From Molecular Structures to Cellular Maps
Understanding biology from molecules to cells
Background and Overview
Mapping Biology at the Cellular Level
Protocell explores how modern technologies are helping researchers understand biology one cell at a time.
Every tissue is made up of diverse cells with different identities, molecular programs and functions. For decades, many biological studies relied on measurements taken from groups of cells together. While these approaches provided valuable information, they could hide important differences between individual cells.
The development of single-cell RNA sequencing (scRNA-seq) changed this perspective by allowing researchers to investigate gene-expression patterns at the level of individual cells. Instead of viewing a tissue as one biological population, scientists can begin to identify its cellular diversity and distinguish different cellular states.
But knowing which cells are present is only the beginning.
Modern research is moving toward a broader objective: mapping cells within their biological environment. Spatial transcriptomics can add information about where cells are located, while single-cell multi-omics can connect gene expression with other molecular layers. Computational biology and artificial intelligence are increasingly being used to integrate these complex datasets and identify patterns across cells, tissues and biological systems.
Our Goals
- Understand cells — explore cellular identity, diversity and molecular states.
- Map biological systems — connect individual cells to their spatial organization within tissues.
- Connect biological data — bring together single-cell RNA-seq, spatial transcriptomics, multi-omics and imaging.
- Explore cellular interactions — investigate how cells communicate and influence one another.
- Track cellular change — understand how cells transition between different states.
- Advance cellular research — make complex single-cell research easier to explore, understand and connect.
Our Path Toward Cellular Mapping
1
Understand the Cell
Build a strong educational foundation around cell biology, single-cell RNA sequencing and cellular identity.
2
Map Cellular Systems
Explore spatial transcriptomics, cell atlases and tissue organization to understand where cells are and how they are organized.
3
Connect & Analyze
Cover cell–cell communication, multi-omics, computational biology and AI to understand relationships between cells and integrate complex datasets.
4
Explore the Future
Follow emerging research toward predictive cellular biology, dynamic cell mapping and increasingly comprehensive models of biological systems.
Why Study Biology One Cell at a Time?
Biological tissues are made up of diverse cells, each with its own molecular characteristics and functions. Studying cells individually allows researchers to uncover differences that can remain hidden when biological measurements are averaged across entire tissues.
Single-cell RNA sequencing has opened new possibilities for studying gene expression at cellular resolution. Today, researchers are combining single-cell approaches with spatial technologies, multi-omics and computational biology to build increasingly detailed views of biological systems.
Toward a Cellular Atlas
What if we could build increasingly detailed maps of biological systems — showing not only which cells are present, but where they are, what molecular programs they use and how they interact?
Cellular Mapping: Key Questions
In this section, you can address common questions efficiently.
Cellular mapping identifies cell types, characterizes their molecular properties, and explores their organization within biological tissues.
Single-cell RNA sequencing, spatial transcriptomics, imaging, and multi-omics help researchers investigate cellular identity, molecular activity, and tissue organization.
AI and computational biology help researchers analyze complex datasets, integrate molecular information, and identify patterns in cellular systems.
Where to find useful, open scientific resources
NCBI Gene Expression Omnibus
Find publicly available gene-expression and functional genomics datasets.
Single Cell Expression Atlas
Explore curated single-cell gene-expression experiments.