Current Bioinformatics - Volume 16, Issue 2, 2021

Background: Epigenetic repression mechanisms play an important role in gene regulation, specifically in cancer development. In many cases, a CpG island’s (CGI) susceptibility or resistance to methylation is shown to be contributed by local DNA sequence features. Objective: To develop unbiased machine learning models–individually and combined for different biological features–that predict the methylation propensity of Read More

Objective: To identify the possible virulence factors (VFs) of P. proliferus. Methods: By Illumina HiSeq 4000 RNA-Seq platform, transcriptomes of adult P. proliferus worms were sequenced to predict VFs via screening the homologues of traditional VFs of parasites based on the annotations in the functional databases. Homology analysis was also performed to screen homologous genes between P. proliferus and other four Para Read More

Background: Oral squamous cell carcinoma (OSCC) has been the sixth most common cancer worldwide. Emerging studies showed long non-coding RNAs to play a key role in human cancers. However, the molecular mechanisms underlying the initiation and progression of OSCC remained to be further explored. Objective: The present study aimed to identify differentially expressed lncRNAs and mRNAs in OSCC. Methods: GSE307 Read More

Background: Osteosarcoma (OS) is one of the most common primary malignant bone tumors in children and adolescents. OS metastasis has been a challenge in the treatment of OS. The present study screened progression related genes in OS by analyzing a public dataset GSE42352, and identified 691 up-regulated and 945 down-regulated genes in advanced stage OS compared to early-stage OS samples. Methods: Protei Read More

Objectives: Graft-versus-host disease (GVHD) is the most common complication after hematopoietic stem cell transplantation (HSCT) and remains to be a major cause of mortality. Activation of toll-like receptor 4 (TLR-4) by lipopolysaccharide induces the NF-ΚB signaling pathway to release critical proinflammatory cytokines and increases the recipient response to GVHD. In order to clarify the role of TLR-4 in the occurrence Read More

Background: Localized radiation therapy is the first-line option for the treatment of nonmetastatic prostate cancer (PCa). Previous studies revealed that long non-coding RNAs (lncRNAs) had crucial roles in disease progression. However, the mechanisms of lncRNAs underlying prostate cancerrelated fatigue remained largely unclear. Objective: The present study aimed to uncover the key genes related to PCa related fati Read More

Background: Bioluminescence is a unique and significant phenomenon in nature. Bioluminescence is important for the lifecycle of some organisms and is valuable in biomedical research, including for gene expression analysis and bioluminescence imaging technology. In recent years, researchers have identified a number of methods for predicting bioluminescent proteins (BLPs), which have increased in accuracy, but c Read More

Background: Neuroimaging is an important tool in early detection of Alzheimer’s disease (AD), which is a serious neurodegenerative brain disease among the elderly subjects. Independent component analysis (ICA) is arguably one of the most widely used algorithm for the analysis of brain imaging data, which can be used to extract intrinsic networks of brain from functional magnetic resonance imaging (fMRI). Methods: Wit Read More

Background: The advancement of bioinformatics and machine learning has facilitated the diagnosis of cancer and the discovery of omics-based biomarkers. Objective: Our study employed a novel data-driven approach to classifying the normal samples and different types of gastrointestinal cancer samples, to find potential biomarkers for effective diagnosis and prognosis assessment of gastrointestinal cancer patients. Metho Read More

Background: Detecting DNA-binding proteins (DBPs) based on biological and chemical methods is time-consuming and expensive. Objective: In recent years, the rise of computational biology methods based on Machine Learning (ML) has greatly improved the detection efficiency of DBPs. Methods: In this study, the Multiple Kernel-based Fuzzy SVM Model with Support Vector Data Description (MK-FSVM-SVDD) is proposed to Read More

Background: Dry Weight (DW) is the lowest weight after dialysis, and patients with lower weight usually have symptoms of hypotension and shock. Several clinical-based approaches have been presented to assess the dry weight of hemodialysis patients. However, these traditional methods all depend on special instruments and professional technicians. Objective: In order to avoid this limitation, we need to find a machine-indep Read More

Background: Among all the major Post-translational modification, lipid modifications possess special significance due to their widespread functional importance in eukaryotic cells. There exist multiple types of lipid modifications and Palmitoylation, among them, is one of the broader types of modification, having three different types. The N-Palmitoylation is carried out by attachment of palmitic acid to an N-terminal cysteine. Read More

Background: Since bacteria are the earliest known organisms, there has been significant interest in their variety and biology, most certainly concerning human health. Recent advances in Metagenomics sequencing (mNGS), a culture-independent sequencing technology, have facilitated an accelerated development in clinical microbiology and our understanding of pathogens. Objective: For the implementation of mNGS in Read More

Background: Cervical cancer is a highly significant cause of mortality in developing countries, and it is one of the most prominent forms of cancer worldwide. Machine learning techniques have been proven more accurate for the identification of cervical cancer as compared to the manual screening methods like Pap smear and Liquid Cytology Based (LCB) tests. Objective: Primarily, these machine-learning techniques use th Read More

Background: Protein secondary structure is vital to predicting the tertiary structure, which is essential in deciding protein function and drug designing. Therefore, there is a high requirement of computational methods to predict secondary structure from their primary sequence. Protein primary sequences represented as a linear combination of twenty amino acid characters and contain the contextual information for sec Read More

Aims: To assess the error profile in NGS data, generated from high throughput sequencing machines. Background: Short-read sequencing data from Next Generation Sequencing (NGS) are currently being generated by a number of research projects. Depicting the errors produced by NGS platforms and expressing accurate genetic variation from reads are two inter-dependent phases. It has high significance in various anal Read More