BACKGROUND: Recent years have seen a surge of novel neural network architectures for the integration of multi-omics data for prediction. Most of the architectures include either encoders alone or encoders and decoders, i.e., autoencoders of various s...
Modern oncology offers a wide range of treatments and therefore choosing the best option for particular patient is very important for optimal outcome. Multi-omics profiling in combination with AI-based predictive models have great potential for strea...
Computer methods and programs in biomedicine
Jan 27, 2023
BACKGROUND AND OBJECTIVE: Integrating multi-omics data for the comprehensive analysis of the biological processes in human diseases has become one of the most challenging tasks of bioinformatics. Deep learning (DL) algorithms have recently become one...
Journal of the American Chemical Society
Jan 27, 2023
Only around 20% of the human proteome is considered to be druggable with small-molecule antagonists. This leaves some of the most compelling therapeutic targets outside the reach of ligand discovery. The concept of targeted protein degradation (TPD) ...
Comprehensive reviews in food science and food safety
Jan 12, 2023
Microbiome science as an interdisciplinary research field has evolved rapidly over the past two decades, becoming a popular topic not only in the scientific community and among the general public, but also in the food industry due to the growing dema...
With biotechnological advancements, innovative omics technologies are constantly emerging that have enabled researchers to access multi-layer information from the genome, epigenome, transcriptome, proteome, metabolome, and more. A wealth of omics tec...
Single-cell multimodal sequencing technologies are developed to simultaneously profile different modalities of data in the same cell. It provides a unique opportunity to jointly analyze multimodal data at the single-cell level for the identification ...
Early diagnosis of lung cancer to increase the survival rate, which is currently at a low range of mid-30%, remains a critical need. Despite this, multi-omics data have rarely been applied to non-small-cell lung cancer (NSCLC) diagnosis. We developed...
The discovery of cancer subtypes based on unsupervised clustering helps in providing a precise diagnosis, guide treatment, and improve patients' prognoses. Instead of single-omics data, multi-omics data can improve the clustering performance because ...