Author

Miguel R. Pebes-Trujillo

Nanyang Technological UniversityORCID 0009-0001-0652-5161Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Plant Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Organism:plant (other)· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Assay:metabolomics· 1

Frequent Co-Authors

Aravind HarikumariD· 2 shared Itamar ShenhariD· 2 shared Ittai HerrmanniD· 2 shared Jie HeiD· 2 shared Kee Woei NgiD· 2 shared Matan GavishiD· 2 shared Menachem MoshelioniD· 2 shared Li Yi TaniD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 43 mutual co-author links

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2 shared papersPlant Biology

Aravind HarikumarORCID

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2 papers

Recent·Most cited

Designed nutrient-gradient phenotyping enables predictive ionomics of tropical leafy greens

Itamar Shenhar, Miguel R. Pebes-Trujillo, Aravind Harikumar, Zhitong Zhao, Li Yi Tan, Magdiel Inggrid Setyawati, Jie He, Ittai Herrmann, Kee Woei Ng, Matan Gavish, Menachem Moshelion

The paper uses a designed nutrient-gradient framework and machine learning to predict leaf ionome in tropical crops, achieving high predictive accuracy across unseen conditions.

bioRxiv · Sep 17, 2026 · PreprintPlant Biology

Harnessing Smartphone RGB Imagery and LiDAR Point Cloud for Enhanced Leaf Nitrogen and Shoot Biomass Assessment - Chinese Spinach as a Case Study

Aravind Harikumar, Itamar Shenhar, Miguel R. Pebes-Trujillo, Lin Qin, Menachem Moshelion, Jie He, Kee Woei Ng, Matan Gavish, Ittai Herrmann

This study uses smartphone RGB imagery and LiDAR data to accurately estimate leaf nitrogen concentration and shoot biomass in Chinese spinach, with low error rates.

Frontiers in Plant Science · Aug 13, 2025Peer-reviewedBioinformatics