Development of terpenoid repellents against Aedes albopictus: a combined study of biological activity evaluation and computational modelling [0.03%]
对白纹伊蚊的萜类驱避剂的研究：生物活性评价和计算机模拟结合分析
J Wang,X Feng,W Yuan et al.
J Wang et al.
To explore novel terpenoid repellents, 22 candidate terpenoid derivatives were synthesized and tested for their electroantennogram (EAG) responses and repellent activities against Aedes albopictus. The results from the EAG experiments revea...
Correction [0.03%]
纠正
Development of a standardized methodology for transfer learning with QSAR models: a purely data-driven approach for source task selection [0.03%]
QSAR模型迁移学习的标准化方法开发：源任务选择的纯粹数据驱动方法
L Melo,L Scotti,M T Scotti
L Melo
Transfer learning is a machine learning technique that works well with chemical endpoints, with several papers confirming its efficiency. Although effective, because the choice of source/assistant tasks is non-trivial, the application of th...
Steroidal hydrazones as antimicrobial agents: biological evaluation and molecular docking studies [0.03%]
甾体肼腙作为抗菌剂的生物活性评价和分子对接研究
M Merlani,N Nadaraia,N Barbakadze et al.
M Merlani et al.
Most of pharmaceutical agents display several or even many biological activities. It is obvious that testing even one compound for thousands of biological activities is a practically not reasonable task. Therefore, computer-aided prediction...
Ligand-based virtual screening and biological evaluation of inhibitors of Mycobacterium tuberculosis H37Rv [0.03%]
结核分枝杆菌H37Rv抑制剂的配体虚拟筛选和生物学评估
P V Pogodin,E G Salina,V V Semenov et al.
P V Pogodin et al.
Novel antimycobacterial compounds are needed to expand the existing toolbox of therapeutic agents, which sometimes fail to be effective. In our study we extracted, filtered, and aggregated the diverse data on antimycobacterial activity of c...
Descriptor generation from Morgan fingerprint using persistent homology [0.03%]
使用持续同调从Morgan指纹生成描述符
T Ehiro
T Ehiro
In cheminformatics, molecular fingerprints (FPs) are used in various tasks such as regression and classification. However, predictive models often underutilize Morgan FP for regression and related tasks in machine learning. This study intro...
q-RASTR modelling for prediction of diverse toxic chemicals towards T. pyriformis [0.03%]
q-RASTR模型预测多种毒性化学物质对T.pyriformis的影响
V Ghosh,A Bhattacharjee,A Kumar et al.
V Ghosh et al.
A series of diverse organic compounds impose serious detrimental effects on the health of living organisms and the environment. Determination of the structural aspects of compounds that impart toxicity and evaluation of the same is crucial ...
BC CLC-Pred: a freely available web-application for quantitative and qualitative predictions of substance cytotoxicity in relation to human breast cancer cell lines [0.03%]
BC CLC-Pred：一个用于预测物质相对于人类乳腺癌细胞系毒性作用的定量和定性预测的免费网络应用程序
A A Lagunin,A S Sezganova,E S Muraviova et al.
A A Lagunin et al.
In silico prediction of cell line cytotoxicity considerably decreases time and financial costs during drug development of new antineoplastic agents. (Q)SAR models for the prediction of drug-like compound cytotoxicity in relation to nine bre...
Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project [0.03%]
关于第二Ames/QSAR国际挑战项目的致突变性预测QSAR模型的评估
A Furuhama,A Kitazawa,J Yao et al.
A Furuhama et al.
Quantitative structure-activity relationship (QSAR) models are powerful in silico tools for predicting the mutagenicity of unstable compounds, impurities and metabolites that are difficult to examine using the Ames test. Ideally, Ames/QSAR ...
Prioritizing pharmaceutically active compounds (PhACs) based on occurrence-persistency-mobility-toxicity (OPMT) criteria: an application to the Brazilian scenario [0.03%]
基于发生-持续-移动-毒性（OPMT）标准优先处理药物活性化合物（PhACs）：巴西情况下的应用
V Roveri,L Lopes Guimarães,A T Correia
V Roveri
A study of Quantitative Structure Activity Relationship (QSAR) was performed to assess the possible adverse effects of 25 pharmaceuticals commonly found in the Brazilian water compartments and to establish a ranking of environmental concern...