Author

Noor S. Mohammed

Iowa State University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Molecular Biology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:contrastive learning· 1 Approach:graph neural network· 1 Approach:machine learning (classical)· 1 Assay:metabolomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Angel FrazieriD· 2 shared B. ArunrajiD· 2 shared Jacek A. KozieliD· 2 shared Karuna Anna SajeevaniD· 2 shared Matthew R BeckiD· 2 shared Randy AryeeiD· 2 shared Ratul ChowdhuryiD· 2 shared Supantha DeyiD· 2 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersSystems Biology

Angel FrazierORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Structural and Metabolic Characterization of Ni(I)-inhibitors Provide a Robust Anti-Methanogenicity Scoring System

Randy Aryee, Mohammad Reza Zargar, Vaishnavey SR, B. Arunraj, Noor S. Mohammed, Supantha Dey, Karuna Anna Sajeevan, Angel Frazier, Jacek A. Koziel, Matthew R Beck, Thomas J. Mansell, Ratul Chowdhury

The paper develops a scoring system to identify effective anti-methanogenic compounds by analyzing their structural and metabolic properties.

bioRxiv · Feb 27, 2026 · PreprintSystems Biology

Exploring putative enteric methanogenesis inhibitors using molecular simulations and a graph neural network

Randy Aryee, Noor S. Mohammed, Supantha Dey, B. Arunraj, Swathi Nadendla, Karuna Anna Sajeevan, Matthew R Beck, Angel Frazier, Jacek A. Koziel, Thomas J. Mansell, Ratul Chowdhury

This paper uses molecular simulations and a graph neural network to identify potential methanogenesis inhibitors and their biochemical properties.

bioRxiv · Sep 16, 2024 · PreprintMolecular Biology