Author

K. Michael Martini

Emory UniversityORCID 0000-0002-5946-1122Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:C. elegans· 2 Research Focus:clustering· 2 Research Focus:host-pathogen & immune response· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Approach:deep learning· 1

Frequent Co-Authors

Ilya M. NemenmaniD· 2 shared Nic M. VegaiD· 2 shared Satya Spandana BodduiD· 2 shared Andrew D. B. LeakeyiD· 1 shared Ashish B. RajurkariD· 1 shared Dylan P. AlleniD· 1 shared Jeremy Ruhter· 1 shared Kinjalk Parth· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBiophysics

Ilya M. NemenmanORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

ROOTQUANT: AUTOMATED ROOT TRAIT QUANTIFICATION FROMMINIRHIZOTRON IMAGES USING DEEP LEARNING

Kinjalk Parth, Sebastián Varela, Zhiru Liu, K. Michael Martini, Ashish B. Rajurkar, Dylan P. Allen, Scott M. McCoy, Jeremy Ruhter, Samuel Walker, Nigel D. Goldenfeld, Andrew D. B. Leakey

RootQuant uses deep learning to automatically quantify root traits from minirhizotron images, achieving high accuracy across species without pixel-level annotations.

bioRxiv · Jul 8, 2026 · PreprintPlant Biology

Variance in C. elegans gut bacterial load suggests complex host-microbe dynamics

Satya Spandana Boddu, K. Michael Martini, Ilya M. Nemenman, Nic M. Vega

The paper investigates host-microbe dynamics in C. elegans by combining experiments and modeling, finding that stochastic switching between growth rate phenotypes explains observed bacterial load variation better than traditional models.

PLoS Computational Biology · Jun 9, 2025Peer-reviewedBiophysics

Correlations in microbial abundance data reveal host-bacteria and bacteria-bacteria interactions jointly shaping the C. elegans microbiome

K. Michael Martini, Satya Spandana Boddu, Megan N. Taylor, Ilya M. Nemenman, Nic M. Vega

The paper analyzes microbial abundance data in C. elegans to assess host-bacteria and bacteria-bacteria interactions, finding that neither model alone fully explains the observed correlations.

Physical Review Research · Dec 2, 2024Peer-reviewedBiophysics