Homa Mohammadi Peyhani

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New drugs are needed to assure effective therapies for previously untreated diseases, emerging diseases, and personalized medicine, but the process of drug development is complex, costly, and time-consuming. This is especially problematic considering that ...

The discovery of a drug requires over a decade of intensive research and financial investments – and still has a high risk of failure. To reduce this burden, we developed the NICEdrug.ch resource, which incorporates 250,000 bioactive molecules, and studied ...

The data and scripts used to produce, analyze, and visualize the results of the manuscript Enzyme promiscuous profiles for protein sequence and reaction annotation by Homa MohammadiPeyhani, Anastasia Sveshnikova, Ljubisa Miskovic, and Vassily Hatzimanikati ...

Nontyphoidal Salmonella strains (NTS) are among the most common foodborne enteropathogens and constitute a major cause of global morbidity and mortality, imposing a substantial burden on global health. The increasing antibiotic resistance of NTS bacteria h ...

Advances in medicine and biotechnology rely on a deep understanding of biological processes. Despite the increasingly available types and amounts of omics data, significant knowledge gaps remain, with current approaches to identify and curate missing annot ...

Supplementary datasets accompanying the manuscript "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds" published in the Metabolic Engineering Journal (https://doi.org/10.1016/j.ymben.2022.03.013). In line w ...

Homa Mohammadi Peyhani

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Algorithms and flowchart for the design of synthetic biochemical networks

NICEdrug.ch, a workflow for rational drug design and systems-level analysis of drug metabolism

Supplementary dataset for Enzyme promiscuous profiles for protein sequence and reaction annotation

Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine

A workflow for annotating the knowledge gaps in metabolic reconstructions using known and hypothetical reactions

Supplementary datasets for "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds"