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highlights:2025:itercr [2025/10/23 10:39] – Didier Barradas Bautistahighlights:2025:itercr [2025/10/23 10:48] (current) – Didier Barradas Bautista
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-<WRAP center round important box 100% large> {{:favicon.ico?nolink&0x30}} <fs:26px>** KVL Staff on Project**</fs>+<WRAP center round box 100% large> {{:favicon.ico?nolink&0x30}} <fs:26px>** KVL Staff on Project**</fs>
  
 {{:icon:twbs:link:w-25:h-auto:person.svg?nolink&}} Didier Barradas Bautista \\ {{:icon:twbs:link:w-25:h-auto:person.svg?nolink&}} Didier Barradas Bautista \\
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 ===== Research Breakthrough ===== ===== Research Breakthrough =====
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 Protein–protein docking generates thousands of possible interaction models—but only a few are correct. In our latest collaborative work, we introduce Iter-CONSRANK, an iterative scoring algorithm that filters out incorrect models and enriches the ensemble with correct ones. Protein–protein docking generates thousands of possible interaction models—but only a few are correct. In our latest collaborative work, we introduce Iter-CONSRANK, an iterative scoring algorithm that filters out incorrect models and enriches the ensemble with correct ones.
   * 📊 Tested on two challenging datasets, Iter-CONSRANK increased the fraction of correct models by up to 8× for medium-difficulty targets and outperformed over 150 scoring functions in ranking accuracy.   * 📊 Tested on two challenging datasets, Iter-CONSRANK increased the fraction of correct models by up to 8× for medium-difficulty targets and outperformed over 150 scoring functions in ranking accuracy.
   * 🎯 The method is available for use in pre-processing docking ensembles or as an independent scoring tool.   * 🎯 The method is available for use in pre-processing docking ensembles or as an independent scoring tool.
   * 🔬 This work was led in collaboration with Luigi Cavallo and our partners at the University of Naples “Parthenope”   * 🔬 This work was led in collaboration with Luigi Cavallo and our partners at the University of Naples “Parthenope”
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 The graphical abstract below illustrates the iterative filtering strategy used to enrich correct protein–protein docking models. The paper entitled "Increasing the Fraction of Correct Solutions in Ensembles of Protein-Protein Docking Models by an Iterative Consensus Algorithm" is available for download and review. [[https://onlinelibrary.wiley.com/doi/pdf/10.1002/pro.70314|here]].  The graphical abstract below illustrates the iterative filtering strategy used to enrich correct protein–protein docking models. The paper entitled "Increasing the Fraction of Correct Solutions in Ensembles of Protein-Protein Docking Models by an Iterative Consensus Algorithm" is available for download and review. [[https://onlinelibrary.wiley.com/doi/pdf/10.1002/pro.70314|here]]. 
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 <fs 18>**🎯 KVL's Contribution**</fs> <fs 18>**🎯 KVL's Contribution**</fs>
 KVL's visualization scientist **Didier Barradas-Bautista** contributed significantly to the development and validation of the Iter-CONSRANK algorithm through: KVL's visualization scientist **Didier Barradas-Bautista** contributed significantly to the development and validation of the Iter-CONSRANK algorithm through:
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   * Active participation in CAPRI scoring rounds, validating the method in blind tests   * Active participation in CAPRI scoring rounds, validating the method in blind tests
  
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