Allen Cell Explorer, the data portal of the Allen Institute for Cell Science

Welcome to the Allen Cell Explorer where you can access an unprecedented view into the organizational diversity of human stem cells through open data, tools, cell lines, plasmids, and models developed by the Allen Institute for Cell Science. All our scientific resources are openly available to support the cell biology community and accelerate discovery in human health and disease.

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New Disease Cell Line Collections launched

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Browse our Disease Cell Line Collections

We just released 8 disease cell line collections, each containing multiple isogenic control and mutation-carrying clones:

6 cardiomyopathy disease collections, each with a different point mutation in the MYH7 gene
1 skeletal myopathy disease collection with point mutation in the MYH3 gene
1 laminopathy disease collection has a mutation in the LMNA/C gene associated with progeria

These cell lines will be valuable tools to further our understanding of the fundamental mechanisms which underly these disease phenotypes and enable relevant pharmacological discoveries to treat them. This monumental one-time release of the 8 disease cell line collections with a total of 37 clones is comparable in magnitude to the 58 cell lines in the Allen Cell Catalog, which were released over the last 8 years.

New article published in Cell

Establishing a conceptual framework for holistic cell states and state transitions

"Cell states were traditionally defined by how they looked, where they were located, and what functions they performed. In this post-genomic era, the field is largely focused on a molecular view of cell state. Moving forward, we anticipate that the observables used to define cell states will evolve again as single-cell imaging and analytics are advancing at a breakneck pace via the collection of large-scale, systematic cell image datasets and the application of quantitative image-based data science methods. This is, therefore, a key moment in the arc of cell biological research to develop approaches that integrate the spatiotemporal observables of the physical structure and organization of the cell with molecular observables toward the concept of a holistic cell state. In this perspective, we propose a conceptual framework for holistic cell states and state transitions that is data-driven, practical, and useful to enable integrative analyses and modeling across many data types."

Read Cell article

Register for TEMTIA 11

We are excited to host the 11th EMT International Association (TEMTIA 11) meeting at the Allen Institute in Seattle, Washington, USA, on November 12-15, 2024.

Event Details

Abstract Submission

The epithelial to mesenchymal transition (EMT) is a cell state change during which cells transition from stationary to migratory behavior. Associated with normal development but also a characteristic of many cancers, EMT includes complex changes across multiple cell characteristics and is consistently and universally difficult to define. At this year’s TEMTIA, we will leverage the diversity of the field, convening experts across contexts, perspectives, and scales of study to address this challenge. Scientific sessions will be organized with common themes such as: data integration, microscopy in EMT, modeling of state changes, and more.

To recognize the seminal contributions of Dr. Elizabeth Hay to the EMT field, TEMTIA will present the Betty Hay award of AU$1000.00 to a young female scientist. To apply for the fellowship or for more information, visit the Event Details page.

Talk/poster abstract submission deadline: May 31, 2024
Please contact [email protected] for any questions.

Featured Publications

Integrated intracellular organization and its variations in human iPS cells
Viana MP, Chen J, Knijnenburg TA, Vasan R, Yan C, Arakaki JE, Bailey M, Berry B, Borensztejn A, Brown EM, Carlson S, Cass JA, Chaudhuri B, Metzler KRC, Coston ME, Crabtree ZJ, Davidson S, DeLizo CM, Dhaka S, Dinh SQ, Do TP, Domingus J, Donovan-Maiye RM, Ferrante AJ, Foster TJ, Frick CL, Fujioka G, Fuqua MA, Gehring JL, Gerbin KA, Grancharova T, Gregor BW, Harrylock L, Haupt A, Hendershott MC, Hookway C, Horwitz AR, Hughes C, Isaac EJ, Johnson GR, Kim B, Leonard AN, Leung W, Lucas JJ, Ludmann SA, Lyons BM, Malik H, McGregor R, Medrash GE, Meharry SL, Mitcham K, Mueller IA, Murphy-Stevens TL, Nath A, Nelson AM, Oluoch SA, Paleologu L, Popiel TA, Riel-Mehan MM, Roberts B, Schaefbauer LM, Schwarzl M, Sherman J, Slaton S, Sluzewski MF, Smith JE, Sul Y, Swain-Bowden MJ, Tang WJ, Thirstrup DJ, Toloudis DT, Tucker AP, Valencia V, Wiegraebe W, Wijeratna T, Yang R, Zaunbrecher RJ, Labitigan RLD, Sanborn AL, Johnson GT, Gunawardane RN, Gaudreault N, Theriot JA, Rafelski SM. Nature, January 4, 2023.

A comprehensive analysis of gene expression changes in a high replicate and open-source dataset of differentiating hiPSC-derived cardiomyocytes
Grancharova T, Gerbin KA, Rosenberg AB, Roco CM, Arakaki JE, DeLizo CM, Dinh SQ, Donovan-Maiye RM, Hirano M, Nelson AM, Tang J, Theriot JA, Yan C, Menon V, Palecek SP, Seelig G, Gunawardane RN. Scientific Reports, August 04, 2021.

Cell states beyond transcriptomics: Integrating structural organization and gene expression in hiPSC-derived cardiomyocytes
Gerbin KA, Grancharova T, Donovan-Maiye RM, Hendershott MC, Anderson HG, Brown JM, Chen J, Dinh SQ, Gehring JL, Johnson GR, , Lee H, Nath A, Nelson AM, Sluzewski MF, Viana MP, Yan C, Zaunbrecher RJ, Cordes Metzler KR, Gaudreault N, Knijnenburg T, Rafelski SM, Theriot JA, Gunawardane RN. Cell Systems, June 16, 2021.

See More of Our Publications...

We study the human cell holistically. To understand and predict cell behaviors, we develop and image high quality human induced pluripotent stem (hiPS) cell lines with genome editing to illuminate over 40 key cellular structures. This live cell imaging, together with image analysis, visualization tools and computational models enable novel interpretations of cell behavior by us and researchers around the globe.

Cells & plasmids for your lab

We have created a series of gene edited human iPSCs that we use as the foundation for our image data, and that we share with the larger scientific community.

Cell Catalog