Bioinformatics Tools for Analysis of Big Genomic Data

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Arsen Arakelyan

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, Epigenetic influence of human long-term environmental exposure to metals, Biological pathway activity analysis, ML approaches for omic data analysis, Tools for Telomere Biology, Mental disorders and aging brain, Armenian Wine Genome Program

Institutions: Institute of Molecular Biology NAS RA, Armenian Bioinformatics Institute

https://orcid.org/0000-0002-6851-1056

Hans Binder

Projects: Functional Genomics of Vine, Molecular Profiling of Cancer Metastases, Biological pathway activity analysis, Mental disorders and aging brain

Institutions: Armenian Bioinformatics Institute

https://orcid.org/0000-0002-2242-4678

Expertise: Bioinformatics, Genomics, Precision Medicine, Machine Learning, Cancer Biology

Tools: Mathematical Modelling, Single Cell analysis, Computational and theoretical biology, Genomics, Transcriptomics

Siras Hakobyan

Projects: Biological pathway activity analysis, Sex-specific differences in long-term gamma and simGCRsim-associated alterations in deferential gene expression in the heart tissue

Institutions: Institute of Molecular Biology NAS RA

https://orcid.org/0000-0002-6875-2482

Expertise: Bioinformatics

Tools: Cytoscape, Genomics, Microarray analysis, Python, R, Single Cell analysis, Transcriptomics

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 ...

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Biological pathway activity analysis

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Programme: Bioinformatics Tools for Analysis of Big Genomic Data

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Tools for Telomere Biology

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Programme: Bioinformatics Tools for Analysis of Big Genomic Data

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ML approaches for omic data analysis

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Programme: Bioinformatics Tools for Analysis of Big Genomic Data

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Armenian Bioinformatics Institute

Country: Armenia

City: Yerevan

Web page: https://www.abi.am

Institute of Molecular Biology NAS RA

Country: Armenia

City: Yerevan

Web page: https://molbiol.sci.am

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Test model - KEGGParser: parsing and editing KEGG pathway maps in Matlab

Biological pathway activity analysis

KEGG pathway database is a collection of manually drawn pathway maps representing current knowledge on molecular interaction and reaction networks, accompanied with KGML (KEGG pathway xml format) files for automatic computational analyses and modeling of metabolic and signaling networks. In a KGML file the pathway is represented as a graph object with entry elements (gene products, compounds, pathways) as its nodes, and relations between elements as edges. However, in most cases there is a lack ...

Creator: Arsen Arakelyan

Submitter: Arsen Arakelyan

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Environment: Matlab

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Created: 7th Mar 2024 at 09:36, Last updated: 7th Mar 2024 at 09:36

Showing 5 out of a possible 9 Publications Advanced Publications list for this Programme with search and filtering

Temporal changes of gene expression in health, schizophrenia, bipolar disorder, and major depressive disorder.

Mental disorders and aging brain, ML approaches for omic data analysis

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Abstract (Expand)

The molecular events underlying the development, manifestation, and course of schizophrenia, bipolar disorder, and major depressive disorder span from embryonic life to advanced age. However, little …

Authors: A. Arakelyan, S. Avagyan, A. Kurnosov, T. Mkrtchyan, G. Mkrtchyan, R. Zakharyan, K. R. Mayilyan, H. Binder

Date Published: 17th Feb 2024

Publication Type: Journal

PubMed ID: 38368435

Citation: Schizophrenia (Heidelb). 2024 Feb 17;10(1):19. doi: 10.1038/s41537-024-00443-7.

Created: 28th Apr 2024 at 14:09

PSF toolkit: an R package for pathway curation and topology-aware analysis.

Biological pathway activity analysis

Abstract (Expand)

Most high throughput genomic data analysis pipelines currently rely on over-representation or gene set enrichment analysis (ORA/GSEA) approaches for functional analysis. In contrast, topology-based … pathway analysis methods, which offer a more biologically informed perspective by incorporating interaction and topology information, have remained underutilized and inaccessible due to various limiting factors. These methods heavily rely on the quality of pathway topologies and often utilize predefined topologies from databases without assessing their correctness. To address these issues and make topology-aware pathway analysis more accessible and flexible, we introduce the PSF (Pathway Signal Flow) toolkit R package. Our toolkit integrates pathway curation and topology-based analysis, providing interactive and command-line tools that facilitate pathway importation, correction, and modification from diverse sources. This enables users to perform topology-based pathway signal flow analysis in both interactive and command-line modes. To showcase the toolkit's usability, we curated 36 KEGG signaling pathways and conducted several use-case studies, comparing our method with ORA and the topology-based signaling pathway impact analysis (SPIA) method. The results demonstrate that the algorithm can effectively identify ORA enriched pathways while providing more detailed branch-level information. Moreover, in contrast to the SPIA method, it offers the advantage of being cut-off free and less susceptible to the variability caused by selection thresholds. By combining pathway curation and topology-based analysis, the PSF toolkit enhances the quality, flexibility, and accessibility of topology-aware pathway analysis. Researchers can now easily import pathways from various sources, correct and modify them as needed, and perform detailed topology-based pathway signal flow analysis. In summary, our PSF toolkit offers an integrated solution that addresses the limitations of current topology-based pathway analysis methods. By providing interactive and command-line tools for pathway curation and topology-based analysis, we empower researchers to conduct comprehensive pathway analyses across a wide range of applications.

Authors: S. Hakobyan, A. Stepanyan, L. Nersisyan, H. Binder, A. Arakelyan

Date Published: 8th Sep 2023

Publication Type: Journal

PubMed ID: 37680201

Citation: Front Genet. 2023 Aug 23;14:1264656. doi: 10.3389/fgene.2023.1264656. eCollection 2023.

Created: 6th Mar 2024 at 19:17

Projection of High-Dimensional Genome-Wide Expression on SOM Transcriptome Landscapes

ML approaches for omic data analysis

Abstract (Expand)

organizing maps portraying has been proven to be a powerful approach for analysis of transcriptomic, genomic, epigenetic, single-cell, and pathway-level data as well as for “multi-omic” integrative …

Authors: Maria Nikoghosyan, Henry Loeffler-Wirth, Suren Davidavyan, Hans Binder, Arsen Arakelyan

Date Published: 27th Dec 2021

Publication Type: Journal

DOI: 10.3390/biomedinformatics2010004

Citation: BioMedInformatics,2(1):62-76

Created: 7th Mar 2024 at 11:00

Telomere Maintenance Pathway Activity Analysis Enables Tissue- and Gene-Level Inferences.

Biological pathway activity analysis, Tools for Telomere Biology

Abstract (Expand)

Telomere maintenance is one of the mechanisms ensuring indefinite divisions of cancer and stem cells. Good understanding of telomere maintenance mechanisms (TMM) is important for studying cancers and …

Authors: L. Nersisyan, A. Simonyan, H. Binder, A. Arakelyan

Date Published: 26th Apr 2021

Publication Type: Journal

PubMed ID: 33897770

Citation: Front Genet. 2021 Apr 7;12:662464. doi: 10.3389/fgene.2021.662464. eCollection 2021.

Created: 7th Mar 2024 at 09:09, Last updated: 7th Mar 2024 at 15:40

SOMmelier-Intuitive Visualization of the Topology of Grapevine Genome Landscapes Using Artificial Neural Networks.

ML approaches for omic data analysis

Abstract (Expand)

BACKGROUND: Whole-genome studies of vine cultivars have brought novel knowledge about the diversity, geographical relatedness, historical origin and dissemination, phenotype associations and genetic …

Authors: M. Nikoghosyan, M. Schmidt, K. Margaryan, H. Loeffler-Wirth, A. Arakelyan, H. Binder

Date Published: 17th Jul 2020

Publication Type: Journal

PubMed ID: 32709105

Citation: Genes (Basel). 2020 Jul 17;11(7):817. doi: 10.3390/genes11070817.

Created: 7th Mar 2024 at 10:50

View all 9 Publications