Merge remote-tracking branch 'origin/dev' into dev

README.md

@@ -9,32 +9,32 @@
 ## What is PhysioFit?
 **PhysioFit is a scientific tool designed to quantify cell growth parameters and uptake & production fluxes**
 
-Fluxes are estimated using various mathematical models by fitting time-course measurements of the concentration of
-cells and extracellular substrates and products. PhysioFit v3 includes by default the most common growth models, and
-additional models can be implemented by users.
+Fluxes are estimated using mathematical models by fitting time-course measurements of the concentration of
+cells and extracellular substrates and products. PhysioFit is shipped with some common growth models, and
+additional tailor-made models can be implemented by users.
 
-It is one of the routine tools that we use at the [MetaSys team](http://www.lisbp.fr/en/research/molecular-physiology-and-metabolism/metasys.html) 
-and [MetaToul platform](http://www.metatoul.fr) in functional studies of metabolic systems.
+It is one of the routine tools that we use at the [MetaSys team](https://www.toulouse-biotechnology-institute.fr/en/poles/equipe-metasys/) 
+and [MetaToul platform](https://www.metabohub.fr/home.html) in functional studies of metabolic systems.
 
 The code is open-source, and available under a GPLv3 license. Additional information can be found in the following 
-[publication](https://doi.org/10.1128/aem.00768-19).
+[publication](https://doi.org/10.1101/2023.10.12.561695).
 
 Detailed documentation can be found online at Read the Docs 
 ([https://physiofit.readthedocs.io/](https://physiofit.readthedocs.io/)).
 
 ## Key features
+
    * **calculation of growth rate and extracellular (uptake and production) fluxes**,
-   * default models for quantifying parameters in steady-state conditions (with and without lag & metabolite degradation
-     over time),
-   * **user-defined growth models**,
-   * Monte-Carlo sensitivity analysis to **estimate the precision of the calculated fluxes**,
+   * **a set of steady-state and dynamic models** are shipped with PhysioFit,
+   * **tailor-made models** can be constructed by users,
+   * Monte-Carlo sensitivity analysis to **estimate the precision on the calculated fluxes**,
    * **evaluation of the goodness of fit and visual inspection of the fitted curves**,
-   * shipped as a **library** with both a **graphical** and **command line** interface,
-   * open-source, free and easy to install everywhere where Python 3 and pip run,
+   * shipped as a **library** with both a **graphical** and a **command line** interface,
+   * **open-source, free and easy to install** everywhere where Python 3 and pip run,
    * **biologist-friendly**.
 
 ## Quick-start
-PhysioFit requires Python 3.8 or higher and run on all platforms.
+PhysioFit requires Python 3.9 or higher and run on all platforms.
 Please check [the documentation](https://physiofit.readthedocs.io/en/latest/quickstart.html) for complete
 installation and usage instructions.
 
@@ -44,12 +44,6 @@ Use `pip` to **install PhysioFit from PyPi**:
 $ pip install physiofit
 ```
 
-Use `conda` to install from conda:
-
-```bash
-$ conda install physiofit -c bioconda
-```
-
 Then, start the graphical interface with:
 
 ```bash
@@ -87,9 +81,9 @@ The PDF documentation can be built locally by replacing `html` by `latexpdf`
 in the command above. You will need a recent latex installation.
 
 ## How to cite
-PhysioFit: quantifying cell growth parameters and uptake and production fluxes.
+PhysioFit: a software to quantify cell growth parameters and extracellular fluxes.
 Le Grégam L., Guitton Y., Bellvert F., Jourdan F., Portais J.C., Millard P.
-In preparation for publication
+bioRxiv preprint, [doi: 10.1101/2023.10.12.561695](https://doi.org/10.1101/2023.10.12.561695)
 
 ## Authors
 Loïc Le Grégam, Pierre Millard

docs/cite.rst

@@ -3,8 +3,8 @@ How to cite
 
 Thank you for using PhysioFit and citing us in your work! It means a lot to us and encourage us to continue its development.
 
-  PhysioFit: quantifying cell growth parameters and uptake and production fluxes.
+  PhysioFit: a software to quantify cell growth parameters and extracellular fluxes.
 
   Le Grégam L., Guitton Y., Bellvert F., Jourdan F., Portais J.C., Millard P.
 
-  **doi**: https://doi.org/10.1101/2023.10.12.561695
+  bioRxiv preprint, doi: https://doi.org/10.1101/2023.10.12.561695

docs/faq.rst

@@ -76,7 +76,7 @@ The quality of the fit can be evaluated based on:
 What is a χ² test?
 ------------------------------------------------------------------
 
-A χ² test describes how well a model fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model used in PhysioFit (see the :doc:`models` section). It is calculated as the sum of differences between measured and simulated values, each squared and divided by the simulated value.
+A χ² test describes how well a model fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model used in PhysioFit (see the :doc:`method` section). It is calculated as the sum of differences between measured and simulated values, each squared and divided by the simulated value.
 A good fit corresponds to small differences between measured and simulated values, thereby the χ² value is low. In contrast, a bad fit corresponds to large differences between simulations and measurements, and the χ² value is high. 
 
 The resulting χ² value can then be compared with a χ² distribution to determine the goodness of fit. The p-value of one-tail χ² test is calculated by PhysioFit from the best fit and is given in the log file (have a look to the :doc:`usage` section). A p-value close to 0 means poor fitting, and a p-value close to 1 means good fitting (keeping in mind that a p-value very close to 1 can be an evidence that standard deviations might be overestimated). A 

docs/method.rst

@@ -52,8 +52,8 @@ more details on the interpretation of the khi2 test results.
 Sensitivity analysis
 *********************
 
-To determine the precision on the fit and on the estimated parameters (including fluxes), PhysioFit performs a Monte Carlo analysis. Briefly, several 
-noisy datasets are generated from the simulated dynamics of the best fit (i.e defined in parameter :samp:`number of iterations` of the GUI) and calculate fluxes and other growth 
+To determine the precision on the fit and on the estimated parameters (including fluxes), PhysioFit performs a Monte Carlo analysis. Briefly, PhysioFit generates several 
+datasets by adding noise to the dynamics simulated from the best fit, and calculated fluxes and other growth 
 parameters for each of these synthetic datasets. This enables PhysioFit to compute statistics (mean, median, standard deviation and 95% confidence interval) for 
-each parameter. We recommend always running a sensitivity analysis when using PhysioFit.
+each parameter (including fluxes). We recommend always running a sensitivity analysis when using PhysioFit.
 

docs/models.rst

@@ -1,6 +1,12 @@
 Models
 =========
 
+Some common flux calculation models are provided with PhysioFit, and users can also build their own models.
+
+.. note:: We would be happy to broaden the types of models shipped with PhysioFit. If you have developed a new model, it might be 
+          usefull and valuable to the fluxomics community! Please, keep in touch with us to discuss and see if we can include your 
+          model in the built-in models shipped with PhysioFit! :)
+
 
 Models shipped with PhysioFit
 ******************************

physiofit/ui/gui.py

@@ -34,6 +34,7 @@ def start_app(self):
 
         st.set_page_config(page_title=f"PhysioFit (v{physiofit.__version__})")
         st.title(f"Welcome to PhysioFit (v{physiofit.__version__})")
+        st.write("Documentation available at [https://physiofit.readthedocs.io](https://physiofit.readthedocs.io).")
         self.update_info = st.empty()
         self.check_uptodate()
         self.select_menu = st.selectbox(