{"id":507,"date":"2023-12-20T12:01:19","date_gmt":"2023-12-20T20:01:19","guid":{"rendered":"https:\/\/dornsife.usc.edu\/levine\/?page_id=507"},"modified":"2026-04-01T17:51:04","modified_gmt":"2026-04-02T00:51:04","slug":"modeling","status":"publish","type":"page","link":"https:\/\/dornsife.usc.edu\/levine\/modeling\/","title":{"rendered":"Model Code"},"content":{"rendered":"\n\n  \n    \n\n\n\n\n\n\n<div\n  class=\"cc--component-container cc--rich-text \"\n\n  \n  \n  \n  \n  \n  \n  >\n  <div class=\"c--component c--rich-text\"\n    \n      >\n\n    \n      \n<div class=\"f--field f--wysiwyg\">\n\n    \n  <p><span style=\"font-weight: 400;\">Levine Lab research has generated a range of numerical models from cellular-scale proteome allocation models to water column biogeochemical models.\u00a0 We are committed to keeping our work accessible and open source to promote knowledge sharing within and beyond the scientific community. Below, you will find numerous resources on our different models and their intended purposes.<\/span><\/p>\n\n\n\n<\/div>\n\n\n  <\/div><\/div>\n\n\n\n\n\n  \n  \n    \n    \n  \n    \n    \n  \n    \n    \n  \n    \n    \n  \n    \n    \n  \n    \n    \n  \n    \n    \n  \n    \n    \n  \n    \n  \n\n  \n    \n\n\n\n\n\n\n<div\n  class=\"cc--component-container cc--interactive-content-pane \"\n\n  \n  \n  \n  \n  \n  \n  >\n  <div class=\"c--component c--interactive-content-pane\"\n    \n      >\n\n    \n<div class=\"inner-wrapper\">\n  <div class=\"left\">\n              \n<div class=\"f--field f--section-title\">\n\n    \n  <h2>\n           \n      <\/h2>\n\n\n<\/div>\n      \n    <div class=\"pagination-wrapper\">\n      <ul class=\"interactive-content-pane-pagination\"><\/ul>\n    <\/div>\n  <\/div>\n\n  <div class=\"right\">\n          <div class=\"swiper\">\n        <div class=\"swiper-wrapper\">\n                      <div class=\"swiper-slide\">\n              <h3 class=\"pane-title\">\n                Phytoplankton Proteome Model\n              <\/h3>\n                                  \n<div class=\"f--field f--description\">\n\n    \n  <p><span style=\"font-weight: 400;\">We developed a proteome allocation model for phytoplankton that optimizes for cell size, the relative investment into different protein pools, and the concentration of different macromolecules in order to maximize growth rate according to temperature, light, and external inorganic nutrient availability.<\/span><\/p>\n<p>Read the paper where we used this model <a href=\"https:\/\/www.science.org\/doi\/10.1126\/sciadv.adh8043\">here<\/a><\/p>\n<p>Find the model code <a href=\"https:\/\/github.com\/LevineLab\/ProteomePhyto\">here<\/a><\/p>\n\n\n\n<\/div>\n                          \n  \n                          <\/div>\n                      <div class=\"swiper-slide\">\n              <h3 class=\"pane-title\">\n                Bacterial Guild Identification (CarveWe)\n              <\/h3>\n                                  \n<div class=\"f--field f--description\">\n\n    \n  <p><strong>CarveWe<\/strong> is a comprehensive workflow that integrates other open source tools, chiefly the CarveMe model annotation [software](https:\/\/github.com\/cdanielmachado\/carveme), and offers several distinct applications for metabolic modeling. Principally the complete workflow was designed to apply SOM neural networks to feature data of metabolic sensitivities based on <em>i<\/em><em>n silico<\/em> nutrient limitation tests in order to group marine heterotrophic organisms into functional cohorts.<\/p>\n<p>Read the paper where we used this model <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2024.05.29.596556v1.abstract\">here<\/a><\/p>\n<p>Find the model code <a href=\"https:\/\/github.com\/LevineLab\/CarveWe\">here<\/a><\/p>\n\n\n\n<\/div>\n                          \n  \n                          <\/div>\n                      <div class=\"swiper-slide\">\n              <h3 class=\"pane-title\">\n                Bacterial Proteome Model\n              <\/h3>\n                                  \n<div class=\"f--field f--description\">\n\n    \n  <p><span style=\"font-weight: 400;\">The model represents molecular-level transport and cellular proteome allocation specifically designed to compare the performance of ABC transport and PTS.<\/span><\/p>\n<p>Read the paper where we used this model <a href=\"https:\/\/journals.plos.org\/ploscompbiol\/articleid=10.1371\/journal.pcbi.1009023\">here<\/a><\/p>\n<p><span style=\"font-weight: 400;\">Find the model code <a href=\"https:\/\/github.com\/noelenorris\/ABC_proteome_allocation\">here<\/a><\/span><\/p>\n<p><br style=\"font-weight: 400;\" \/><br style=\"font-weight: 400;\" \/><\/p>\n\n\n\n<\/div>\n                          \n  \n                          <\/div>\n                      <div class=\"swiper-slide\">\n              <h3 class=\"pane-title\">\n                Particle Degradation Model\n              <\/h3>\n                                  \n<div class=\"f--field f--description\">\n\n    \n  <p><span style=\"font-weight: 400;\">This model captures key micro-scale dynamics occurring on particulate organic carbon (POC) in a manner scalable to the water column. We represent 18 groups of particle-associated heterotrophic microbes, encounter rates, enzymatic production and degradation of POC, and dynamic sinking rates.<\/span><\/p>\n<p>Read the paper where we used this model <a href=\"https:\/\/www.nature.com\/articles\/s41467-022-29297-2\">here<\/a><\/p>\n<p>Find the model code <a href=\"https:\/\/github.com\/LevineLab\/POMmodel\">here<\/a><\/p>\n<p><br style=\"font-weight: 400;\" \/><br style=\"font-weight: 400;\" \/><\/p>\n\n\n\n<\/div>\n                          \n  \n                          <\/div>\n                      <div class=\"swiper-slide\">\n              <h3 class=\"pane-title\">\n                AB Guild Model\n              <\/h3>\n                                  \n<div class=\"f--field f--description\">\n\n    \n  <p><span style=\"font-weight: 400;\">This model extracts a low-dimensional representation of binary data into groups of features that are tightly linked and co-occur with high specificity. The model pipeline is designed for use with binary presence\/absence data of genomic features (e.g., presence\/absence of genes, KO pathways, metabolic reaction components, etc.) to identify marine microbial functional guilds as an alternative to taxonomic community structure.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Read the paper where we used this model <a href=\"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmicb.2023.1197329\/full\">here<\/a><\/span><\/p>\n<p>Find the model code <a href=\"https:\/\/github.com\/LevineLab\/AB-guilds_model\">here<\/a><\/p>\n<p><br style=\"font-weight: 400;\" \/><br style=\"font-weight: 400;\" \/><\/p>\n\n\n\n<\/div>\n                          \n  \n                          <\/div>\n                      <div class=\"swiper-slide\">\n              <h3 class=\"pane-title\">\n                TRACE Model\n              <\/h3>\n                                  \n<div class=\"f--field f--description\">\n\n    \n  <p><span style=\"font-weight: 400;\">The TRAit Correlation Evolution (TRACE) model framework simulates the adaptive walk of a microbial population across a trait landscape (trait-scape) towards a high-fitness area.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Read the paper where we used this model <a href=\"https:\/\/royalsocietypublishing.org\/doi\/full\/10.1098\/rspb.2021.0940\">here<\/a><\/span><\/p>\n<p>Find the model code <a href=\"https:\/\/github.com\/LevineLab\/TRACE\">here<\/a><\/p>\n<p><br style=\"font-weight: 400;\" \/><br style=\"font-weight: 400;\" \/><\/p>\n\n\n\n<\/div>\n                          \n  \n                          <\/div>\n                      <div class=\"swiper-slide\">\n              <h3 class=\"pane-title\">\n                EpiGen Model\n              <\/h3>\n                                  \n<div class=\"f--field f--description\">\n\n    \n  <p><span style=\"font-weight: 400;\">An individual-based model of adaptation modified from Fisher\u2019s model in which the simulated population moved between the \u201cnew\u201d and \u201cancestral\u201d environments. Adaptation is driven by both fast variation, low transmission and slow variation, high transmission modifications.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Read the paper where we used this model <a href=\"https:\/\/www.pnas.org\/content\/early\/2020\/02\/28\/1919332117\">here<\/a><\/span><\/p>\n<p>Find the model code <a href=\"https:\/\/github.com\/LevineLab\/EpiGen\">here<\/a><\/p>\n<p><br style=\"font-weight: 400;\" \/><br style=\"font-weight: 400;\" \/><\/p>\n\n\n\n<\/div>\n                          \n  \n                          <\/div>\n                      <div class=\"swiper-slide\">\n              <h3 class=\"pane-title\">\n                EcoTRACE &#8211; coming soon!\n              <\/h3>\n                                  \n<div class=\"f--field f--description\">\n\n    \n  <p><span style=\"font-weight: 400;\">This model combines a quota-based phytoplankton model with a stochastic evolution step for certain traits (similar to the TRACE model). The goal of this model is to explore the possible evolutionary trajectories within phytoplankton and their effect on intra- and interspecific population dynamics.<\/span><\/p>\n\n\n\n<\/div>\n                          \n  \n                          <\/div>\n                      <div class=\"swiper-slide\">\n              <h3 class=\"pane-title\">\n                Plastic Model &#8211; coming soon!\n              <\/h3>\n                                  \n<div class=\"f--field f--description\">\n\n    \n  <p><span style=\"font-weight: 400;\">This model competes multiple populations of phytoplankton grown on a single nutrient and allows for specific nutrient response strategies to be toggled on or off for each population. <\/span><\/p>\n\n\n\n<\/div>\n                          \n  \n                          <\/div>\n                  <\/div>\n      <\/div>\n      <\/div>\n  \n<\/div>\n\n\n\n  <div class=\"background-images\">\n          <div class=\"swiper swiper-background-images\">\n        <div class=\"swiper-wrapper\">\n                      <div class=\"swiper-slide\">\n                          <\/div>\n\n                      <div class=\"swiper-slide\">\n                          <\/div>\n\n                      <div class=\"swiper-slide\">\n                          <\/div>\n\n                      <div class=\"swiper-slide\">\n                          <\/div>\n\n                      <div class=\"swiper-slide\">\n                          <\/div>\n\n                      <div class=\"swiper-slide\">\n                          <\/div>\n\n                      <div class=\"swiper-slide\">\n                          <\/div>\n\n                      <div class=\"swiper-slide\">\n                          <\/div>\n\n                      <div class=\"swiper-slide\">\n                          <\/div>\n\n                  <\/div>\n      <\/div>\n      <\/div>\n\n\n\n  <\/div><\/div>\n\n\n\n\n  \n    \n\n\n\n\n\n\n<div\n  class=\"cc--component-container cc--rich-text \"\n\n  \n  \n  \n  \n  \n  \n  >\n  <div class=\"c--component c--rich-text\"\n    \n      >\n\n    \n      \n<div class=\"f--field f--wysiwyg\">\n\n    \n  <p>All model code is also available directly on the <a href=\"https:\/\/github.com\/LevineLab\">Levine Lab GitHub<\/a><\/p>\n\n\n\n<\/div>\n\n\n  <\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":392,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-507","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - 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