Combining the Powers of Single Cell Sequencing and AI in Understanding Disease Biology and Drug Development

Single cell sequencing has revolutionized the study of biological tissues and systems at the cellular and molecular level. Recent advances in the technology have allowed for the interrogation of distinct subsets of cell populations within tissues, and associated molecular markers that may function as important disease drivers.

The use of single cell sequencing in profiling bulk, heterogeneous tissues at the single cell level can help in the identification of dominant, unique and rare cell subtypes in a sample. Coupling single cell omics with other omics technologies and machine learning tools such as artificial intelligence (AI) can provide key insights about cellular and molecular targets that drive diseases. Characterization of disease pathways and systems can ultimately help lead to more effective disease treatment strategies such as cell-based and immunotherapies.

In recent webinars by Genuity Science, formerly known as WuXi NextCODE, experts from the biotech and pharma industries spoke about leveraging the power of single cell RNA sequencing platforms and solutions in conjunction with machine learning technologies such as AI in cell biology and disease research.

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