Systems Biology of Aging Group aging.biochim.ro
multi-disciplinary lab, awesome international team, cool tools and models
News
Starting 15.12.2017, the Institute of Biochemistry of the Romanian Academy is pleased to invite IT equipment providers to participate in the public acquisitions procedure for the project “Multi-omics prediction system for prioritization of gerontological interventions - GERONTOMICS”.
The invitation to participate can be accessed through the SEAP system, at e-licitatie.ro. The invitation/ad number is: 419933 / 15.12.2017.
WHO WE ARE
The Systems Biology of Aging Group was founded by Dr. Robi Tacutu in 2016, and is part of the department of Bioinformatics and Structural Biochemistry at the Institute of Biochemistry of the Romanian Academy. We are currently funded by a recently awarded EUR 2 million EU grant, for the project “Multi-omics Prediction System for Prioritization of Gerontological Interventions”, and our main areas of interest include biogerontology, systems biology and bioinformatics.
With a highly multi-disciplinary team, our projects include both computational aspects (data aggregation and processing, multidimensional data analysis, network-based methods, systems theory approaches, deep learning, etc.) as well as wet-lab experiments (in particular in-vivo testing of the computationally predicted interventions).
If you would like to learn more about the Gerontomics project, please go here.
BACKGROUND
Aging is a biological process defined by a progressive loss of viability and an exponential increase in fragility and vulnerability. Age is also the main risk factor for many diseases, including most types of cancers, heart and vascular diseases, type 2 diabetes, neurodegenerative diseases, etc. This is not surprising, as at the molecular level, age-related diseases share many genetic components and molecular pathways with the “normal” aging process.
Understanding the aging process, and the mechanisms underlining it, is one of the major biological and biomedical challenges of our century and could result in much higher dividends to society in our capacity to extend lifespan and more importantly healthspan (i.e. the interval of healthy, productive years in a person’s life).
With the current advances in high-throughput technologies many of the genetic and molecular aspects of aging can now be easily screened at various “omics” levels, using a wide range of models and starting from various hypotheses. While all the existing datasets are extremely valuable by themselves, they pose an incomparably higher potential if analyzed together. In terms of data integration however, more efforts are required to achieve a cohesive approach and an integrative view on how these molecular measurements are all interconnected and manifest as aging and/or age-related diseases. Such a multi-model integration, combined with systems biology approaches will be of paramount importance in the coming years and will maximize the amount of knowledge that we can gather from gerontological observational studies.
MISSION AND AIMS
Our mission is to use and develop computational tools, with the goal of enhancing our knowledge and understanding of the aging process. Ultimately, our mission is to translate these theoretical results into genetic and pharmacological interventions that can be tested in the lab.
More specifically, our current aims are to 1) integrate and analyze large-scale datasets from different biological levels (including genomics, transcriptomics and epigenomics); 2) to use frontier systems biology approaches, network biology, machine learning, and artificial intelligence, to create mathematical and computational models of aging; and 3) using these data, models and algorithms, to predict novel genetic and epigenetic interventions that would have the highest potential to impact lifespan and healthspan in model organisms.
If you would like to learn more about our projects, to collaborate or inquire about any available jobs/internships in our group, just drop us a line.
FUNDING
Our group is very grateful for the kind support received from EU-RO funding, through the Competitiveness Operational Programme 2014-2020, POC-A.1-A.1.1.4-E-2015.
Our group would like to also thank Microsoft for the Azure Research sponsorship (cloud computing resources) awarded to our group.
We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for our research.
The content of this material does not necessarily represent the official position of the European Union or that of the Romanian Government.
For any informations regarding any other EU-RO co-funded programmes, please visit www.fonduri-ue.ro.