日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Explainable artificial intelligence for molecular design in pharmaceutical research

可解释人工智能在药物研发中的分子设计应用

Lamens, Alec; Bajorath, Jürgen

Transformer Learning in Sequence-Based Drug Design Depends on Compound Memorization and Similarity of Sequence-Compound Pairs

基于序列的药物设计中的Transformer学习依赖于化合物记忆和序列-化合物对的相似性

Bajorath, Jürgen

Protocol update to: Protocol to generate dual-target compounds using a transformer-based chemical language model

协议更新:使用基于Transformer的化学语言模型生成双靶点化合物的协议

Srinivasan, Sanjana; Bajorath, Jürgen

Redirecting the Peptide Cleavage Causes Protease Inactivation

改变肽链切割方向会导致蛋白酶失活

Breuer, Christian; Küppers, Jim; Schulz-Fincke, Anna-Christina; Heilos, Anna; Lemke, Carina; Spiwoková, Petra; Schmitz, Janina; Cremer, Laura; Frigolé-Vivas, Marta; Lülsdorff, Michael; Mertens, Matthias D; Wichterle, Filip; Apeltauer, Miloš; Horn, Martin; Gilberg, Erik; Furtmann, Norbert; Bajorath, Jürgen; Bartz, Ulrike; Engels, Bernd; Mareš, Michael; Gütschow, Michael

Unraveling learning characteristics of transformer models for molecular design

揭示Transformer模型在分子设计中的学习特性

Roth, Jannik P; Bajorath, Jürgen

Context-dependent similarity analysis of analogue series for structure-activity relationship transfer based on a concept from natural language processing

基于自然语言处理概念的类比序列结构-活性关系转移的上下文相关相似性分析

Yoshimori, Atsushi; Bajorath, Jürgen

Context-dependent similarity searching for small molecular fragments

基于上下文的相似性搜索小分子片段

Yoshimori, Atsushi; Bajorath, Jürgen

Contrastive explanations for machine learning predictions in chemistry

化学领域机器学习预测的对比解释

Lamens, Alec; Bajorath, Jürgen

A meta-learning framework to mitigate negative transfer in transfer learning applicable to drug design

一种用于缓解迁移学习中负迁移的元学习框架,适用于药物设计

Mera, Antonia; Vogt, Martin; Bajorath, Jürgen

Identifying and evaluating understudied protein kinases using biological and chemical criteria

利用生物学和化学标准鉴定和评价研究不足的蛋白激酶

Koch, Selina; Bajorath, Jürgen