diff --git a/tools/dimet/dimet_differential_analysis.xml b/tools/dimet/dimet_differential_analysis.xml
index cd6e011860d..634536cfb7f 100644
--- a/tools/dimet/dimet_differential_analysis.xml
+++ b/tools/dimet/dimet_differential_analysis.xml
@@ -266,11 +266,11 @@ compartments names are, the longer the output files' names! Please pick short an
 
 You can precise how you want your analysis to be executed, with the parameters:
 
-- **conditions**: the conditions present in your data, to perform the pairwise comparison.
+- **datatypes** : the measures type(s) that you want to run (see above in Input data files section)
 
-- **comparisons** : the pairs of [condition, timepoint] groups to compare
+- **conditions**: the two 'Conditions' boxes must be filled in a coherent order, keeping in mind that the last specified condition is the reference or control.
 
-- **datatypes** : the measures type(s) that you want to run (see above in Input data files section)
+- **timepoint** : the time point at which the two conditions will be compared.
 
 - **statistical_test** : choose, by type of measure, the specific statistical test to be applied.
 
diff --git a/tools/dimet/macros.xml b/tools/dimet/macros.xml
index d9e7aec91e5..c6c4c09546e 100644
--- a/tools/dimet/macros.xml
+++ b/tools/dimet/macros.xml
@@ -1,6 +1,6 @@
 <macros>
     <token name="@TOOL_VERSION@">0.2.4</token>
-    <token name="@VERSION_SUFFIX@">3</token>
+    <token name="@VERSION_SUFFIX@">4</token>
     <xml name="requirements">
         <requirements>
             <requirement type="package" version="@TOOL_VERSION@">dimet</requirement>
@@ -49,6 +49,23 @@
     </xml>
     <xml name="citations">
         <citations>
+            <citation type="bibtex">
+                @article{10.1093/bioinformatics/btae282,
+                author = {Galvis, Johanna and Guyon, Joris and Dartigues, Benjamin and Hecht, Helge and Grüning, Björn and Specque, Florian and Soueidan, Hayssam and Karkar, Slim and Daubon, Thomas and Nikolski, Macha},
+                title = "{DIMet: an open-source tool for differential analysis of targeted isotope-labeled metabolomics data}",
+                journal = {Bioinformatics},
+                volume = {40},
+                number = {5},
+                pages = {btae282},
+                year = {2024},
+                month = {04},
+                abstract = "{Many diseases, such as cancer, are characterized by an alteration of cellular metabolism allowing cells to adapt to changes in the microenvironment. Stable isotope-resolved metabolomics (SIRM) and downstream data analyses are widely used techniques for unraveling cells’ metabolic activity to understand the altered functioning of metabolic pathways in the diseased state. While a number of bioinformatic solutions exist for the differential analysis of SIRM data, there is currently no available resource providing a comprehensive toolbox.In this work, we present DIMet, a one-stop comprehensive tool for differential analysis of targeted tracer data. DIMet accepts metabolite total abundances, isotopologue contributions, and isotopic mean enrichment, and supports differential comparison (pairwise and multi-group), time-series analyses, and labeling profile comparison. Moreover, it integrates transcriptomics and targeted metabolomics data through network-based metabolograms. We illustrate the use of DIMet in real SIRM datasets obtained from Glioblastoma P3 cell-line samples. DIMet is open-source, and is readily available for routine downstream analysis of isotope-labeled targeted metabolomics data, as it can be used both in the command line interface or as a complete toolkit in the public Galaxy Europe and Workfow4Metabolomics web platforms.DIMet is freely available at https://github.com/cbib/DIMet, and through https://usegalaxy.eu and https://workflow4metabolomics.usegalaxy.fr. All the datasets are available at Zenodo https://zenodo.org/records/10925786.}",
+                issn = {1367-4811},
+                doi = {10.1093/bioinformatics/btae282},
+                url = {https://doi.org/10.1093/bioinformatics/btae282},
+                eprint = {https://academic.oup.com/bioinformatics/article-pdf/40/5/btae282/57802928/btae282.pdf},
+            }
+            </citation>
             <citation type="bibtex">
                 @software{Galvis_Rodriguez_DIMet,
                     author = {Galvis Rodriguez, Johanna  and Guyon, Joris and Dartigues, Benjamin and Specque, Florian and Daubon, Thomas and Karkar, Slim and Nikolski, Macha},
@@ -56,7 +73,6 @@
                     title = {{DIMet}},
                     url = {https://github.com/cbib/DIMet}
                     }
-
             </citation>
         </citations>