Hosein Mohimani, Ph.D.
Affiliations: | 2013 | Electrical Engineering | University of California, San Diego, La Jolla, CA |
Area:
Bioinformatics Biology, PharmacyGoogle:
"Hosein Mohimani"Parents
Sign in to add mentor| Pavel A. Pavezner | grad student | 2013 | UCSD | |
| (Bioinformatics Methods for Natural Product Discovery.) | ||||
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Publications
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| Lee YY, Guler M, Chigumba DN, et al. (2023) HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search. Nature Communications. 14: 4219 |
| Kunyavskaya O, Tagirdzhanov AM, Caraballo-Rodríguez AM, et al. (2021) Nerpa: A Tool for Discovering Biosynthetic Gene Clusters of Bacterial Nonribosomal Peptides. Metabolites. 11 |
| Behsaz B, Bode E, Gurevich A, et al. (2021) Publisher Correction: Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery. Nature Communications. 12: 4318 |
| Behsaz B, Bode E, Gurevich A, et al. (2021) Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery. Nature Communications. 12: 3225 |
| Nothias LF, Petras D, Schmid R, et al. (2020) Feature-based molecular networking in the GNPS analysis environment. Nature Methods |
| van der Hooft JJJ, Mohimani H, Bauermeister A, et al. (2020) Linking genomics and metabolomics to chart specialized metabolic diversity. Chemical Society Reviews |
| Behsaz B, Mohimani H, Gurevich A, et al. (2019) De Novo Peptide Sequencing Reveals Many Cyclopeptides in the Human Gut and Other Environments. Cell Systems |
| Cao L, Gurevich A, Alexander KL, et al. (2019) MetaMiner: A Scalable Peptidogenomics Approach for Discovery of Ribosomal Peptide Natural Products with Blind Modifications from Microbial Communities. Cell Systems |
| Cao L, Shcherbin E, Mohimani H. (2019) A Metabolome- and Metagenome-Wide Association Network Reveals Microbial Natural Products and Microbial Biotransformation Products from the Human Microbiota. Msystems. 4 |
| Meleshko D, Mohimani H, Traccana V, et al. (2019) BiosyntheticSPAdes: Reconstructing Biosynthetic Gene Clusters From Assembly Graphs. Genome Research |