Author

Zahmeeth Sakkaff

Argonne National LaboratoryORCID 0000-0001-7779-9971Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:bacteria (other)· 2 Approach:machine learning (classical)· 2 Assay:metagenomics· 2 Approach:statistical model· 2 Research Focus:variant effect prediction· 2 Research Focus:benchmarking· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1

Frequent Co-Authors

Christopher S. HenryiD· 4 shared Andrew FreiburgeriD· 2 shared Dileep KishoreiD· 2 shared Janaka N. EdirisingheiD· 2 shared Massimiliano PieroboniD· 2 shared Mikaela CashmaniD· 2 shared Myra B. CoheniD· 2 shared Adam P. ArkiniD· 1 shared

Activity by Year

2023-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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4 shared papersBioinformatics

Christopher S. HenryORCID

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Author profile →

4 papers

Recent·Most cited

Data coherence over data volume drives generalisable genome-based prediction of microbial carbon utilisation

Dileep Kishore, Priya Ranjan, Christopher J. Neely, Mikaela Cashman, Zahmeeth Sakkaff, William J. Riehl, Marcin P. Joachimiak, Janaka N. Edirisinghe, José P. Faria, Pamela B. Weisenhorn, Myra B. Cohen, Dale A. Pelletier, Robert W. Cottingham, Christopher S. Henry, Mitchel J. Doktycz, , Paramvir Dehal

This study shows that filtering genomes based on coherent genotype-phenotype relationships improves cross-dataset prediction of microbial carbon utilisation, outperforming larger but less coherent datasets.

bioRxiv · Aug 12, 2026 · PreprintBioinformatics

Information- and Communication-Centric Approach in Cell Metabolism for Analyzing Behavior of Microbial Communities

Zahmeeth Sakkaff, Andrew Freiburger, Nidhi Gupta, Massimiliano Pierobon, Christopher S. Henry

The paper develops a community mutual information model to quantify information flow in microbial communities and demonstrates its application using simulated ecosystems.

bioRxiv · Aug 23, 2023 · PreprintBioinformatics

Machine Learning-Driven Phenotype Predictions based on Genome Annotations

Janaka N. Edirisinghe, Samaksh Goyal, Alexander Brace, Zahmeeth Sakkaff, Venkat Sai Suman Lamba Karanam, Dileep Kishore, Ricardo Colasanti, Tianhao Gu, Boris Sadhkin, Qizhi Zhang, Roy T. Kamimura, Christopher S. Henry

This paper develops a machine learning framework using genome annotations to predict bacterial phenotypes, achieving high accuracy for Gram-stain type and respiration type.

bioRxiv · Aug 11, 2023 · PreprintSystems Biology

A Molecular Communication model for cellular metabolism

Zahmeeth Sakkaff, Andrew Freiburger, Jennie L. Catlett, Mikaela Cashman, Aditya Immaneni, Nicole R. Buan, Myra B. Cohen, Christopher S. Henry, Massimiliano Pierobon

The paper develops a molecular communication model integrating metabolic modeling and information theory to analyze how environmental perturbations affect cellular metabolism.

bioRxiv · Jun 28, 2023 · PreprintBioinformatics