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Dr. Samia Mora's group

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Hesam Dashti

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Hesam Dashti (Hesamaddin Torabi Dashti)
Postdoctoral Fellow,
Department of Medicine, Division of Preventive Medicine,
Brigham and Women's Hospital,
Harvard Medical School,
Boston, MA.
hdashti@bwh dot harvard dot edu
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Research interests

Personalized prevention of cardiovascular disease

Personalized medicine relies primarily on genomic variations. Alternatively, small molecule traits (e.g., metabolites, lipids, carbohydrates) reflect additional factors, including the microbiome and environmental factors. We are trying to use both sets of traits to develop integrative omics for improving personalized prevention of CVD.
Projects:
Machine learning and biomedicine

  • Hesam Dashti, Yanyan Liu, Robert J. Glynn, Paul M Ridker, Olga V. Demler, Samia Mora, CVD Risk Prediction Using Machine Learning Approaches
Biomarkers
  • Hesam Dashti, Olga Demler, Jonathan R. Wedell, William M. Westler, Hamid R. Eghbalnia, John L. Markley, and Samia Mora, Probabilistic identification of saccharide moieties in biomolecules and their protein complexes, Scientific Data volume 7, Article number: 210 (2020), https://doi.org/10.1038/s41597-020-0547-y
  • Hesam Dashti, William Westler, Jonathan Wedell, Olga Demler, Hamid Eghbalnia, John Markley, Samia Mora, Using machine learning methods for parameterization of NMR spin system matrices of small molecules
  • Hesam Dashti, Olga Demler, Jonathan R. Wedell, William M. Westler, Hamid R. Eghbalnia, John L. Markley, and Samia Mora, Probabilistic annotation of carbohydrate structures facilitates systematic organization of information on carbohydrates as inflammatory biomarkers

Small molecules

Small molecules, molecular fragments, and natural products are at the center of investigations for disease-specific biomarker discovery and designing new drugs. We are working on several computational modules for improving the identification and quantification of these chemical compounds.
Projects:
Cheminformatics Tool for Probabilistic Identification of Carbohydrates

  • Hesam Dashti, Olga Demler, Jonathan R. Wedell, William M. Westler, Hamid R. Eghbalnia, John L. Markley, and Samia Mora, Probabilistic identification of saccharide moieties in biomolecules and their protein complexes, Scientific Data volume 7, Article number: 210 (2020), https://doi.org/10.1038/s41597-020-0547-y
Atom Label Assignment Tool using InChI String (ALATIS)
  • Hesam Dashti, William M. Westler, John L. Markley, Hamid R. Eghbalnia, Unique identifiers for small molecules enable rigorous labeling of their atoms, Scientific Data 4, Article number: 170073 (2017), doi:10.1038/sdata.2017.73, https://www.nature.com/articles/sdata201773
  • Hesam Dashti , Jonathan R. Wedell , William M. Westler , John L. Markley, Hamid R. Eghbalnia, Automated evaluation of consistency within the PubChem Compound database, Scientific Data volume 6, Article number: 190023 (2019), doi:10.1038/sdata.2019.23, https://www.nature.com/articles/sdata201923
  • Hesam Dashti, Jonathan R. Wedell, Gabriel Cornilescu, Charles D. Schwieters, William M. Westler, John L. Markley, Hamid R. Eghbalnia, Robust nomenclature and software for enhanced reproducibility in molecular modeling of small molecules, BioRxiv, https://doi.org/10.1101/429530
Guided Ideographic Spin System Model Optimization (GISSMO)
  • Hesam Dashti, William M. Westler, Marco Tonelli, Jonathan R. Wedell, John L. Markley, and Hamid R. Eghbalnia, Spin System Modeling of Nuclear Magnetic Resonance Spectra for Applications in Metabolomics and Small Molecule Screening, Analytical Chemistry, 2017, 89 (22), pp 12201–12208,doi:10.1021/acs.analchem.7b02884
  • Hesam Dashti, Jonathan R. Wedell, William M. Westler, Marco Tonelli, David Aceti, Gaya K. Amarasinghe, John L. Markley, and Hamid R. Eghbalnia, Applications of Parametrized NMR Spin Systems of Small Molecules, Analytical Chemistry, 2018, 90 (18), pp 10646–10649, DOI: 10.1021/acs.analchem.8b02660
  • Dries Sels, Hesam Dashti, Samia Mora, Olga Demler & Eugene Demler, Quantum approximate Bayesian computation for NMR model inference, Nature Machine Intelligence volume 2, pages396–402(2020), https://doi.org/10.1038/s42256-020-0198-x

FAIR data principles

Promoting findable, accessible, interoperable and reusable principles
Projects:
NMR-STAR

  • Eldon L. Ulrich, Kumaran Baskaran, Hesam Dashti, Yannis E. Ioannidis, Miron Livny, Pedro R. Romero, Dimitri Maziuk, Jonathan R. Wedell, Hongyang Yao, Hamid R. Eghbalnia, Jeffrey C. Hoch, and John L. Markley, NMR-STAR: comprehensive ontology for representing, archiving and exchanging data from nuclear magnetic resonance spectroscopic experiments, Journal of Biomolecular NMR, 73 (1), 5-9, PMID: 30580387, PMCID: PMC6441402, DOI: 10.1007/s10858-018-0220-3
NMReData
  • Marion Pupier, Jean-Marc Nuzillard, Julien Wist, Nils E. Schlörer, Stefan Kuhn, Mate Erdelyi, Christoph Steinbeck, Antony J. Williams, Craig Butts, Tim D. W. Claridge, Bozhana Mikhova, Wolfgang Robien, Hesam Dashti, Hamid R. Eghbalnia, Christophe Farès, Christian Adam, Pavel Kessler, Fabrice Moriaud, Mikhail Elyashberg, Dimitris Argyropoulos, Manuel Pérez, Patrick Giraudeau, Roberto R. Gil, Paul Trevorrow, and Damien Jeannerat, NMReDATA, a standard to report the NMR assignment and parameters of organic compounds, Magnetic resonance in chemistry, 56 (8), 703-715, PMID: 29656574, PMCID: PMC6226248, DOI: 10.1002/mrc.4737

Research funding:


Current
  • National Heart Lung and Blood Institute T32 HL007575
Previous
  • NMRFAM: National Institute of General Medical Sciences P41GM103399
  • NMRbox: National Institute of General Medical Sciences P41GM111135
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