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    <title>PyPI recent updates for deepx-dock</title>
    <link>https://pypi.org/project/deepx-dock/</link>
    <description>Recent updates to the Python Package Index for deepx-dock</description>
    <language>en</language>    <item>
      <title>0.9.11</title>
      <link>https://pypi.org/project/deepx-dock/0.9.11/</link>
      <description>DeepH-dock seamlessly integrates deep learning with first-principles calculations. It serves as a modular and extensible bridge, functioning both as the dedicated interface for the DeepH-pack suite and as a standalone tool for coupling deep learning models with computational materials science workflows.</description>
<author>deeph-pack@outlook.com</author>      <pubDate>Sat, 28 Feb 2026 09:50:19 GMT</pubDate>
    </item>    <item>
      <title>0.9.10</title>
      <link>https://pypi.org/project/deepx-dock/0.9.10/</link>
      <description>DeepH-dock seamlessly integrates deep learning with first-principles calculations. It serves as a modular and extensible bridge, functioning both as the dedicated interface for the DeepH-pack suite and as a standalone tool for coupling deep learning models with computational materials science workflows.</description>
<author>deeph-pack@outlook.com</author>      <pubDate>Fri, 27 Feb 2026 06:43:53 GMT</pubDate>
    </item>    <item>
      <title>0.9.9</title>
      <link>https://pypi.org/project/deepx-dock/0.9.9/</link>
      <description>DeepH-dock seamlessly integrates deep learning with first-principles calculations. It serves as a modular and extensible bridge, functioning both as the dedicated interface for the DeepH-pack suite and as a standalone tool for coupling deep learning models with computational materials science workflows.</description>
<author>deeph-pack@outlook.com</author>      <pubDate>Fri, 30 Jan 2026 11:02:07 GMT</pubDate>
    </item>    <item>
      <title>0.9.8</title>
      <link>https://pypi.org/project/deepx-dock/0.9.8/</link>
      <description>DeepH-dock seamlessly integrates deep learning with first-principles calculations. It serves as a modular and extensible bridge, functioning both as the dedicated interface for the DeepH-pack suite and as a standalone tool for coupling deep learning models with computational materials science workflows.</description>
<author>deeph-pack@outlook.com</author>      <pubDate>Fri, 30 Jan 2026 03:10:25 GMT</pubDate>
    </item>    <item>
      <title>0.9.7</title>
      <link>https://pypi.org/project/deepx-dock/0.9.7/</link>
      <description>DeepH-dock seamlessly integrates deep learning with first-principles calculations. It serves as a modular and extensible bridge, functioning both as the dedicated interface for the DeepH-pack suite and as a standalone tool for coupling deep learning models with computational materials science workflows.</description>
<author>deeph-pack@outlook.com</author>      <pubDate>Thu, 29 Jan 2026 11:27:39 GMT</pubDate>
    </item>    <item>
      <title>0.9.6.post2</title>
      <link>https://pypi.org/project/deepx-dock/0.9.6.post2/</link>
      <description>DeepH-dock seamlessly integrates deep learning with first-principles calculations. It serves as a modular and extensible bridge, functioning both as the dedicated interface for the DeepH-pack suite and as a standalone tool for coupling deep learning models with computational materials science workflows.</description>
<author>deeph-pack@outlook.com</author>      <pubDate>Mon, 19 Jan 2026 06:16:46 GMT</pubDate>
    </item>    <item>
      <title>0.9.6.post1</title>
      <link>https://pypi.org/project/deepx-dock/0.9.6.post1/</link>
      <description>DeepH-pack dock that designed for DeepH-pack data preparation.</description>
<author>deeph-pack@outlook.com</author>      <pubDate>Fri, 16 Jan 2026 10:04:33 GMT</pubDate>
    </item>    <item>
      <title>0.9.6</title>
      <link>https://pypi.org/project/deepx-dock/0.9.6/</link>
      <description>DeepH-pack dock that designed for DeepH-pack data preparation.</description>
<author>duanw@tsinghua.com, yongxu@tsinghua.com, deeph-pack@outlook.com</author>      <pubDate>Fri, 16 Jan 2026 07:39:46 GMT</pubDate>
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