oposSOM Browser Version 1
oposSOM is a comprehensive, machine learning based open-source data analysis software combining functionalities such as diversity analyses, biomarker selection, function mining, and visualization. These functionalities are now available as interactive web-browser application for a broader user audience interested in extracting detailed information from high-throughput omics data sets pre-processed by oposSOM. It enables interactive browsing of single-gene and gene set profiles, of molecular 'portrait landscapes', of associated phenotype diversity, and signalling pathway activation patterns.
SEEK ID: https://armlifebank.am/models/4?version=1
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Created: 1st Jun 2026 at 13:19
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Version 1 (earliest) Created 1st Jun 2026 at 13:19 by Arsen Arakelyan
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Projects: Sex-specific differences in long-term gamma and simGCRsim-associated alterations in differential gene expression in the heart tissue, Functional Genomics of Vine, Molecular Profiling of Cancer Metastases, Omics-Based Insights into Human Long-Term Exposure to Environmental Metals, Biological pathway activity analysis, ML approaches for omic data analysis, Tools for Telomere Biology, Mental disorders and aging brain, Armenian Wine Genome Program, Study of the molecular mechanisms of familial Mediterranean fever using genetic engineering and functional genomics, Molecular characterization of cancers with long-read RNA sequencing, Low dose radiation risks: present research and future perspectives, Third International Congress "CRISPR-2025", International Summit in Immuno-Oncology, Molecular Diagnostics in Oncology and Related Fields of Medicine, Discovery of new antiviral compounds by combining in silico and in vitro methods, African swine fever virus, Whole genome and whole exome sequencing based analysis of diversity of genomic variants in Armenian population
Institutions: Institute of Molecular Biology NAS RA, Armenian Bioinformatics Institute
https://orcid.org/0000-0002-6851-1056
This Programme focuses on the development, implementation, and application of bioinformatics tools for the analysis of large-scale genomic datasets. It aims to facilitate the processing, integration, and interpretation of high-throughput sequencing data, including whole-genome, transcriptome, and epigenome analyses. The Programme encompasses computational approaches for variant discovery, gene expression profiling, network biology, and multi-omics data integration.
Projects: Biological pathway activity analysis, ML approaches for omic data analysis, Tools for Telomere Biology
Web page: Not specified
This project focuses on developing and applying machine learning (ML) methodologies to analyze complex omic datasets, including genomics, transcriptomics, proteomics, and metabolomics. By leveraging advanced ML techniques, the project aims to uncover novel biological insights, identify biomarkers, and enhance our understanding of molecular mechanisms underlying various diseases. The initiative is a collaborative effort maintained by the Institute of Molecular Biology NAS RA (IMB), ...
Programme: Bioinformatics Tools for Analysis of Big Genomic Data
Public web page: Not specified
