council 042
Armenian society of biological psychiatry
Armenian association for molecular
and cellular biology and immunology
Eng Rus Arm




Arsen Arakelyan, PhD, DrSc

E-mail1: aarakelyan@sci.am

E-mail2: arakelyanaa@gmail.com

Phone1(off1): +374 10 282-061

Phone2(off2): +374 10 281-626

FAX: +374 10 282-061

Group members:

  1. Lilit Nersisyan, PhD
  2. Siras Hakobyan
  3. Mariam Alkhazyan
  4. Maria Nikoghosyan
  5. Tigran Mkrtchyan
  6. Meline Hakobyan
  7. Suren Davitavyan
  8. Nelli Vardazaryan
  9. Arabo Apresyan

General information:

The Research Group of Bioinformatics was established in January 2011. We develop and apply algorithms and software for analysis of high throughput gene expression data, next generation sequencing data and linking it to molecular networks and pathways in order to facilitate discovery of pathomechanisms of various diseases.

Current research projects:

Pathway-based gene expression data analysis

- Entropy based analysis of pathway involvement in diseases and differentiation

We develop entropy-based quantitative measures for biomolecular pathways' impact on cell differentiation and disease development. This approach analyzes whole pathway activation dynamics based on its topology and time series gene expression data. Our approach allows for stepping ahead from gene- to pathway-based level in understanding of molecular mechanisms of biological processes.

- Finding shared and specific pathway deregulation patterns in human diseases

The proposed project is aimed at investigating molecular pathomechanisms of complex human diseases via evaluation of similarities and specificities of biomolecular pathway perturbations involved in their pathogenesis. For this purpose we use the GSS-PSF algorithm, and phylogenetic and graph analysis techniques. The employed data analysis strategy will allow for identification of “candidate” genes which may become targets for development of “universal” drugs for treatment of diseases characterized by common patterns of gene expression changes, as well as candidate genes that may serve as targets for specific treatment of a particular disease.

Telomere length association with age related diseases and cancer

Telomere length is known to be associated with cellular ageing and replicative cell senescence. This association is partially explained by telomere position effect (TPE), a phenomenon described by silencing of genes located near telomeres. It is proposed that this process may be linked to several human diseases related to ageing and prolonged exposure to stress, as well as cancers. We are reconstructing gene regulatory networks associated with TPE in normal and diseased states using NGS data. The results of this study will reveal genes associated with cellular senescence and tumor growth, and their interconnections and links to disease development.

Development of software for KEGG pathway parsing and analysis

We develop software for parsing and visualization of KEGG pathway maps in MATLAB and in Cytoscape. In addition to parsing and visualization, our software performs automatic corrections of inconsistencies inherent in KEGG xml formatted files (KGML files) and provides an easy interface for manual editing and saving of KEGG pathway graphs. We are also developing features for tissue-specific tuning of the pathways based on available data on gene activities in each tissue type, as well as pathway drill-down based on physical protein-protein interactions.

Selected Publications:

>> Full publications list of IMB
  1. Arakelyan A, Nersisyan L, Petrek M, Löffler-Wirth H, Binder H. Cartography of pathway signal perturbations identifies distinct molecular pathomechanisms in malignant and chronic lung diseases. Front. Genet. 2016, prov article. doi: 10.3389/fgene.2016.00079.
  2. Nersisyan L, Löffler-Wirth H, Arakelyan A, Binder H. Gene Set- and Pathway- Centered Knowledge Discovery Assigns Transcriptional Activation Patterns in Brain, Blood, and Colon Cancer: A Bioinformatics Perspective. International Journal of Knowledge Discovery in Bioinformatics (IJKDB) 2016, 4(2):46-49.
  3. Hakobyan A, Nersisyan L, Arakelyan A. Quantitative trait association study for mean telomere length in the South Asian Genomes. Bioinformatics 2016. doi: 10.1093/bioinformatics/btw027
  4. Hopp L., Nersisyan L., Löffler-Wirth H. et al. Epigenetic heterogeneity of B-cell lymphoma: Chromatin modifiers. Genes 2015, 6(4):1076-1112.
  5. Nersisyan L, Johnson G, Riel-Mehan M et al. PSFC: a Pathway Signal Flow Calculator App for Cytoscape [version 1; referees: 1 approved] F1000Research 2015, 4:480.
  6. Nersisyan L, Arakelyan A. Computel: computation of mean telomere length from whole-genome next-generation sequencing data. PLoS One. 2015;10(4):e0125201.
  7. Binder H, Wirth H, Arakelyan A, Lembcke K, Tiys ES, Ivanisenko VA, Kolchanov NA, Kononikhin A, Popov I, Nikolaev EN, Pastushkova L, Larina IM. Time-course human urine proteomics in space-flight simulation experiments. BMC Genomics. 2014; 15 Suppl 12:S2.
  8. Nersisyan L, Samsonyan R, Arakelyan A. CyKEGGParser: tailoring KEGG pathways to fit into systems biology analysis workflows. Version 2. F1000Res. 2014 Jul 1 [revised 2014 Aug 14];3:145. doi: 10.12688/f1000research.4410.2. eCollection 2014.
  9. Arakelyan A, Nerisyan L, Gevorgyan A, Boyajyan A. Geometric approach for Gaussian-Kernel bolstered error estimation for linear classification in computational biology. Information Theories and Applications, 2014, 21(2), 170-181.
  10. Arakelyan A, Nersisyan L. KEGGParser: parsing and editing KEGG pathway maps in Matlab. Bioinformatics. 2013 Feb 15;29(4):518-9. doi: 10.1093/bioinformatics/bts730. Epub 2013 Jan 3.