Assigning transcriptomic subtypes to CLL samples using nanopore RNA-sequencing and self-organizing maps - dataset

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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.

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 overarching objective of this project is to utilize nanopore sequencing technology and to develop machine learning–based pipelines for the integrative analysis of heterogeneous biological "big data," including multi-omic and phenotypic datasets. The goal is to investigate the molecular mechanisms underlying selected cancers and to identify novel omics-based markers for cancer classification, diagnostics, and prognostics.