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highlights:2023:ld_graphsumm [2023/05/04 11:33] – removed - external edit (Unknown date) 127.0.0.1highlights:2023:ld_graphsumm [2023/05/07 13:41] (current) – Sohaib Ghani
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 +====== The LightDock Server: Artificial Intelligence-powered modeling of macromolecular interactions   ======
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 +<WRAP center round box 100%> {{:favicon.ico?nolink&0x30}} <fs:26px>** KVL Staff on Project**</fs>
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 +{{:icon:twbs:link:w-25:h-auto:person.svg?nolink&}} Didier Barradas Bautista \\
 +{{:icon:twbs:link:w-25:h-auto:envelope-at.svg?nolink&}}  didier.barradasbautista@kaust.edu.sa \\
 +{{:icon:twbs:link:w-25:h-auto:building.svg?nolink&}} Building 1, Level 0, Office 0125 \\
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 +/*
 +<WRAP center round box 100%> {{:wiki:kaust-seeds.png?nolink&0x30}} <fs:26px>** KAUST PI on Project**</fs>
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 +{{:icon:twbs:link:w-25:h-auto:person.svg?nolink&}} Dr. Shehzad Afzal  \\
 +{{:icon:twbs:link:w-25:h-auto:envelope-at.svg?nolink&}}  shehzad.afzal@kaust.edu.sa \\
 +{{:icon:twbs:link:w-25:h-auto:building.svg?nolink&}} KAUST Climate Change Center \\
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 +===== Overview =====
 +The KVL is happy to announce the project's conclusion, resulting in a paper about Artificial intelligence techniques applied to computational structural biology.
 +
 +===== Work Summary=====
 +Computational docking is an instrumental method of the structural biology toolbox. Specifically, integrative modeling software, such as LightDock, arises as complementary and synergetic methods to experimental structural biology techniques. Ubiquity and accessibility are fundamental features to ease of use and improve user experience. With this goal in mind, we have developed the LightDock Server, a web server for the integrative modeling of macromolecular interactions, along with several dedicated and powerful usage modes. The server builds upon the LightDock macromolecular docking framework, which has proved useful for modeling medium-to-high flexible complexes, antibody-antigen interactions, or membrane-associated protein assemblies. We believe that this free-to-use resource will be a valuable addition to the structural biology community and can be accessed online at: [[ https://server.lightdock.org/ | lightdock.org ]]
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 +The paper is available for download from: [[https://doi.org/10.1093/nar/gkad327 | here]]
 +
 +
 +===== Impact =====
 +This work offers a public tool for research on protein-protein interactions that Alphafold can not predict. This server uses state-of-the-art AI and ML in the back-end 
 +
 +/* This machine learning paper shows state-of-the-art different binary classifiers and semi-weak deep learning techniques related to data augmentation datasets. It provides a complete description to use in a new way, framework Snorkel and discusses the differences in performance of deep learning and classical machine learning algorithms. */
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 +/* {{ youtube>mkeZS74PfhE?half |KAUST Visualization Core Laboratory Video}} */
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 +----
 +{{tag>DS ML AI}}