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How to build the virtual cell with artificial intelligence: Priorities and opportunities
Department of Computer Science, Stanford University, Stanford, CA, USA; Genentech, South San Francisco, CA, USA; Chan Zuckerberg Initiative, Redwood City, CA, USA; School of Computer and Communication Sciences and School of Life Sciences, EPFL, Lausanne, Switzerland.
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chan Zuckerberg Initiative, Redwood City, CA, USA.ORCID iD: 0000-0002-9961-1041
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chan Zuckerberg Initiative, Redwood City, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA; Department of Pathology, Stanford University, Stanford, CA, USA.ORCID iD: 0000-0001-7034-0850
Chan Zuckerberg Initiative, Redwood City, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA; Department of Applied Physics, Stanford University, Stanford, CA, USA.
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Number of Authors: 422024 (English)In: Cell, ISSN 0092-8674, E-ISSN 1097-4172, Vol. 187, no 25, p. 7045-7063Article, review/survey (Refereed) Published
Abstract [en]

Cells are essential to understanding health and disease, yet traditional models fall short of modeling and simulating their function and behavior. Advances in AI and omics offer groundbreaking opportunities to create an AI virtual cell (AIVC), a multi-scale, multi-modal large-neural-network-based model that can represent and simulate the behavior of molecules, cells, and tissues across diverse states. This Perspective provides a vision on their design and how collaborative efforts to build AIVCs will transform biological research by allowing high-fidelity simulations, accelerating discoveries, and guiding experimental studies, offering new opportunities for understanding cellular functions and fostering interdisciplinary collaborations in open science.

Place, publisher, year, edition, pages
Elsevier BV , 2024. Vol. 187, no 25, p. 7045-7063
Keywords [en]
AI, cell biology, ML, virtual cell
National Category
Computer and Information Sciences Biological Sciences
Identifiers
URN: urn:nbn:se:kth:diva-357888DOI: 10.1016/j.cell.2024.11.015ISI: 001409698100001PubMedID: 39672099Scopus ID: 2-s2.0-85211477743OAI: oai:DiVA.org:kth-357888DiVA, id: diva2:1922595
Note

QC 20241220

Available from: 2024-12-19 Created: 2024-12-19 Last updated: 2025-02-17Bibliographically approved

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Gupta, AnkitKäller Lundberg, Emma

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