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‎examples/Community Modeling/Index.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"![ModelSEEDpy](../images/ms-logo-horizontal.png)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Back to the main [Index](../Index.ipynb)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Community Modeling"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Community Modeling examples with modelseedpy models."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Examples"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"* [notebook1](notebook.ipynb) topic"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎examples/Escher/Index.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"![ModelSEEDpy](../images/ms-logo-horizontal.png)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Back to the main [Index](../Index.ipynb)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Escher Visualization"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The modelseedpy-escher integrates Escher with SEED Metabolic Models"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Examples"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"* [notebook1](notebook.ipynb) topic"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎examples/Flux Analysis/FBA Model functions.ipynb

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{
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"cell_type": "code",
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"execution_count": 121,
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"metadata": {
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"scrolled": false
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},
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"metadata": {},
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"outputs": [
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"name": "stdout",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.3"
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"version": "3.8.10"
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}
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},
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"nbformat": 4,

‎examples/Flux Analysis/Index.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Topics"
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"## Examples"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"* [IPython Kernel](IPython Kernel/Index.ipynb): IPython's core syntax and command line features available in all frontends\n",
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"* [Embedding](Embedding/Index.ipynb): Embedding and reusing IPython's components into other applications"
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"* [Flux Balance Analysis](FBAExampleNotebook.ipynb) Running Flux Balance Analysis\n",
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"* [Media Scan](MediaScan.ipynb) Testing Multiple Media"
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]
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},
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{

‎examples/Index.ipynb

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"* [Model Reconstruction](Model Reconstruction/Index.ipynb): Build SEED Models\n",
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"* [Flux Analysis](Flux Analysis/Index.ipynb): Run Flux Analysis Methods\n",
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"* [Community Modeling](Community Modeling/Index.ipynb): Community Modeling Notebooks\n",
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"* [Escher Visualization](Escher/Index.ipynb): Visualization of Pathway Maps with Escher\n",
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"* [KBase](KBase/Index.ipynb): KBase Interaction Notebooks\n",
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"* [Others](Others/Index.ipynb): Unsorted examples"
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]
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},

‎examples/KBase/Index.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"![ModelSEEDpy](../images/ms-logo-horizontal.png)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Back to the main [Index](../Index.ipynb)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# KBase"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The modelseedpy-kbase allows to interact with KBase workspace objects enabling data sharing and manipulation."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Examples"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"* [notebook1](notebook.ipynb) topic"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎examples/Model Reconstruction/Gapfilling.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6"
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"version": "3.8.10"
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}
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},
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"nbformat": 4,

‎examples/Model Reconstruction/Index.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Topics"
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"## Examples"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"* [IPython Kernel](IPython Kernel/Index.ipynb): IPython's core syntax and command line features available in all frontends\n",
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"* [Embedding](Embedding/Index.ipynb): Embedding and reusing IPython's components into other applications"
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"* [Genomes](Genomes.ipynb) Read genome\n",
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"* [Build Metabolic Model](build_metabolic_model.ipynb) Build Genome-Scale Metabolic Model\n",
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"* [Gapfilling](Gapfilling.ipynb) Gapfill Model\n",
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"* [Edit](add_ms_reaction.ipynb) Edit Model"
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]
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},
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{

‎examples/Others/Index.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"![ModelSEEDpy](../images/ms-logo-horizontal.png)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Back to the main [Index](../Index.ipynb)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Model Reconstruction"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The modelseedpy allows to build metabolic models from given genome. This section covers a variety of methods involved in model reconstruction and manipulation."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Examples"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"* [Genomes](Genomes.ipynb) Read genome\n",
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"* [Build Metabolic Model](build_metabolic_model.ipynb) Build Genome-Scale Metabolic Model\n",
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"* [Gapfilling](Gapfilling.ipynb) Gapfill Model\n",
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"* [Edit](add_ms_reaction.ipynb) Edit Model"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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