Vecura
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© 2026 NYB AI. 全ての権利を留保しています。

すべてのシステムは正常に稼働中です。
Vecura
料金解決方法
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Vecuraチームからの視点

AIを活用したライフサイエンス探索に関する研究分析、業界の視点、深掘り解説

注目

NYB.AI Connects Scientific Knowledge to Discovery: Exploring NVIDIA Nemotron in Vecura

A closer look at a natural-product literature pilot in NYB.AI evaluated how NVIDIA Nemotron 3.5 Super VL could help verify compound records against their source publications.

Oct 15, 2026注目記事を読む

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Vecura Biotech Insiders Spotlight #13: Five Generations, and the Potency Never Moved

For Vecura Biotech Insiders Spotlight #13, Chang Yong Zu shares all five generations, the controls as well as the leads, and what the contact data showed that the docking scores did not.

Oct 23, 2026

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From generated molecule to synthesis route, in one workflow

Vecura now runs Selenium, the retrosynthesis model from b12 Labs, as the final step of its discovery workflow, so a molecule you generate comes back with routes for making it. Here is what that looked like on a real run against NEK2.

Dr. Thanh Nguyen·Sep 9, 2026

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From Prediction to Decision: Choosing Graph-Based AI Models for Drug-Target Interaction Research

How an output-driven perspective can help researchers select graph-based AI models for drug-target interaction research, with a closer look at DTIGN and LigoSPACE.

Dr. Thanh Nguyen, Duy Anh Nguyen +1·Jul 22, 2026

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Vecura Biotech Insiders Spotlight #12: Building and Optimizing a Virtual Screening Pipeline for HIV-1 Protease: Lessons from Real-World Benchmarking with Darunavir

For Vecura Biotech Insiders Spotlight #12, Viet Nguyen Duc shares a structure-based screening campaign against HIV-1 protease built so that every threshold in it had to answer to a drug already known to work.

Oct 16, 2026

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Making Water Visible: How Generative AI Can Support Protein Structure Research

SuperWater, a generative AI framework developed to predict water molecule positions around biomolecular complexes, offers a new approach to this longstanding computational challenge.

Dr. Yunchao (Lance) Liu·Jul 14, 2026

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Vecura Biotech Insiders Spotlight #11: Grafting the Enzyme I active site onto a new scaffold

For Vecura Biotech Insiders Spotlight #11, Ethan Lee shares a nine step campaign logged exactly as it ran, including the gate that failed every single design and the comparison that only existed because three candidates went forward instead of one.

Oct 9, 2026

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Vecura Biotech Insiders Spotlight #10: The fragments never bridged. They circled back instead.

For Biotech Insiders #10, Paolo Reyes shares a campaign that draws an unusually sharp line between what a generative docking model can be trusted with and what it can't, not because the model got confused, but because the two tasks are geometrically different problems wearing the same name.

Sep 24, 2026

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Vecura Biotech Insiders #09: It cleared every filter. Then the most confident synthesis step turned out to be impossible.

For Vecura Biotech Insiders Spotlight #09, Kerem brought us a campaign that passed four straight stages of computational scrutiny and stalled on the fifth, the one that decides whether anyone could ever hold the molecule in their hand.

Sep 16, 2026

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Harnessing Vecura’s AI Platform to Design FGFR4-Targeting Peptides for Hepatocellular Carcinoma Therapy

Hepatocellular carcinoma (HCC) is the predominant primary liver cancer and a major cause of cancer-related mortality worldwide. Despite advances in current therapies, advanced HCC remains difficult to treat, highlighting the need for new therapeutic targets.

TPTran Phuong Hoa·Sep 10, 2026

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Vecura Biotech Insiders #08: A binder with a near-perfect interface score, on entirely the wrong face

For Biotech Insiders #08, Goh brought us a campaign that did not work, and a reasonable person reading the metrics at stage three would have called it finished. That is exactly why we asked to publish it

Sep 10, 2026

インサイト

Vecura Biotech Insiders #07: Beta-Lactam Design Against Amoxicillin: The Highest-Scoring Edit Was the One That Breaks the Drug

In this seventh edition of Vecura Biotech Insiders, we highlight a workflow shared with the Vecura team by Azlan Firdaus Iskandar: a constrained generative design campaign against amoxicillin's beta-lactam core, and what it took to stop the highest-scoring edit from being the one that breaks the drug.

Aug 28, 2026
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Vecura

商品

  • 解決方法
  • 見積
  • 紹介プログラム

会社

  • お問い合わせ
  • 学術研究プログラム

リソース

  • 更新
  • ニュース
  • 詳細専門分析
  • 適用事例
  • AI4Life Bootcamp
  • コミュニティ

法定

  • プライバシーポリシー
  • 利用規約
  • 引用ガイドライン
  • お問い合わせ

© 2026 NYB AI. 全ての権利を留保しています。

すべてのシステムは正常に稼働中です。