Deep learning methods possess many processing layers to understand the stratified
representation of data and have achieved state-of-art results in several domains. Recently …

Genomics is advancing towards data-driven science. Through the advent of high-throughput
data generating technologies in human genomics, we are overwhelmed with the heap of …

Annotating cell types on the basis of single-cell RNA-seq data is a prerequisite for research
on disease progress and tumour microenvironments. Here we show that existing annotation …

Molecular classification has transformed the management of brain tumors by enabling more
accurate prognostication and personalized treatment. However, timely molecular diagnostic …

Data-centric approaches have been used to develop predictive methods for elucidating
uncharacterized properties of proteins; however, studies indicate that these methods should …

Cancer is a Toxic health concern worldwide, it happens when cellular modifications cause
the irregular growth and division of human cells. Several traditional approaches such as …

The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized
transcriptomic studies. However, large-scale integrative analysis of scRNA-seq data remains …

Dimensionality reduction (DR) is frequently applied during the analysis of high-dimensional
data. Both a means of denoising and simplification, it can be beneficial for the majority of …

Deciphering universal gene regulatory mechanisms in diverse organisms holds great
potential for advancing our knowledge of fundamental life processes and facilitating clinical …

There has been significant recent progress in leveraging large-scale gene expression data
to develop foundation models for single-cell biology. Models such as Geneformer and …