scispace - formally typeset
Open AccessJournal ArticleDOI

The Human Cell Atlas

Aviv Regev, +81 more
- 05 Dec 2017 - 
- Vol. 6
Reads0
Chats0
TLDR
An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease.
Abstract
The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

read more

Citations
More filters
Posted ContentDOI

Genome-wide CRISPRi/a screens in human neurons link lysosomal failure to ferroptosis

TL;DR: The first genome-wide CRISPR interference andCRISPR activation screens in human neurons are presented and pathways controlling neuronal response to chronic oxidative stress are uncovered, which is implicated in neurodegenerative diseases.
Journal ArticleDOI

The evolving concept of cell identity in the single cell era.

TL;DR: This Spotlight explores emerging technologies that are enabling the systematic and unbiased quantification of cell identity, and how these efforts will enable the construction of high-resolution, dynamic cell atlases.
Journal ArticleDOI

Cell composition analysis of bulk genomics using single-cell data.

TL;DR: Cell Population Mapping (CPM), a deconvolution algorithm in which reference scRNA-seq profiles are leveraged to infer the composition of cell types and states from bulk transcriptome data, demonstrates the power of CPM in reconstructing the continuous spectrum of cell states within heterogeneous tissues.
Journal ArticleDOI

Interplay of EMT and CSC in Cancer and the Potential Therapeutic Strategies.

TL;DR: The mechanism of cancer stem cell (CSC) population, EMT, regulation of EMT and CSCs by microRNAs and nanomedicine-based approaches to target CSC’s are focused on.
Journal ArticleDOI

Single-cell transcriptomics in cancer: computational challenges and opportunities.

TL;DR: In this paper, the authors highlight emerging themes in the computational analysis of single-cell transcriptomics data and their applications to cancer research, including how to perform unified analysis across many patients and disease states, distinguish neoplastic from nonneoplastic cells, infer communication with the tumor microenvironment, and delineate tumoral and microenvironmental evolution with trajectory and RNA velocity analysis.
References
More filters
Journal ArticleDOI

Continuous cultures of fused cells secreting antibody of predefined specificity

TL;DR: The derivation of a number of tissue culture cell lines which secrete anti-sheep red blood cell (SRBC) antibodies is described here, made by fusion of a mouse myeloma and mouse spleen cells from an immunised donor.
Journal ArticleDOI

Fast unfolding of communities in large networks

TL;DR: This work proposes a heuristic method that is shown to outperform all other known community detection methods in terms of computation time and the quality of the communities detected is very good, as measured by the so-called modularity.
Journal ArticleDOI

Fast unfolding of communities in large networks

TL;DR: In this paper, the authors proposed a simple method to extract the community structure of large networks based on modularity optimization, which is shown to outperform all other known community detection methods in terms of computation time.
Related Papers (5)