Update README.md

README.md

@@ -5,7 +5,7 @@ datasets:
 pipeline_tag: tabular-classification
 repo: https://github.com/KDrewLab/DirectContacts2_analysis.git
 ---
-# # DirectContacts2: A network of direct physical protein interactions derived from high throughput mass spectrometry experiments
+# DirectContacts2: A network of direct physical protein interactions derived from high throughput mass spectrometry experiments
 Proteins carry out cellular functions by self-assembling into functional complexes, a process that depends on direct physical interactions 
 between components. While tools like AlphaFold and RoseTTAFold have advanced structure prediction, they remain limited in scaling to the full 
 human proteome. DirectContacts2 addresses this challenge by integrating diverse large-scale protrin interaction datasets, including AP/MS (BioPlex1–3, Boldt et al., Hein et al.), 
@@ -48,12 +48,12 @@ is used to is used train, test, and make predictions with the model.
 
 This can be downloaded using the following:
 
-      $ pip install autogluon==0.4.0
+      $ pip install autogluon==0.8.2
 
 Then it can be imported as:
 
     >>> from autogluon.tabular import TabularPredictor
-Note that to perform operations with our model the **0.4.0 version** must be used
+Note that to perform operations with our model the **0.8.2 version** must be used
 
   To use the model and make predictions, we show two full code examples using the [full feature matrix]() 
   and the [test feature matrix]() in jupyter notebooks.