In recent years, with the rapid development of techniques in bioinformatics and life science,
a considerable quantity of biomedical data has been accumulated, based on which …

Cancer presents a significant global health burden, resulting in millions of annual deaths.
Timely detection is critical for improving survival rates, offering a crucial window for timely …

Technological advancements in cell-free DNA (cfDNA) liquid biopsy have triggered
exponential growth in numerous clinical applications. While cfDNA-based liquid biopsy has …

Background The coronavirus disease 2019 (COVID-19) pandemic has caused health
concerns worldwide since December 2019. From the beginning of infection, patients will …

Background Drug sensitivity prediction and drug responsive biomarker selection on high-
throughput genomic data is a critical step in drug discovery. Many computational methods …

A new approach is presented to predict breast cancer recurrence through gene expression
profiles using hidden Markov models (HMM). In this regard, 322 genes were selected from …

In information extraction, named entity recognition (NER) aims to locate named entities in
unstructured text and classify them into predefined categories. Most existing methods for …

This work presents the first resistive random access memory (RRAM)-based compute-in-
memory (CIM) macro design tailored for genome processing. We analyze and demonstrate …

The use of high-throughput omics technologies is becoming increasingly popular in all
facets of biomedical science. The mRNA sequencing (RNA-seq) method reports quantitative …

Tumor metastasis is the major cause of mortality from cancer. From this perspective,
detecting cancer gene expression and transcriptome changes is important for exploring …