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Homa MohammadiPeyhani
Homa MohammadiPeyhani
PhD student, EPFL
Verified email at epfl.ch
Title
Cited by
Cited by
Year
Enzyme annotation for orphan and novel reactions using knowledge of substrate reactive sites
N Hadadi, H MohammadiPeyhani, L Miskovic, M Seijo, V Hatzimanikatis
Proceedings of the National Academy of Sciences 116 (15), 7298-7307, 2019
802019
A computational workflow for the expansion of heterologous biosynthetic pathways to natural product derivatives
J Hafner, J Payne, H MohammadiPeyhani, V Hatzimanikatis, C Smolke
Nature Communications 12 (1), 1760, 2021
482021
Updated ATLAS of biochemistry with new metabolites and improved enzyme prediction power
J Hafner, H MohammadiPeyhani, A Sveshnikova, A Scheidegger, ...
ACS synthetic biology 9 (6), 1479-1482, 2020
402020
Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx
H MohammadiPeyhani, J Hafner, A Sveshnikova, V Viterbo, ...
Nature Communications 13 (1), 1560, 2022
292022
Computational tools and resources for designing new pathways to small molecules
A Sveshnikova, H MohammadiPeyhani, V Hatzimanikatis
Current Opinion in Biotechnology 76, 102722, 2022
122022
A workflow for annotating the knowledge gaps in metabolic reconstructions using known and hypothetical reactions
E Vayena, A Chiappino-Pepe, H MohammadiPeyhani, Y Francioli, ...
Proceedings of the National Academy of Sciences 119 (46), e2211197119, 2022
82022
NICEdrug. ch, a workflow for rational drug design and systems-level analysis of drug metabolism
H MohammadiPeyhani, A Chiappino-Pepe, K Haddadi, J Hafner, ...
Elife 10, e65543, 2021
82021
ATLASx: a computational map for the exploration of biochemical space
H Mohammadi-Peyhani, J Hafner, A Sveshnikova, V Viterbo, ...
BioRxiv, 2021.02. 17.431583, 2021
62021
ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds
A Sveshnikova, H MohammadiPeyhani, V Hatzimanikatis
Metabolic Engineering 72, 259-274, 2022
32022
Knowledge of the neighborhood of the reactive site up to three atoms can predict biochemistry and protein sequences
N Hadadi, H MohamadiPeyhani, L Miskovic, M Seijo, V Hatzimanikatis
bioRxiv, 210039, 2017
22017
Enzyme promiscuous profiles for protein sequence and reaction annotation
H MohammadiPeyhani, A Sveshnikova, L Miskovic, V Hatzimanikatis
bioRxiv, 2023.09. 13.557547, 2023
12023
NICEgame: A workflow for annotating the knowledge gaps in metabolic reconstructions, using known and hypothetical reactions
E Vayena, A Chiappino-Pepe, H MohammadiPeyhani, Y Francioli, ...
bioRxiv, 2022.02. 10.479881, 2022
12022
Supplementary dataset for Enzyme promiscuous profiles for protein sequence and reaction annotation
H Mohammadi Peyhani, A Sveshnikova, L Miskovic, V Hatzimanikatis
Zenodo, 2023
2023
Bridging the gap between rule-based expert systems and machine learning in computer-aided retrosynthetic design
D Probst, A Sveshnikova, HM Peyhani, V Hatzimanikatis, T Laino
American Chemical Society (ACS) Fall Meeting, 2022
2022
Supplementary datasets for" ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds"
A Sveshnikova, H Mohammadi Peyhani, V Hatzimanikatis
EPFL Infoscience, 2022
2022
Pathway Design
J Hafner, H Mohammadi‐Peyhani, V Hatzimanikatis
Metabolic Engineering: Concepts and Applications 13, 237-257, 2021
2021
Pathway Design
H Jasmin, MP Homa, H Vassily
Metabolic Engineering: Concepts and Applications 13, 2021
2021
Database for drug metabolism and comparisons, NICEdrug. ch, aids discovery and design
H MohammadiPeyhani, A Chiappino-Pepe, K Haddadi, J Hafner, ...
bioRxiv, 2020.05. 28.120782, 2020
2020
Algorithms and flowchart for the design of synthetic biochemical networks
H Mohammadi Peyhani
EPFL, 2020
2020
Assigning enzyme sequences to orphan and novel reactions using knowledge of substrate reactive sites
N Hadadi, H MohamadiPeyhani, L Miskovic, M Seijo, V Hatzimanikatis
2017
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