Max Gordon

Works (5)

Updated: March 3rd, 2026 07:09

2026 article

KeySDL: sparse dictionary learning for keystone microbe identification from steady-state observations using a dynamical-systems model

Gordon, M., Akyol, T. Y., Amos, B., Andersen, S. U., & Williams, C. (2026, February 19). BioData Mining, Vol. 2.

By: M. Gordon n, T. Akyol *, B. Amos n, S. Andersen* & C. Williams n 

topics (OpenAlex): Gene Regulatory Network Analysis; Gaussian Processes and Bayesian Inference; Model Reduction and Neural Networks
Sources: NC State University Libraries, NC State University Libraries
Added: March 2, 2026

2024 article

Global genotype by environment prediction competition reveals that diverse modeling strategies can deliver satisfactory maize yield estimates

Washburn, J. D., Varela, J. I., Xavier, A., Chen, Q., Ertl, D., Gage, J. L., … Leon, N. (2024, November 22). (M. Sillanpää, Ed.). Genetics, Vol. 12.

By: J. Washburn *, J. Varela *, A. Xavier *, Q. Chen n , D. Ertl *, J. Gage n , J. Holland n , D. Lima * ...

Ed(s): M. Sillanpää

author keywords: genotype by environment; prediction; competition; maize; yield; phenotype
MeSH headings : Zea mays / genetics; Gene-Environment Interaction; Plant Breeding / methods; Models, Genetic; Genotype; Phenotype; Machine Learning
topics (OpenAlex): Genetics and Plant Breeding; Crop Yield and Soil Fertility; Genetic and phenotypic traits in livestock
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Sources: Web Of Science, ORCID, NC State University Libraries
Added: November 22, 2024

2022 article

FER and LecRK show haplotype-dependent cold-responsiveness and mediate freezing tolerance in Lotus japonicus

Mustamin, Y., Akyol, T. Y., Gordon, M., Manggabarani, A. M., Isomura, Y., Kawamura, Y., … Sato, S. (2022, November 30). PLANT PHYSIOLOGY, Vol. 191, pp. 1138–1152.

By: Y. Mustamin *, T. Akyol *, M. Gordon n, A. Manggabarani *, Y. Isomura*, Y. Kawamura*, M. Bamba *, C. Williams n , S. Andersen *, S. Sato *

MeSH headings : Lotus / metabolism; Haplotypes / genetics; Freezing; Acclimatization / genetics; Adaptation, Physiological / genetics; Gene Expression Regulation, Plant
topics (OpenAlex): Plant Reproductive Biology; Plant Molecular Biology Research; Plant Stress Responses and Tolerance
TL;DR: This work suggests that recruiting a conserved growth regulator gene, FER, and a receptor-like kinase gene, LecRK, into the set of cold-responsive genes has contributed to freezing tolerance and local climate adaptation in L. japonicus, offering functional genetic insight into perennial herb evolution. (via Semantic Scholar)
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2. Zero Hunger (Web of Science)
13. Climate Action (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: August 7, 2023

2022 article

Compositionality, sparsity, spurious heterogeneity, and other data-driven challenges for machine learning algorithms within plant microbiome studies

Busato, S., Gordon, M., Chaudhari, M., Jensen, I., Akyol, T., Andersen, S., & Williams, C. (2022, December 18). Current Opinion in Plant Biology, Vol. 71.

By: S. Busato n, M. Gordon n, M. Chaudhari  n, I. Jensen *, T. Akyol*, S. Andersen *, C. Williams n 

author keywords: Machine learning; Deep learning; Plant-associated microbiome; Compositional data analysis
MeSH headings : Microbiota; Algorithms; Machine Learning; Plants
topics (OpenAlex): Gut microbiota and health; Gene expression and cancer classification; Genomics and Phylogenetic Studies
TL;DR: The analysis is expanded to other fields to quantify the degree to which mitigation approaches improve the performance of ML and describe the mathematical basis for this. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, ORCID
Added: January 30, 2023

2020 journal article

Gene Regulatory Network Inference: Connecting Plant Biology and Mathematical Modeling

Frontiers in Genetics, 11.

By: L. Van den Broeck n , M. Gordon n, D. Inzé *, C. Williams n  & R. Sozzani n 

author keywords: gene regulatory network; network properties; network inference; machine learning; experimental methodologies
topics (OpenAlex): Gene Regulatory Network Analysis; Plant Molecular Biology Research; CRISPR and Genetic Engineering
TL;DR: This review provides examples of experimental methodologies commonly used to identify regulatory interactions and generate GRNs, and describes network inference techniques that leverage gene expression data to predict regulatory interactions. (via Semantic Scholar)
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Sources: Web Of Science, Crossref, NC State University Libraries, ORCID
Added: July 13, 2020

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