and screen potential pathogenic single nucleotide polymorphisms (SNPs). By comparing the genomes Read More

Background: The high incidence rate of prostate disease poses a requirement of accurate early detection. Magnetic Resonance Imaging (MRI) is one of the main imaging methods used for prostate cancer detection so far, but it has problems of imbalance and variation in appearance, therefore, automated prostate segmentation is still challenging. Objective: Aiming to accurately segment the prostate from MRI, the foc Read More