Bioinformatics Group, Institute of Molecular Biology NAS RA
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Yerevan, AM
We are a team of bioinformatics researchers at the Institute of Molecular Biology, that develops and provides creative solutions to high-throughput biological data analysis. Our lab members are experienced in various aspects of bioinformatics and computational biology: starting from raw data processing, ending... Show more »
We are a team of bioinformatics researchers at the Institute of Molecular Biology, that develops and provides creative solutions to high-throughput biological data analysis. Our lab members are experienced in various aspects of bioinformatics and computational biology: starting from raw data processing, ending with systems biology level analysis, as well as with bioinformatics software development.
Our group is engaged in research projects aimed at secondary analyses of publicly available datasets to reveal the mechanisms of development of complex human diseases. On one hand, we develop novel algorithms, approaches and software for efficient knowledge inference from gene expression and sequencing datasets. On the other hand, we use existing tools to perform actual biological research. We have more than seven years of experience in pathway-based analysis of high-throughput gene expression data, particularly using the pathway signal flow algorithm developed in our group. Another research direction at focus is telomere bioinformatics: development and application of novel computational approaches for analysis of telomere length dynamics and telomere maintenance mechanisms from gene expression/DNA sequencing data. These, and other interests of our group are reflected in the following publications, and described at our website (http://big.sci.am/).
Selected publications:
Book chapters
1. Arakelyan A, Nersisyan L, Hakobyan A. Application of MATLAB in -Omics and Systems Biology. Applications from Engineering with MATLAB Concepts, Associate Prof. Jan Valdman (Ed.), ISBN: 978-953-51-2459-7. InTech, Croatia, 2016. DOI: 10.5772/62847.
2. Arakelyan A, Aslanyan L, Boyajyan A. High-throughput Gene Expression Analysis Concepts and Applications. Sequence and Genome Analysis II – Bacteria, Viruses and Metabolic Pathways. ISBN: 978-1-480254-14-5. iConcept Press Ltd, USA , 2013, 71-95.
3. Arakelyan A, Boyajyan A, Sahakyan H, Aslanyan L, Ivanova K, Mitov I. Growing support set systems in analysis of high-throughput gene expression data. In: New trends in classification and data mining (Editors: K. Markov, V. Ryazanov, V. Velychko, L. Aslanyan), Sofia: ITHEA, 2010, 47-53.
Journal articles
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, 7:79.
2. Hakobyan A, Nersisyan L, Arakelyan A. Quantitative trait association study for mean telomere length in the South Asian Genomes. Bioinformatics 2016, 32(11):1697-700.
3. Hopp L, Nersisyan L, Löffler-Wirth H, Arakelyan A, Binder H. Epigenetic heterogeneity of B-cell lymphoma: Chromatin modifiers. Genes 2015, 6(4):1076-1112.
4. 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.
5. Nersisyan L, Arakelyan A. Computel: computation of mean telomere length from whole-genome next-generation sequencing data. PLoS One 2015, 10(4):e0125201.
6. 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.
7. Nersisyan L, Samsonyan R, Arakelyan A. CyKEGGParser: tailoring KEGG pathways to fit into systems biology analysis workflows. Version 2. F1000Res 2014, 3:145.
8. Arakelyan A, Nersisyan L. KEGGParser: parsing and editing KEGG pathway maps in Matlab. Bioinformatics 2013 Feb 15;29(4):518-9.
We provide a wide range of bioinformatics data analysis pipelines. For details, see the available specialized services. If none are relevant, you may contact us through this service.
We provide a wide range of bioinformatics data analysis pipelines. For details, see the available specialized services. If none are relevant, you may contact us through this service.
We have considerable experience in systems biology analysis of high-throughput data, including enrichment/overreperesntation analysis for pathways and functional gene sets, as well as advanced pathway analysis, machine learning approaches and others. If none of the more specialized services correspond to the type of systems biology analyses you'd like to undertake, contact us through this one.
We have considerable experience in systems biology analysis of high-throughput data, including enrichment/overreperesntation analysis for pathways and functional gene sets, as well as advanced pathway analysis, machine learning approaches and others. If none of the more specialized services correspond to the type of systems biology analyses you'd like to undertake, contact us through this one.
We provide a wide range of biostatistics and bioinformatics data analysis pipelines. For details, see the available specialized services. If none are relevant, you may contact us through this service.
We provide a wide range of biostatistics and bioinformatics data analysis pipelines. For details, see the available specialized services. If none are relevant, you may contact us through this service.
Brainstorming/miscellaneous requests
This service is for the cases where:
Brainstorming/miscellaneous requests
This service is for the cases where:
Biostatistics/Machine-learning
Biostatistics/Machine-learning
Input: Any spreadsheet type file with data.
Output: Results are presented in graphical format with clear, comprehensive and aesthetic figures and schemes, as well as in tabular and text formats. All the results are explained in detail, with the option of further discussions and post-feedback modifications.
Input: Fastq or BAM raw data files or already processed RPKM/TPM/FPKM files.
Output: Results are presented in graphical format, with clear, comprehensive and esthetic figures and schemes, as well as in tabular and text formats. All the results are explained in detail, with the option of further discussions and post-feedback modifications.
Input: CEL and TXT formatted raw data files or Gene Expression Omnibus dataset file formats
Output: Results are presented in graphical format, with clear, comprehensive and aesthetic figures and schemes, as well as in tabular and text formats. All the results are explained in detail, with the option of further discussions and post-feedback modifications.
Advanced pathway analysis
Advanced pathway analysis
Input: Gene expression matrix (or fold-change values) files in a wide variety of formats (.txt, .csv, .xls, .xlsx). Or no additional input is required, if this is a downstream analysis of microarray and RNA-seq data analysis services.
Output: Results are presented in graphical format, with clear, comprehensive and aesthetic figures and schemes, as well as .gif files showing pathway signal flow in certain cases. Additionally, tabular and text formats will also be delivered. All the results are explained in detail, with the option of further discussions and post-feedback modifications.
Input: Gene expression matrix (fold-change values) files in a wide variety of formats (.txt, .csv, .xls, .xlsx). Or no additional input is required, if this is a downstream analysis of microarray and RNA-seq data analysis services.
Output: Results are presented in graphical format, with clear, comprehensive and esthetic figures and schemes, as well as .gif files showing pathway signal flow in certain cases. Additionally, tabular and text formats will also be delivered. All the results are explained in detail, with the option of further discussions and post-feedback modifications.
Computational analysis of telomere biology
Computational analysis of telomere biology
Input: Please contact us for data type and format requirements.
Output: Depending on the input data type, computation of mean telomere length (whole genome) or telomere maintenance mechanisms (gene expression data), or association analysis with -omics data from different sources (epigenomics) is possible. Results are presented in graphical format, with clear, comprehensive and aesthetic figures and schemes, as well as .gif files showing telomere maintenance mechanisms’ activity. Additionally, tabular and text formats will also be delivered. All the results are explained in detail, with the option of further discussions and post-feedback modifications.
Input: fastq or BAM files and phenotype data (optional).
Output: Results are presented in graphical format with clear, comprehensive and aesthetic figures and schemes, as well as in tabular and text formats. All the... Show more »
Input: fastq or BAM files and phenotype data (optional).
Output: Results are presented in graphical format with clear, comprehensive and aesthetic figures and schemes, as well as in tabular and text formats. All the results are explained in detail, with the option of further discussions and post-feedback modifications.
Input: fastq or BAM files.
Output: For ChIP-seq... Show more »
Input: fastq or BAM files.
Output: For ChIP-seq datasets, the output is details of detected peaks, including genomic position and width of the peak, the summit and the peak score. For BS-seq, the output is positions of all sequenced cytosines (in CpG, CHG and CHH contexts) along with the methylation score. All the results are explained in detail, with the option of further discussions and post-feedback modifications.
"The team at the Institute of Molecular Biology NAS RA provided excellent bioinformatics analysis for us. They recommended an approach that was unique to us among the service providers that we engaged with previously inside and outside the Science Exchange, and ultimately their methods delivered novel insights and leads on biological mechanism. The team was responsive, professional, timely, and thorough in the delivery of the work."
Bioinformatics Group, Institute of Molecular Biology NAS RA has not received any endorsements.