Project acronym A-BINGOS
Project Accreting binary populations in Nearby Galaxies: Observations and Simulations
Researcher (PI) Andreas Zezas
Host Institution (HI) IDRYMA TECHNOLOGIAS KAI EREVNAS
Call Details Consolidator Grant (CoG), PE9, ERC-2013-CoG
Summary "High-energy observations of our Galaxy offer a good, albeit not complete, picture of the X-ray source populations, in particular the accreting binary sources. Recent ability to study accreting binaries in nearby galaxies has shown that we would be short-sighted if we restricted ourselves to our Galaxy or to a few nearby ones. I propose an ambitious project that involves a comprehensive study of all the galaxies within 10 Mpc for which we can study in detail their X-ray sources and stellar populations. The study will combine data from a unique suite of observatories (Chandra, XMM-Newton, HST, Spitzer) with state-of-the-art theoretical modelling of binary systems. I propose a novel approach that links the accreting binary populations to their parent stellar populations and surpasses any current studies of X-ray binary populations, both in scale and in scope, by: (a) combining methods and results from several different areas of astrophysics (compact objects, binary systems, stellar populations, galaxy evolution); (b) using data from almost the whole electromagnetic spectrum (infrared to X-ray bands); (c) identifying and studying the different sub-populations of accreting binaries; and (d) performing direct comparison between observations and theoretical predictions, over a broad parameter space. The project: (a) will answer the long-standing question of the formation efficiency of accreting binaries in different environments; and (b) will constrain their evolutionary paths. As by-products the project will provide eagerly awaited input to the fields of gravitational-wave sources, γ-ray bursts, and X-ray emitting galaxies at cosmological distances and it will produce a heritage multi-wavelength dataset and library of models for future studies of galaxies and accreting binaries."
Summary
"High-energy observations of our Galaxy offer a good, albeit not complete, picture of the X-ray source populations, in particular the accreting binary sources. Recent ability to study accreting binaries in nearby galaxies has shown that we would be short-sighted if we restricted ourselves to our Galaxy or to a few nearby ones. I propose an ambitious project that involves a comprehensive study of all the galaxies within 10 Mpc for which we can study in detail their X-ray sources and stellar populations. The study will combine data from a unique suite of observatories (Chandra, XMM-Newton, HST, Spitzer) with state-of-the-art theoretical modelling of binary systems. I propose a novel approach that links the accreting binary populations to their parent stellar populations and surpasses any current studies of X-ray binary populations, both in scale and in scope, by: (a) combining methods and results from several different areas of astrophysics (compact objects, binary systems, stellar populations, galaxy evolution); (b) using data from almost the whole electromagnetic spectrum (infrared to X-ray bands); (c) identifying and studying the different sub-populations of accreting binaries; and (d) performing direct comparison between observations and theoretical predictions, over a broad parameter space. The project: (a) will answer the long-standing question of the formation efficiency of accreting binaries in different environments; and (b) will constrain their evolutionary paths. As by-products the project will provide eagerly awaited input to the fields of gravitational-wave sources, γ-ray bursts, and X-ray emitting galaxies at cosmological distances and it will produce a heritage multi-wavelength dataset and library of models for future studies of galaxies and accreting binaries."
Max ERC Funding
1 242 000 €
Duration
Start date: 2014-04-01, End date: 2019-03-31
Project acronym CAUSALPATH
Project Next Generation Causal Analysis: Inspired by the Induction of Biological Pathways from Cytometry Data
Researcher (PI) Ioannis Tsamardinos
Host Institution (HI) PANEPISTIMIO KRITIS
Call Details Consolidator Grant (CoG), PE6, ERC-2013-CoG
Summary 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.
Summary
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.
Max ERC Funding
1 724 000 €
Duration
Start date: 2015-01-01, End date: 2019-12-31
Project acronym NetVolution
Project Evolving Internet Routing:
A Paradigm Shift to Foster Innovation
Researcher (PI) Christos-Xenofon Dimitropoulos
Host Institution (HI) IDRYMA TECHNOLOGIAS KAI EREVNAS
Call Details Starting Grant (StG), PE7, ERC-2013-StG
Summary Although the Internet is a great technological achievement, more than 40 years after its creation some of its original security and reliability problems remain unsolved. The root cause of these problems is the rigidity of the Internet architecture or in other words the Internet ossification problem, i.e., the basic architectural components of the Internet are set to stone and cannot be changed. The most ossified component of the Internet architecture is the inter-domain routing system.
In this project, our goal is to address this challenge and to introduce a new Internet routing architecture that 1) enables innovation at the inter-domain level, 2) is backward-compatible with the present Internet architecture, and 3) provides concrete economic incentives for adopting it. We propose a new Internet routing paradigm based on a novel techno-economic framework, which exploits emerging technologies and meets these three goals. Our novel idea is that the combination of routing control logic outsourcing with Software Defined Networking (SDN) principles enables to innovate at the inter-domain level and therefore has the potential for a major break-through in the architecture of the Internet routing system. SDN is a rapidly emerging new computer networking architecture that makes the routing control plane of a network programmable. Based on our framework, we propose to design, build, and verify a better inter-domain routing system, which solves fundamental security, reliability, and manageability problems of the Internet architecture. Our work will be organized in four core topics 1) build a mutli-domain centralized routing control platform, 2) improve the reliability and security of the current inter-domain routing system, 3) design techniques for resolving tussles between competing network domains, 4) introduce advanced network monitoring and security techniques that intelligently correlate data from multiple domain to diagnose routing outages and attacks.
Summary
Although the Internet is a great technological achievement, more than 40 years after its creation some of its original security and reliability problems remain unsolved. The root cause of these problems is the rigidity of the Internet architecture or in other words the Internet ossification problem, i.e., the basic architectural components of the Internet are set to stone and cannot be changed. The most ossified component of the Internet architecture is the inter-domain routing system.
In this project, our goal is to address this challenge and to introduce a new Internet routing architecture that 1) enables innovation at the inter-domain level, 2) is backward-compatible with the present Internet architecture, and 3) provides concrete economic incentives for adopting it. We propose a new Internet routing paradigm based on a novel techno-economic framework, which exploits emerging technologies and meets these three goals. Our novel idea is that the combination of routing control logic outsourcing with Software Defined Networking (SDN) principles enables to innovate at the inter-domain level and therefore has the potential for a major break-through in the architecture of the Internet routing system. SDN is a rapidly emerging new computer networking architecture that makes the routing control plane of a network programmable. Based on our framework, we propose to design, build, and verify a better inter-domain routing system, which solves fundamental security, reliability, and manageability problems of the Internet architecture. Our work will be organized in four core topics 1) build a mutli-domain centralized routing control platform, 2) improve the reliability and security of the current inter-domain routing system, 3) design techniques for resolving tussles between competing network domains, 4) introduce advanced network monitoring and security techniques that intelligently correlate data from multiple domain to diagnose routing outages and attacks.
Max ERC Funding
1 410 600 €
Duration
Start date: 2014-01-01, End date: 2018-12-31
