PSF toolkit: an R package for pathway curation and topology-aware analysis Version 1
The Pathway Signal Flow (PSF) toolkit is an R package designed for pathway editing and signal flow analysis. It enables users to perform PSF analysis on functional -omics data, facilitating the study of signaling pathways in various biological contexts.
Key Features:
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Pathway Editing: Allows customization and editing of biological pathways to suit specific research needs.
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Signal Flow Calculation: Computes signal flow within pathways based on gene expression data, aiding in the understanding of pathway dynamics.
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Visualization: Provides tools to visualize pathways with color-coded nodes representing PSF activities, enhancing interpretability.
SEEK ID: https://armlifebank.am/models/3?version=1
1 item is associated with this Model:- https://github.com/hakobyansiras/psf (Website)
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Created: 5th Feb 2025 at 05:42
Last updated: 5th Feb 2025 at 05:46
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Version 1 (earliest) Created 5th Feb 2025 at 05:42 by Arsen Arakelyan
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Projects: Sex-specific differences in long-term gamma and simGCRsim-associated alterations in deferential gene expression in the heart tissue, Functional Genomics of Vine, Molecular Profiling of Cancer Metastases, Study of the molecular mechanisms of familial Mediterranean fever using genetic engineering and functional genomics, Mental disorders and aging brain, 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, Armenian Wine Genome Program, Molecular characterization of cancers with long-read RNA sequencing, Low dose radiation risks: present research and future perspectives
Institutions: Institute of Molecular Biology NAS RA, Armenian Bioinformatics Institute
https://orcid.org/0000-0002-6851-1056
Siras Hakobyan is currently a Junior Researcher and PhD student in the Research Group of Bioinformatics at the Institute of Molecular Biology NAS RA in Yerevan, Armenia. He received his Master's and Bachelor's degrees in Bioinformatics from Yerevan State University, completing his studies in 2018 and 2016. His PhD project focuses on pathway-centered analysis of high-throughput omics data, particularly examining pathway activity states in cancers based on pathway topology, gene expression, and ...
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
Programme: Bioinformatics Tools for Analysis of Big Genomic Data
Public web page: Not specified
Abstract (Expand)
Authors: S. Hakobyan, A. Stepanyan, L. Nersisyan, H. Binder, A. Arakelyan
Date Published: 8th Sep 2023
Publication Type: Journal
