Current Bioinformatics - Volume 17, Issue 5, 2022

The search for marker genes associated with different pathologies traditionally begins with some form of differential expression analysis. This step is essential in most functional genomics' works that analyze gene expression data. In the present article, we present a different analysis, starting from the known biological significance of different groups of genes and then assessing the proportion of differentially expressed genes. Read More

Background: DNA storage is becoming a global research hotspot in recent years, and today, most research focuses on storage density and big data. The security of DNA storage needs to be observed. Some DNA-based security methods were introduced for traditional information security problems. However, few encryption algorithms considered the limitation of biotechnology and applied it for DNA storage. The difference Read More

Background: Genomic data sets generated by several recent large scale high-throughput screening efforts pose a complex computational challenge for anticancer drug sensitivity prediction. Objective: We aimed to design an algorithm model that would predict missing elements in incomplete matrices and could be applicable to drug response prediction programs. Methods: We developed a novel self-expressive mat Read More

Background: SARS-CoV-2 has paralyzed mankind due to its high transmissibility and its associated mortality, causing millions of infections and deaths worldwide. The search for gene expression biomarkers from the host transcriptional response to infection may help understand the underlying mechanisms by which the virus causes COVID-19. This research proposes a smart methodology integrating different RNA-Se Read More

Background: Due to the limited amount of mRNA in single-cell, there are always many missing values in scRNA-seq data, making it impossible to accurately quantify the expression of singlecell RNA. The dropout phenomenon makes it impossible to detect the truly expressed genes in some cells, which greatly affects the downstream analysis of scRNA-seq data, such as cell cluster analysis and cell development trajectories. O Read More

Aims: This paper is intended to identify 5-methylcytosine sites in human promoters. Background: Aberrant DNA methylation patterns are often associated with tumor development. Moreover, hypermethylation inhibits the expression of tumor suppressor genes, and hypomethylation stimulates the expression of certain oncogenes. Most DNA methylation occurs on the CpGisland of the gene promoter region. Objective: Read More

Background: The most common joint illness is osteoarthritis (OA). The goal of this study was to find changes in gene signatures between normal knee joints and OA tissue samples and look for prospective gene targets for OA. Methods: The gene expression profiles of GSE12021, GSE51588, and GSE55457 were downloaded from Gene Expression Omnibus (GEO). A total of 64 samples (40 OA and 24 standard control samples) Read More

Background: DNA N6-methyladenine plays an important role in the restriction-modification system to isolate invasion from adventive DNA. The shortcomings of the high time consumption and high costs of experimental methods have been exposed, and some computational methods have emerged. The support vector machine theory has received extensive attention in the bioinformatics field due to its solid theoretical foun Read More