Maxim Artyomov, Ph.D.

Assistant Professor
Pathology and Immunology

Immunology Program
Computational and Systems Biology Program
Biochemistry, Biophysics, and Structural Biology Program

  • 314-286-2951

  • 8118

  • 8th lab BJCIH

  • martyomov@WUSTL.EDU

  • artyomovlab.wustl.edu

  • systems immunology, systems biology, computational biology, RNA-seq

  • Systems immunology using high-throughput next-generation sequencing in conjunction with mathematical and statistical modeling approaches rooted in statistical physics

Research Abstract:

We are located at BJCIH (Medical School Campus) as a part of Department of Pahology&Immunology. Our lab is also a part Center Biological Systems Engineering (Danforth Campus).

Our research is focused on developing integrated experimental and computational pipeline to address important biological problems by leveraging the power of next-generation sequencing. Two major components comprise creation of such integrated pipeline: first, optimization of sequencing library preparation protocols to achieve high-throughput and cost affordability, and, second, corresponding bioinformatic processing of sequencing data and computational analysis of the high-throughput gene-expression and other kinds of sequencing data (e.g. ChipSeq, RACE etc) that allow one to gain insight into the biology in hand.

As a part of collaborative team at Broad Institute, I developed multiplexed affordable RNA-Sequencing based platform for genome-wide expression analysis by trading some of powers of traditional RNA-Seq (such as information about splicing etc) to achieve high-throughput and dramatic cost reduction making cost per sample lower than 100$. Our approach is optimized for 96-well plates, thus, allowing extreme throughput and mitigating batch-effects that plague traditional microarray based approaches.

Such a through-put makes generation of hundreds of genome wide profiles possible in reasonable cost and timeframe, dramatically changing amount of data available for analysis. This requires extension of existing and development of novel methods for analysis of gene-expression on such scale which is the subject of computational component of my research. Our current projects are focused on developing network topology analysis tools to identify most important genes and gene modules from a high-throughput expression studies.

In summary, our research is on the cross-roads between experiments and theory/computation and can be characterized most succinctly as systems immunology whereby we use high-throughput next-generation sequencing in conjunction with mathematical and statistical modeling approaches rooted in statistical physics.

Selected Publications:

Targeted Chromatin Profiling Reveals Novel Enhancers in Immunoglobulin Heavy and Light Chain Loci. Predeus A*, Gopalakrishnan S*, Huang Y, Tung J, Feeney AJ, Oltz EM, Artyomov MN. J Immunol. 2013 Dec 18. [Epub ahead of print] PMID:24353267

Unifying model for molecular determinants of the preselection Vβ repertoire. Gopalakrishnan S, Majumder K, Predeus A, Huang Y, Koues OI, Verma-Gaur J, Loguercio S, Su AI, Feeney AJ, Artyomov MN, Oltz EM. Proc Natl Acad Sci U S A. 2013 Aug 20;110(34):E3206-15. doi:10.1073/pnas.1304048110. Epub 2013 Aug 5. PMID:23918392

Deep sequencing of the murine IgH repertoire reveals complex regulation of nonrandom v gene rearrangement frequencies Choi NM, Loguercio S, Verma-Gaur J, Degner SC, Torkamani A, Su AI, Oltz EM, Artyomov M, Feeney AJ. J Immunol. 2013 Sep 1;191(5):2393-402. doi: 10.4049/jimmunol.1301279. Epub 2013 Jul 29. PMID:23898036

Defining the transcriptional and cellular landscape of type 1 diabetes in the NOD mouse Carrero JA, Calderon B, Towfic F, Artyomov MN, Unanue ER. PLoS One. 2013;8(3):e59701. doi: 10.1371/journal.pone.0059701. Epub 2013 Mar 26. PMID:23555752

Last Updated: 1/14/2014 9:05:17 AM

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