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Open AccessJournal ArticleDOI

The Human Cell Atlas

Aviv Regev, +81 more
- 05 Dec 2017 - 
- Vol. 6
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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.

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Citations
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Putative cell type discovery from single-cell gene expression data.

TL;DR: The Single-Cell Clustering Assessment Framework (SCCAF) as mentioned in this paper is a method for the automated identification of putative cell types from single-cell RNA sequencing (scRNA-seq) data.
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Single-cell genomic approaches for developing the next generation of immunotherapies.

TL;DR: How emerging single-cell genomic technologies can serve as an engine for target identification and drug development and improve the development of immunotherapies is discussed.
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Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas

TL;DR: Reconstruction of regulatory networks combined with data from the Connectivity Map showed that HDAC inhibitors could be a potential effective therapy for multiple soft tissue sarcoma subtypes and prognostic genes that are strong predictors of disease outcome when used in a k-nearest neighbor algorithm.
References
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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.
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