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Software developed by the Louca lab
Cariaco metabolic modeling
MATLAB code for inverse linear transport modeling (ILTM), estimation of eddy diffusivity based on the spatiotemporal distribution of a conserved tracer, and spatial metabolic flux (SMF) analysis of microbial systems near steady state, exemplified for the Cariaco Basin sub-euphotic water column.
Reference: Louca, S., Scranton, M. I., Taylor, G. T., Astor, Y. M., Crowe, S. A., Doebeli, M. (2019). Circumventing kinetics in biogeochemical modeling. PNAS 116:11329-11338
ILTM Cariaco estimated diffusivity
SMF idealizing chemical transition zones as hotspots
ILTM Cariaco estimated net metabolite production rates
SMF Cariaco predicted metabolite concentrations vs data
An R package for efficient phylogenetics on large trees.
Ancestral state reconstruction - schematic
castor benchmarks - set 1
castor benchmarks - set 2
castor benchmarks - set 3
Hidden state prediction - schematic
Database and software for mapping prokaryotic taxa to metabolic functional groups.
Reference: Louca, S., Parfrey, L. W., Doebeli, M. (2016). Decoupling function and taxonomy in the global ocean microbiome. Science 353:1272-1277
FAPROTAX schematic
FAPROTAX usage overview
Fast-reaction-transport modeling
MATLAB code demonstrating fast-reaction-transport biogeochemical models in 1-dimensional water and sediment columns.
Reference: Louca, S., Taylor, G. T, Astor, Y. M., Buck, K., Muller-Karger, F. E. (2022). Transport-limited reactions in microbial systems. Environmental Microbiology 25:268-282
MCM (Microbial Community Modeler)
A computational framework for modeling microbial communities using dynamic flux balance analysis of genome-based cell models, in the context of a dynamical environment. Classical functional group models are also supported.
Reference: Louca, S., Doebeli, M. (2015). Calibration and analysis of genome-based models for microbial ecology. eLife 4:e08208
MCM model-data comparison
MCM overview
MCM simulation - schematic
MCM simulation of methanogenic community
Metabolic fluxes predicted by MCM
peacots (Periodogram Peaks in Correlated Time Series)
An R package for detecting cyclicity in time series using the Ornstein-Uhlenbeck state-space model (rather than simple white noise) as a null hypothesis.
Reference: Louca, S., Doebeli, M. (2015). Detecting cyclicity in ecological time series. Ecology 96:1724-1732
peacots principle
Saanich GCM (Gene Centric Model)
Gene-centric biogeochemical model (MATLAB code) for the Saanich Inlet seasonally anoxic water column, under steady state conditions.
Reference: Louca, S., Hawley, A. K., Katsev, S., Torres-Beltran, M., Bhatia, M. P., Kheirandish, S., Michiels, C. C., Capelle, D., Lavik, G., Doebeli, M., Crowe, S. A., Hallam, S. J (2016). Integrating biogeochemistry with multiomic sequence information in a model oxygen minimum zone. PNAS 113:E5925-E5933
Saanich predicted mRNA and protein profiles
Saanich metabolic model
Saanich predicted chemical profiles

Louca lab. Department of Biology, University of Oregon, Eugene, USA
© 2023 Stilianos Louca all rights reserved