Advances in quantitative biomarker development have accelerated new forms of data-driven
insights for patients with cancer. However, most approaches are limited to a single mode of …

The development of single-cell multimodal assays provides a powerful tool for investigating
multiple dimensions of cellular heterogeneity, enabling new insights into development …

Increased availability of high-throughput technologies has generated an ever-growing
number of omics data that seek to portray many different but complementary biological …

Multi-omics, variously called integrated omics, pan-omics, and trans-omics, aims to combine
two or more omics data sets to aid in data analysis, visualization and interpretation to …

Abstract Characterization and integration of the genome, epigenome, transcriptome,
proteome and metabolome of different datasets is difficult owing to a lack of ground truth …

The growing number of multi-omics studies demands clear conceptual workflows coupled
with easy-to-use software tools to facilitate data analysis and interpretation. This protocol …

Background A fused method using a combination of multi-omics data enables a
comprehensive study of complex biological processes and highlights the interrelationship of …

Despite the notable success of chimeric antigen receptor (CAR) T cell therapies in the
treatment of certain haematological malignancies, challenges remain in optimizing CAR …

Technological advances enabling massively parallel measurement of biological features—
such as microarrays, high-throughput sequencing and mass spectrometry—have ushered in …

Biomedical data is accumulating at a fast pace and integrating it into a unified framework is a
major challenge, so that multiple views of a given biological event can be considered …