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Ali Zomorrodi, Ph.D.

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Mentoring
Available: 04/01/22, Expires: 12/29/23

The goal of this project is to construct computational genome-scale models of metabolism for the gut microbiota of healthy and diseased subjects. We will use these computational models to investigate how the gut microbiota functions in healthy vs. diseases subjects and how it is affected by variations with diet. Examples of diseases we are working on in this area include Celiac Disease, Inflammatory Bowel Disease, and Colorectal Cancer. Skills required: Familiarity with a computer programming language. Interested candidates should email a CV to Dr. Zomorrodi at azomorrodi@mgh.harvard.edu and briefly explain what their interests are. Please use “HMS Scholarly Project Opportunities” as the subject of your email.

Available: 04/01/22, Expires: 12/29/23

The goal of this project is to use bulk or single-cell transcriptional data from human tissues or cell lines to construct tissue- or cell line-specific genome-scale metabolic network models. We will use these models to computationally investigate how the human metabolic machinery responds to nutritional and microbial cues. Skills required: Familiarity with a computer programming language. Interested candidates should email a CV to Dr. Zomorrodi at azomorrodi@mgh.harvard.edu and briefly explain what their interests are. Please use “HMS Scholarly Project Opportunities” as the subject of your email.

Available: 04/01/22, Expires: 12/29/23

The goal of projects in this area is to develop efficient statistical analysis approaches and machine learning algorithms for the integrated analysis of longitudinal multi-omics data from the host and microbiome. Skills required: For the project involving the development of statistical approaches familiarity with statistical hypothesis testing and generalized linear models is needed. For projects involving machine learning, a basic familiarity with machine learning is a plus but not a requirement. Basic proficiency in computer programming (preferably R or Python) is required for both projects. Interested candidates should email a CV to Dr. Zomorrodi at azomorrodi@mgh.harvard.edu and briefly explain what their interests are. Please use “HMS Scholarly Project Opportunities” as the subject of your email.

Available: 01/10/22, Expires: 03/01/24

The goal of this project is to develop systems-level mechanistic computational models of immune cells (particularly macrophages) that integrate multiple intracellular biological processes at different scales including gene expression, metabolism, signal transduction, and gene regulation. We will use these computational models to dissect the immunometabolic response of macrophages to non-microbial and microbially-derived metabolites, and nutritional cues in the intestinal mucosa of healthy and diseased subjects. Skills required: Familiarity with a computer programming language. Interested candidates should email a CV to Dr. Zomorrodi at azomorrodi@mgh.harvard.edu and briefly explain what their interests are. Please use “HMS Scholarly Project Opportunities” as the subject of your email.


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Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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  1. Mehrotra I, Serena G, Cetinbas M, Kenyon V, Martin VM, Harshman SG, Zomorrodi AR, Sadreyev RI, Fasano A, Leonard MM. Characterization of the blood microbiota in children with Celiac disease. Current Research in Microbial Sciences. 2021; 2:100069. View Publication.
  2. Mehrotra I, Serena G, Cetinbas M, Kenyon V, Martin VM, Harshman SG, Zomorrodi AR, Sadreyev RI, Fasano A, Leonard MM. Characterization of the blood microbiota in children with Celiac disease. Curr Res Microb Sci. 2021 Dec; 2:100069. PMID: 34841359.
    Citations:    
  3. Leonard MM, Valitutti F, Karathia H, Pujolassos M, Kenyon V, Fanelli B, Troisi J, Subramanian P, Camhi S, Colucci A, Serena G, Cucchiara S, Trovato CM, Malamisura B, Francavilla R, Elli L, Hasan NA, Zomorrodi AR, Colwell R, Fasano A. Microbiome signatures of progression toward celiac disease onset in at-risk children in a longitudinal prospective cohort study. Proc Natl Acad Sci U S A. 2021 07 20; 118(29). PMID: 34253606.
    Citations: 7     Fields:    Translation:Humans
  4. Olshan KL, Zomorrodi AR, Pujolassos M, Troisi J, Khan N, Fanelli B, Kenyon V, Fasano A, Leonard MM. Microbiota and Metabolomic Patterns in the Breast Milk of Subjects with Celiac Disease on a Gluten-Free Diet. Nutrients. 2021 Jun 29; 13(7). PMID: 34210038.
    Citations: 1     Fields:    Translation:Humans
  5. Colarusso AV, Goodchild-Michelman I, Rayle I, Zomorrodi AR. Computational modeling of metabolism in microbial communities on a genome-scale. Current Opinion in Systems Biology. 2021; (26):46 - 57. View Publication.
  6. Olshan KL, Leonard MM, Serena G, Zomorrodi AR, Fasano A. Gut microbiota in Celiac Disease: microbes, metabolites, pathways and therapeutics. Expert Rev Clin Immunol. 2020 11; 16(11):1075-1092. PMID: 33103934.
    Citations: 3     Fields:    Translation:HumansAnimalsCells
  7. Leonard MM, Karathia H, Pujolassos M, Troisi J, Valitutti F, Subramanian P, Camhi S, Kenyon V, Colucci A, Serena G, Cucchiara S, Montuori M, Malamisura B, Francavilla R, Elli L, Fanelli B, Colwell R, Hasan N, Zomorrodi AR, Fasano A. Multi-omics analysis reveals the influence of genetic and environmental risk factors on developing gut microbiota in infants at risk of celiac disease. Microbiome. 2020 09 11; 8(1):130. PMID: 32917289.
    Citations: 17     Fields:    Translation:HumansCells
  8. Zomorrodi AR, Segrè D. Genome-driven evolutionary game theory helps understand the rise of metabolic interdependencies in microbial communities. Nat Commun. 2017 11 16; 8(1):1563. PMID: 29146901.
    Citations: 36     Fields:    
  9. Maranas, CD Zomorrodi, AR. Optimization methods in metabolic networks, John Wiley & Sons. 2016; 288. View Publication.
  10. Zomorrodi AR, Segrè D. Synthetic Ecology of Microbes: Mathematical Models and Applications. J Mol Biol. 2016 Feb 27; 428(5 Pt B):837-61. PMID: 26522937.
    Citations: 72     Fields:    
  11. Chowdhury A, Zomorrodi AR, Maranas CD. Bilevel optimization techniques in computational strain design. Computers & Chemical Engineering. 2015; 72:363-372. View Publication.
  12. Zomorrodi AR, Maranas CD. Coarse-grained optimization-driven design and piecewise linear modeling of synthetic genetic circuits. European Journal of Operational Research. 2014; 237(2):665-676. View Publication.
  13. Khodayari A, Zomorrodi AR, Liao JC, Maranas CD. A kinetic model of Escherichia coli core metabolism satisfying multiple sets of mutant flux data. Metab Eng. 2014 Sep; 25:50-62. PMID: 24928774.
    Citations: 49     Fields:    Translation:Cells
  14. Zomorrodi AR, Islam MM, Maranas CD. d-OptCom: Dynamic multi-level and multi-objective metabolic modeling of microbial communities. ACS Synth Biol. 2014 Apr 18; 3(4):247-57. PMID: 24742179.
    Citations: 65     Fields:    Translation:CellsPHPublic Health
  15. Chowdhury A, Zomorrodi AR, Maranas CD. k-OptForce: integrating kinetics with flux balance analysis for strain design. PLoS Comput Biol. 2014 Feb; 10(2):e1003487. PMID: 24586136.
    Citations: 33     Fields:    Translation:AnimalsCells
  16. Zomorrodi AR, Lafontaine Rivera JG, Liao JC, Maranas CD. Optimization-driven identification of genetic perturbations accelerates the convergence of model parameters in ensemble modeling of metabolic networks. Biotechnol J. 2013 Sep; 8(9):1090-104. PMID: 23450699.
    Citations: 6     Fields:    Translation:Cells
  17. Ranganathan S, Tee TW, Chowdhury A, Zomorrodi AR, Yoon JM, Fu Y, Shanks JV, Maranas CD. An integrated computational and experimental study for overproducing fatty acids in Escherichia coli. Metab Eng. 2012 Nov; 14(6):687-704. PMID: 23036703.
    Citations: 31     Fields:    Translation:Cells
  18. Zomorrodi AR, Suthers PF, Ranganathan S, Maranas CD. Mathematical optimization applications in metabolic networks. Metab Eng. 2012 Nov; 14(6):672-86. PMID: 23026121.
    Citations: 39     Fields:    Translation:Cells
  19. Wang N, Eckert KA, Zomorrodi AR, Xin P, Pan W, Shearer DA, Weisz J, Maranus CD, Clawson GA. Down-regulation of HtrA1 activates the epithelial-mesenchymal transition and ATM DNA damage response pathways. PLoS One. 2012; 7(6):e39446. PMID: 22761798.
    Citations: 17     Fields:    Translation:HumansCells
  20. Zomorrodi AR, Maranas CD. OptCom: a multi-level optimization framework for the metabolic modeling and analysis of microbial communities. PLoS Comput Biol. 2012 Feb; 8(2):e1002363. PMID: 22319433.
    Citations: 128     Fields:    Translation:Cells
  21. Zomorrodi AR, Maranas CD. Improving the iMM904 S. cerevisiae metabolic model using essentiality and synthetic lethality data. BMC Syst Biol. 2010 Dec 29; 4:178. PMID: 21190580.
    Citations: 43     Fields:    Translation:Animals
  22. Suthers PF, Zomorrodi A, Maranas CD. Genome-scale gene/reaction essentiality and synthetic lethality analysis. Mol Syst Biol. 2009; 5:301. PMID: 19690570.
    Citations: 74     Fields:    Translation:Cells
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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.