Skip to main content
European Commission logo print header

Next Generation Causal Analysis: Inspired by the Induction of Biological Pathways from Cytometry Data

Objective

Discovering the causal mechanisms of a complex system of interacting components is necessary in order to control it. Computational Causal Discovery (CD) is a field that offers the potential to discover causal relations under certain conditions from observational data alone or with a limited number of interventions/manipulations.

An important, challenging biological problem that may take decades of experimental work is the induction of biological cellular pathways; pathways are informal causal models indispensable in biological research and drug design. Recent exciting advances in flow/mass cytometry biotechnology allow the generation of large-sample datasets containing measurements on single cells, thus setting the problem of pathway learning suitable for CD methods.
CAUSALPATH builds upon and further advances recent breakthrough developments in CD methods to enable the induction of biological pathways from cytometry and other omics data. As a testbed problem we focus on the differentiation of human T-cells; these are involved in autoimmune and inflammatory diseases, as well as cancer and thus, are targets of new drug development for a range of chronic diseases. The biological problem acts as our campus for general novel formalisms, practical algorithms, and useful tools development, pointing to fundamental CD problems: presence of feedback cycles, presence of latent confounding variables, CD from time-course data, Integrative Causal Analysis (INCA) of heterogeneous datasets and others.

Three features complement CAUSALPATH’s approach: (A) methods development will co-evolve with biological wet-lab experiments periodically testing the algorithmic postulates, (B) Open-source tools will be developed for the non-expert, and (C) Commercial exploitation of the results will be sought out.

CAUSALPATH brings together an interdisciplinary team, committed to this vision. It builds upon the PI’s group recent important results on INCA algorithms.

Call for proposal

ERC-2013-CoG
See other projects for this call

Host institution

PANEPISTIMIO KRITIS
EU contribution
€ 1 322 000,00
Address
UNIVERSITY CAMPUS GALLOS
74100 Rethimno
Greece

See on map

Region
Νησιά Αιγαίου Κρήτη Ρέθυμνο
Activity type
Higher or Secondary Education Establishments
Administrative Contact
Eleni Karkanaki (Ms.)
Principal investigator
Ioannis Tsamardinos (Prof.)
Links
Total cost
No data

Beneficiaries (2)