Our paper on IJMS has reached more than 2000 views

Our paper, “A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces”, by Rita Melo et al., featuring a novel way to spot Hot-Spots using Machine Learning just reached 2000 views.

Understanding protein-protein interactions is a key challenge in biochemistry. In this work, published in the International Journal of Molecular Sciences, we described a more accurate methodology to predict Hot-Spots in protein-protein interfaces from their native complex structure compared to previous published Machine Learning techniques.

Our model is trained on a large number of complexes and on a significantly larger number of different structural- and evolutionary sequence-based features.

See the paper.


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