Objective
Advances in technologies that measure gene expression at single-cell resolution have revolutionized our understanding of the heterogeneity, structure and dynamics of tissues and whole organisms in health and disease. Yet, in most single-cell experiments tissue structure, temporal trajectories, and their underlying mechanisms are lost or not directly accessible. Despite experimental advances, major gaps remain in understanding how tissues orchestrate multicellular functions. In recent years, we and others focused on computationally recovering single facets of single-cell data, such as tissue structure or differentiation trajectories. However, each cell encodes multiple layers of information about its type, location, and various biological processes. Disentangling these signals from large-scale, high-dimensional single-cell data is a major challenge. Building on my expertise in network reconstruction, probabilistic spatial inference and spectral analysis of single-cell data, I will take a unique approach to this challenge by developing computational methodologies combining machine learning and dynamical systems approaches to: (1) tease apart multiple cellular facets encoded in single-cell data; (2) infer interactions between these facets and mechanisms shaping spatiotemporal expression across them; (3) derive generative models to sample and predict unobserved cell states and design optimal perturbations, providing an interpretable platform to study conditions leading to a physiological disruption and therapies aimed at reversing it. My research program will tackle the core challenge in the single-cell era - transforming this exponentially growing, complex data into insight and principles for the underlying biology of multicellular systems. It will advance our understanding and control of collective tissue behavior, and uncover the multiple facets of cellular identity in health and disease, and thus expected to be valuable for both basic and translational research.
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2021-STG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
91904 JERUSALEM
Israel
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.