Current Bioinformatics - Online First

Background An uncommon neurological condition known as Guillain-Barre syndrome (GBS) develops when the body's immunological system unintentionally targets peripheral nerves. Aim This work aimed to compare scRNA-seq and transcriptome data to find novel gene biomarkers linked to CD4+ T cells and B cells that might potentially be utilized for the diagnosis and assessment of GBS. It aimed to employ scRNA-seq dat Read More

Background The 5' UTR plays a crucial role in gene regulation, which may be through its interaction with introns. Hence, there is a need to further study this interaction. Objective This study aimed to investigate the interactions between 5' UTR and introns and their correlation with species evolution. Methods The optimally matched segments between 5' UTR and introns were identified using Smith-Waterman local similarity Read More

Introduction Multi-omics data integration has transformed personalized medicine, providing a comprehensive understanding of disease mechanisms and informed precision therapeutic options. Multi-omics data generated for the same samples/patients can help in getting insights into the flow of biological information at several levels, thereby providing in-depth information regarding the molecular mechanisms underlyi Read More

Transcriptomics covers the in-depth analysis of RNA molecules in cells or tissues and plays an essential role in understanding cellular functions and disease mechanisms. Advances in spatial transcriptomics (ST) in recent times have revolutionized the field by combining gene expression data with spatial information, enabling the analysis of RNA molecules within their tissue context. The evolution of spatial transcriptomics, particula Read More

Sequence alignment, pattern matching, and mining are important cornerstones in bioinformatics, and they include identifying genome structure, protein function, and biological metabolic regulatory network. However, because it helps speed up the dealing process, the parallel sequential pattern recognition method has gained attention as data volume has increased. This review summarizes the GPU-based sequence align Read More

Background The MTA gene encodes a core component of m6A methyltransferase complex, which plays a crucial role in the post-transcriptional modification of RNA that influences many vital processes in plants. However, due to the constraint of embryonic lethality in MTA knockout mutation, the molecular function of MTA gene has yet to be comprehensively investigated. Objective The aim of this study is to investigate the exp Read More

Aim This study aims to develop and validate a machine learning-based model for the accurate prediction of androgen receptor (AR) agonistic toxicity, addressing the challenges posed by data imbalance in existing predictive models. Background Anomalous agonistic activity of the androgen receptor is a known major indicator of reproductive toxicity, which can lead to prostate cancer. Machine learning-based mode Read More

Background Long non-coding RNAs (lncRNAs) are a category of more extended RNA strands that lack protein-coding abilities. Although they are not involved in the translation of proteins, studies have shown that they play essential regulatory functions in cells, regulating gene expression and cell biological processes. However, it is both costly and inefficient to determine the associations between lncRNAs and diseases through biolo Read More

Introduction Cancers routinely exhibit chromosomal instability that results in copy number variants (CNVs), namely changes in the abundance of genomic material. Unfortunately, the detection of these variants in cancer genomes is difficult. Methods We present Ploidetect, a software package that effectively identifies CNVs within whole-genome sequenced tumors. Ploidetect utilizes a coarse-to-fine segmentation approach whic Read More

Background The root system plays an irreplaceable role in plant growth. Its improvement can increase crop productivity. However, such a system is still mysterious for us. The underlying mechanism has not been fully uncovered. The investigation on proteins related to the root system is an important means to complete this task. In the previous time, lack of root-related proteins makes it impossible to adopt machine learning Read More

Background Since each dimension of a tensor can store different types of genomics data, compared to matrix methods, utilizing tensor structure can provide a deeper understanding of multi-dimensional data while also facilitating the discovery of more useful information related to cancer. However, in reality, there are issues such as insufficient utilization of prior knowledge in multi-omics data and limitations in the recovery Read More

Poor dietary habits and a lack of understanding are contributing to the rapid global increase in the number of diabetic people. Therefore, a framework that can accurately forecast a large number of patients based on clinical details is needed. Artificial intelligence (AI) is a rapidly evolving field, and its implementations to diabetes, a worldwide pandemic, have the potential to revolutionize the strategy of diagnosing and fore Read More

Background One of the main causes of cancer-related mortality in women is breast cancer [BC]. There were four molecular subtypes of this malignancy, and adjuvant therapy efficacy differed based on these subtypes. Gene expression profiles provide valuable information that is helpful for patients whose prognosis is not clear from clinical markers and immunohistochemistry. Objective In this study, we aim to predict mol Read More

Background The human genome is densely populated with repetitive DNA sequences that play crucial roles in genomic functions and structures but are also implicated in over 40 human diseases. The computational challenge of identifying and characterizing these repeats is significant due to the complexity and size of the genome, which are overwhelming traditional algorithms. Methods To address these challenges, we propose G Read More