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fix typos in notebook text
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franciscozorrilla committed Jan 10, 2024
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28 changes: 14 additions & 14 deletions notebooks/1_fba.ipynb
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" <td>iMM904</td>\n",
" </tr><tr>\n",
" <td><strong>Memory address</strong></td>\n",
" <td>0x07faa4bcbf4f0</td>\n",
" <td>0x07feff150e670</td>\n",
" </tr><tr>\n",
" <td><strong>Number of metabolites</strong></td>\n",
" <td>1226</td>\n",
Expand All @@ -145,7 +145,7 @@
" </table>"
],
"text/plain": [
"<Model iMM904 at 0x7faa4bcbf4f0>"
"<Model iMM904 at 0x7feff150e670>"
]
},
"execution_count": 4,
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" <td><strong>Name</strong></td><td>Exo 1 3 beta glucan glucohydrase</td>\n",
" </tr><tr>\n",
" <td><strong>Memory address</strong></td>\n",
" <td>0x07faa59f2d700</td>\n",
" <td>0x07feff1985850</td>\n",
" </tr><tr>\n",
" <td><strong>Stoichiometry</strong></td>\n",
" <td>\n",
Expand All @@ -198,7 +198,7 @@
" "
],
"text/plain": [
"<Reaction 13BGHe at 0x7faa59f2d700>"
"<Reaction 13BGHe at 0x7feff1985850>"
]
},
"execution_count": 5,
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" <td><strong>Name</strong></td><td>Glucose-6-phosphate isomerase</td>\n",
" </tr><tr>\n",
" <td><strong>Memory address</strong></td>\n",
" <td>0x07faa5a804af0</td>\n",
" <td>0x07fefe0ac4be0</td>\n",
" </tr><tr>\n",
" <td><strong>Stoichiometry</strong></td>\n",
" <td>\n",
Expand All @@ -314,7 +314,7 @@
" "
],
"text/plain": [
"<Reaction PGI at 0x7faa5a804af0>"
"<Reaction PGI at 0x7fefe0ac4be0>"
]
},
"execution_count": 7,
Expand Down Expand Up @@ -357,7 +357,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"We can also view reaction upper and lower bounds, large numbers, typically around 1000 or more, are used as infinite limits (unconstained fluxes). \n",
"We can also view reaction upper and lower bounds, large numbers, typically around 1000 or more, are used as infinite limits (unconstrained fluxes). \n",
"Because the `pgi.lower_bound` < 0, and `pgi.upper_bound` > 0, pgi is reversible."
]
},
Expand Down Expand Up @@ -537,7 +537,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"We will consider cytosolic atp as our metabolite, which has the id `atp_c` in our test model. However, if you want to see the IDs of the frist N metabolites in the reconstruction, you can run the code below:"
"We will consider cytosolic atp as our metabolite, which has the id `atp_c` in our test model. However, if you want to see the IDs of the first N metabolites in the reconstruction, you can run the code below:"
]
},
{
Expand Down Expand Up @@ -604,19 +604,19 @@
" <td><strong>Name</strong></td><td>ATP C10H12N5O13P3</td>\n",
" </tr><tr>\n",
" <td><strong>Memory address</strong></td>\n",
" <td>0x07faa382fcd90</td>\n",
" <td>0x07feff161bf10</td>\n",
" </tr><tr>\n",
" <td><strong>Formula</strong></td><td>C10H12N5O13P3</td>\n",
" </tr><tr>\n",
" <td><strong>Compartment</strong></td><td>c</td>\n",
" </tr><tr>\n",
" <td><strong>In 149 reaction(s)</strong></td><td>\n",
" FRUK, GLYK, NADK, ACCOAC, RBK, ASNS1, DURIK1, GLUCYS, SHKK, CTPS2, PFK26, ADK1, PRAIS, PIN3K_SC, PRAGSr, HEX4, DHAK, GLNS, ARGSS, GLUK, HSK, GALKr, HMPK1, AASAD2, GTHS, FMNAT, THFGLUS, PYDXNK,...</td>\n",
" PNTK, NDPK7, PC, AASAD1, ASPTRS, METAT, NMNAT, FACOAL181, PFK_3, ATPPRT, HSK, PRPPS, ADNK1, ATPtm_H, INSK, ETHAK, PRAIS, LEUTRS, GMPS2, RNTR1, NNATr, RBFK, SLCBK1, DGK1, ARGSS, GLUK, PFK, NDPK1,...</td>\n",
" </tr>\n",
" </table>"
],
"text/plain": [
"<Metabolite atp_c at 0x7faa382fcd90>"
"<Metabolite atp_c at 0x7feff161bf10>"
]
},
"execution_count": 16,
Expand Down Expand Up @@ -766,7 +766,7 @@
" <td><strong>Name</strong></td><td>PGI1</td>\n",
" </tr><tr>\n",
" <td><strong>Memory address</strong></td>\n",
" <td>0x07faa59e7aac0</td>\n",
" <td>0x07feff18d3c10</td>\n",
" </tr><tr>\n",
" <td><strong>Functional</strong></td><td>True</td>\n",
" </tr><tr>\n",
Expand All @@ -776,7 +776,7 @@
" </table>"
],
"text/plain": [
"<Gene YBR196C at 0x7faa59e7aac0>"
"<Gene YBR196C at 0x7feff18d3c10>"
]
},
"execution_count": 21,
Expand Down Expand Up @@ -1066,7 +1066,7 @@
"source": [
"1. The distribution of predicted growth rates appears to be bimodal, with a small peak on the left and a larger peak on the right, can you explain why it has this shape? \n",
"2. Can you verify the consistency between gene and reactions knockouts results using a gene or a reaction of your choice?\n",
"3. Can you verify the essentiality of your gene of choice from the previous excercise using relevant databases (e.g. KEGG and the SGD)?\n",
"3. Can you verify the essentiality of your gene of choice from the previous exercise using relevant databases (e.g. KEGG and the SGD)?\n",
"4. Do you expect these results to change if we change the medium where we are growing our yeast model? "
]
},
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90 changes: 45 additions & 45 deletions notebooks/2_fba.ipynb
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Expand Up @@ -63,7 +63,7 @@
"source": [
"The availability of nutrients has a major impact on metabolic fluxes and `cobrapy` provides some helpers to manage the exchanges between the external environment and your metabolic model. In experimental settings the “environment” is usually constituted by the growth medium, i.e. the concentrations of all metabolites and co-factors available to the modeled organism. However, constraint-based metabolic models only consider fluxes. Thus, you cannot simply use concentrations since fluxes have the unit `mmol / [gram of dry-cell weight * hour]` (i.e. concentration per gram dry weight of cells and hour).\n",
"\n",
"Also, you are setting an upper bound for the particular import flux and not the flux itself. There are some crude approximations. For instance, if you supply 1 mmol of glucose every 24h to 1 gram of bacteria you might set the upper exchange flux for glucose to `1 mmol / [1 gDW * h]` since that is the nominal maximum that can be imported. There is no guarantee however that glucose will be consumed with that flux. Thus, the preferred data for exchange fluxes are direct flux measurements as the ones obtained from timecourse exa-metabolome measurements for instance.\n",
"Also, you are setting an upper bound for the particular import flux and not the flux itself. There are some crude approximations. For instance, if you supply 1 mmol of glucose every 24h to 1 gram of bacteria you might set the upper exchange flux for glucose to `1 mmol / [1 gDW * h]` since that is the nominal maximum that can be imported. There is no guarantee however that glucose will be consumed with that flux. Thus, the preferred data for exchange fluxes are direct flux measurements as the ones obtained from time-course exo-metabolome measurements for instance.\n",
"\n",
"So how does that look in COBRApy? The current growth medium of a model is managed by the medium attribute."
]
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{
"data": {
"text/plain": [
"[<Reaction EX_epistest_SC_e at 0x7feb92457ca0>,\n",
" <Reaction EX_epist_e at 0x7feb92457040>,\n",
" <Reaction EX_ergst_e at 0x7feb927caf70>,\n",
" <Reaction EX_ergstest_SC_e at 0x7feb927b6dc0>,\n",
" <Reaction EX_13BDglcn_e at 0x7feb927cab20>,\n",
" <Reaction EX_etha_e at 0x7feb927cafa0>,\n",
" <Reaction EX_2hb_e at 0x7feb927ca5b0>,\n",
" <Reaction EX_etoh_e at 0x7feb927cac40>,\n",
" <Reaction EX_fe2_e at 0x7feb927cab50>,\n",
" <Reaction EX_fecost_e at 0x7feb927caaf0>]"
"[<Reaction EX_epistest_SC_e at 0x7f81da468ca0>,\n",
" <Reaction EX_epist_e at 0x7f81da468040>,\n",
" <Reaction EX_ergst_e at 0x7f81b8c88fa0>,\n",
" <Reaction EX_ergstest_SC_e at 0x7f81b8c72e80>,\n",
" <Reaction EX_13BDglcn_e at 0x7f81b8c88b50>,\n",
" <Reaction EX_etha_e at 0x7f81b8c88fd0>,\n",
" <Reaction EX_2hb_e at 0x7f81b8c885e0>,\n",
" <Reaction EX_etoh_e at 0x7f81b8c88c70>,\n",
" <Reaction EX_fe2_e at 0x7f81b8c88b80>,\n",
" <Reaction EX_fecost_e at 0x7f81b8c88b20>]"
]
},
"execution_count": 6,
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"# Get genes IDs\n",
"id_essential_genes_v2=[gene.id for gene in essential_genes_v2]\n",
"\n",
"# Print number of esssential genes\n",
"# Print number of essential genes\n",
"print(\"Essential genes with ethanol carbon source:\",len(id_essential_genes_v2))"
]
},
Expand Down Expand Up @@ -522,50 +522,50 @@
{
"data": {
"text/plain": [
"['Q0275',\n",
" 'YDR298C',\n",
" 'YGR183C',\n",
" 'YBR196C',\n",
" 'YHR001W_A',\n",
" 'YEL024W',\n",
"['YHR001W_A',\n",
" 'YDR377W',\n",
" 'YBR039W',\n",
" 'YDL181W',\n",
" 'YDL067C',\n",
" 'Q0085',\n",
" 'Q0045',\n",
" 'YHR051W',\n",
" 'YPL078C',\n",
" 'YLR038C',\n",
" 'YLR395C',\n",
" 'YLL041C',\n",
" 'Q0130',\n",
" 'YCR012W',\n",
" 'YPR191W',\n",
" 'YKL060C',\n",
" 'YGL187C',\n",
" 'YJL166W',\n",
" 'YLR038C',\n",
" 'YFR033C',\n",
" 'YJR121W',\n",
" 'Q0045',\n",
" 'YML081C_A',\n",
" 'YHR051W',\n",
" 'YDL004W',\n",
" 'Q0105',\n",
" 'YKL016C',\n",
" 'YLR377C',\n",
" 'YBL045C',\n",
" 'YEL024W',\n",
" 'YPL262W',\n",
" 'YMR256C',\n",
" 'YER065C',\n",
" 'YGL191W',\n",
" 'Q0085',\n",
" 'YKL060C',\n",
" 'YKR097W',\n",
" 'Q0080',\n",
" 'YDR050C',\n",
" 'YJL166W',\n",
" 'YPR191W',\n",
" 'YGR183C',\n",
" 'YLR295C',\n",
" 'YDR298C',\n",
" 'YCR012W',\n",
" 'YGL187C',\n",
" 'YLR377C',\n",
" 'YBL045C',\n",
" 'YBL099W',\n",
" 'Q0105',\n",
" 'YDR529C',\n",
" 'YLR295C',\n",
" 'YKR097W',\n",
" 'YPL271W',\n",
" 'YDL067C',\n",
" 'Q0250',\n",
" 'YOR065W',\n",
" 'YER065C',\n",
" 'YBR039W',\n",
" 'YDR377W',\n",
" 'Q0080',\n",
" 'YJR121W',\n",
" 'YPL078C',\n",
" 'YGL191W']"
" 'YPL271W',\n",
" 'YBR196C',\n",
" 'Q0130',\n",
" 'YKL016C',\n",
" 'YFR033C',\n",
" 'YMR256C',\n",
" 'Q0275']"
]
},
"execution_count": 16,
Expand Down

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