Current Bioinformatics - Volume 18, Issue 6, 2023

Background: Hepatocellular carcinoma (HCC) is one of the malignancies with high mortality rate, and identify relevant biomarkers of HCC is helpful for early diagnosis and patient care. Though some high-dimensional omic data contains intrinsic biomedical information about HCC, how to integrate analysis them effectively and find promising biomarkers of HCC is still an important and difficult issue. Methods: We present a n Read More

Introduction: Lung cancer is the leading cancer in terms of morbidity and mortality rate. Its prevalence has been steadily increasing over the world in recent years. An integrated study is unavoidable to analyse the cascading interrelationships between molecular cell components at multiple levels resulting in hidden biological events in cancer. Methods: Multiplex network modeling is a unique methodology that could be used a Read More

Background: The prediction of the drug-induced liver injury (DILI) of chemicals is still a key issue of the adverse drug reactions (ADRs) that needs to be solved urgently in drug development. The development of a novel method with good predictive capability and strong mechanism interpretation is still a focus topic in exploring the DILI. Objective: With the help of systems biology and network analysis techniques, a class of descript Read More

Background: Human microbial communities play an important role in some physiological process of human beings. Nevertheless, the identification of microbe-disease associations through biological experiments is costly and time-consuming. Hence, the development of calculation models is meaningful to infer latent associations between microbes and diseases. Aims: In this manuscript, we aim to design a computational mod Read More

Background: PIWI-interacting RNAs (piRNAs) are a kind of small non-coding RNAs which interact with PIWI proteins and play a vital role in safeguarding genome. Single nucleotide polymorphisms (SNPs) are widely distributed variations which are associated with diseases and have rich information. Up to now, various studies have proved that SNPs on piRNA were related to diseases. Objective: In order to create a compr Read More

Background: With the rapid development of advanced artificial intelligence technologies which have been applied in varying types of applications, especially in the medical field. Cancer is one of the biggest problems in medical sciences. If cancer can be detected and treated early, the possibility of a cure will be greatly increased. Malignant skin cancer is one of the cancers with the highest mortality rate, which cannot b Read More

Introduction: The discovery of tumor subtypes helps to explore tumor pathogenesis, determine the operability of clinical treatment, and improve patient survival. Clustering analysis is increasingly applied to multi-genomic data. However, due to the diversity and complexity of multi-omics data, developing a complete clustering algorithm for tumor molecular typing is still challenging. Methods: In this study, we present an adaptiv Read More