{"id":18258203,"url":"https://github.com/ginkgobioworks/geckopy","last_synced_at":"2025-10-25T05:09:37.826Z","repository":{"id":58123154,"uuid":"346069489","full_name":"ginkgobioworks/geckopy","owner":"ginkgobioworks","description":"Enzyme-constrained genome-scale models in python","archived":false,"fork":false,"pushed_at":"2023-10-25T08:39:05.000Z","size":5074,"stargazers_count":26,"open_issues_count":6,"forks_count":7,"subscribers_count":5,"default_branch":"master","last_synced_at":"2025-04-04T18:39:03.986Z","etag":null,"topics":["data-integration","enzyme-constraints","kinetics","omics","proteomics","systems-biology","thermodynamics"],"latest_commit_sha":null,"homepage":"https://geckopy.readthedocs.io/en/latest/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ginkgobioworks.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":"CONTRIBUTING.rst","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2021-03-09T16:22:54.000Z","updated_at":"2025-03-27T05:01:35.000Z","dependencies_parsed_at":"2023-01-19T04:02:13.890Z","dependency_job_id":"f7f8d0f4-318d-4f05-9b7f-027b21b5b1f7","html_url":"https://github.com/ginkgobioworks/geckopy","commit_stats":{"total_commits":164,"total_committers":2,"mean_commits":82.0,"dds":0.07317073170731703,"last_synced_commit":"483936200ff0090bcea09944f882549f61c9fe3f"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ginkgobioworks/geckopy","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ginkgobioworks%2Fgeckopy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ginkgobioworks%2Fgeckopy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ginkgobioworks%2Fgeckopy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ginkgobioworks%2Fgeckopy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ginkgobioworks","download_url":"https://codeload.github.com/ginkgobioworks/geckopy/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ginkgobioworks%2Fgeckopy/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265059403,"owners_count":23705216,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-integration","enzyme-constraints","kinetics","omics","proteomics","systems-biology","thermodynamics"],"created_at":"2024-11-05T10:29:36.792Z","updated_at":"2025-10-25T05:09:37.750Z","avatar_url":"https://github.com/ginkgobioworks.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"geckopy\n=======\n\n.. image:: https://github.com/ginkgobioworks/geckopy/actions/workflows/main.yml/badge.svg\n   :target: https://github.com/ginkgobioworks/geckopy/actions\n   :alt: CI build\n\n**G**\\ enome-scale model **E**\\ nzyme **C**\\ onstraints, using **K**\\ inetics and \n**O**\\ mics in **py**\\ thon.\n\nBy combining kcats and proteomics measurement, geckopy allows for improving\nthe modeling capabilities in genome-scale models.\n\n..\n\n   Based on `Sánchez et al., 2017`_.\n\n   Citing geckopy: `Carrasco et al., 2023`_.\n\n\nCheck https://github.com/SysBioChalmers/GECKO for the matlab counterpart.\n\nOverview\n--------\n\nLoad a model.\n\n.. code-block:: python\n\n   import geckopy\n\n   model = geckopy.io.read_sbml_ec_model(\"tests/data/eciML1515.xml.gz\")\n   model.optimize()\n\nAdd copy number experimental data.\n\n.. code-block:: python\n\n   import pandas as pd\n   from geckopy.experiment import from_copy_number\n\n   raw_proteomics = pd.read_csv(\"tests/data/ecoli_proteomics_schmidt2016S5.tsv\")\n   exp_model = from_copy_number(\n       model,\n       index=raw_proteomics[\"uniprot\"],\n       cell_copies=raw_proteomics[\"copies_per_cell\"],\n       stdev=raw_proteomics[\"stdev\"],\n       vol=2.3,\n       dens=1.105e-12,\n       water=0.3,\n   )\n   exp_model.optimize()\n\nAdd pool constraint.\n\n.. code-block:: python\n\n   # add some molecular weights to the proteins if the model does not have them\n   for prot in ec_model.proteins:\n       prot.mw = 330\n   exp_model.constrain_pool(\n       p_measured=12.,\n       sigma_saturation_factor=0.8,\n       fn_mass_fraction_unmeasured_matched=0.2,\n   )\n   print(exp_model.optimize())\n   print(exp_model.protein_pool_exchange)\n\nBuild the documentation\n-----------------------\nTo build the documentation locally, run \n\n.. code-block:: shell\n\n  cd docs\n  pip install -r requirements.txt\n  make ipy2rst  # if there are notebooks for the docs at docs/notebooks\n  make html\n\n\nLicense\n-------\nCopyright 2021 Ginkgo Bioworks.\n\nLicensed under Apache License, Version 2.0, (LICENSE_ or\nhttp://www.apache.org/licenses/LICENSE-2.0).\n\nContribution\n~~~~~~~~~~~~\nUnless you explicitly state otherwise, any contribution intentionally submitted\nfor inclusion in the work by you, as defined in the Apache-2.0 license, shall \nbe licensed as above, without any additional terms or conditions.\n\n.. _Sánchez et al., 2017: https://dx.doi.org/10.15252/msb.20167411\n.. _Carrasco et al., 2023: https://doi.org/10.1128/spectrum.01705-23\n.. _LICENSE: ./LICENSE\n.. _virtualenv: https://pypi.python.org/pypi/virtualenv\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fginkgobioworks%2Fgeckopy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fginkgobioworks%2Fgeckopy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fginkgobioworks%2Fgeckopy/lists"}