Armenian Bioinformatics Institute

This program under is designed to encapsulate and facilitate research projects focusing on the intricate dynamics between genetic predispositions and environmental factors in the progression of chronic diseases, excluding cancer. This initiative aims to unravel the molecular mechanisms and pathways that underlie these diseases, thereby paving the way for targeted interventions and therapies.

This Programme offers a comprehensive summary of various projects focused on deciphering the intricate molecular mechanisms of cancer development, progression, and response to treatments, utilizing bioinformatics, computational biology, and machine learning. These are multi-laboratory efforts carried out across several research institutions, supported by various grant programs.

Principal Investigator: Prof. Hans Binder

University: University of Leipzig

Research Group: Kristina Margaryan, Maria Nikoghosyan, Tomas Konecny, Anush Baloyan, Hripsime Gasoyan, Emma Hovhannisyan, Levon Galstyan, Duan Shengchang

Duration: 2023-2027

Co-implementing and hosting partner: Armenian Bioinformatics Institute (ABI) and Institute of Molecular Biology

Project Importance The cultivated grape (Vitis vinifera) has become the world’s leading fruit crop. Grape is unique not only because ...

This project focuses on studies around brain disorders and ageing.

Together with the scientists at Agenus, a US-based biotech company specializing in innovative forms of cancer treatment, including the discovery and development of immuno-oncology therapies, ABI has formed a team of students and researchers to study cancer metastases and identify potential biomarkers and targets for cancer immunotherapies. This collaboration is also part of our long-term vision of supporting biotech developments in Armenia. The team discovers transcriptomics heterogeneity of Liver ...

The genomic information becomes functional after transcription and translation. Omics-data (e.g., transcriptomics, epigenetics, proteomics) are increasingly generated for vine and other cultivated plants to study functional genomics with impact for improving yield, quality, and resistance. However, many issues, related to, e.g., development, stress-response, and resistance are still understudied. This opens novel opportunities to close this gap by analyzing such datasets.