Development of a deep neural network model for simultaneous analysis of extracellular analyte gradients for a population of cells [0.03%]
开发用于同时分析细胞群体的胞外分析物浓度梯度的深度神经网络模型
Ivon Acosta-Ramirez,Ferhat Sadak,Sruti Das Choudhury et al.
Ivon Acosta-Ramirez et al.
Detecting the spatial release of extracellular nitric oxide (NO) is essential for understanding the dynamics in cell communication for physiological and pathological processes. This study presents an innovative methodology that integrates f...
MegaEye: Applying multiple machine learning approaches to identify oral compounds with ocular bioactivity [0.03%]
MegaEye：应用多种机器学习方法识别具有眼部生物活性的口服给药化合物
Fabio Urbina,Scott H Greenwald,Patricia A Vignaux et al.
Fabio Urbina et al.
The eye is a complex organ with the critical role of mediating the optical and initial signal processing steps of vision. As such, the eye has multiple physiological and dynamic barriers to protect ocular tissues and compartments. Oral admi...
piCRISPR: Physically informed deep learning models for CRISPR/Cas9 off-target cleavage prediction [0.03%]
物理信息深度学习模型预测CRISPR/Cas9脱靶切割
Florian Störtz,Jeffrey K Mak,Peter Minary
Florian Störtz
CRISPR/Cas programmable nuclease systems have become ubiquitous in the field of gene editing. With progressing development, applications in in vivo therapeutic gene editing are increasingly within reach, yet limited by possible adverse side...
Elucidating dynamic cell lineages and gene networks in time-course single cell differentiation [0.03%]
阐明单细胞分化过程中的细胞谱系和基因网络动态变化规律
Mengrui Zhang,Yongkai Chen,Dingyi Yu et al.
Mengrui Zhang et al.
Single cell RNA sequencing (scRNA-seq) technologies provide researchers with an unprecedented opportunity to exploit cell heterogeneity. For example, the sequenced cells belong to various cell lineages, which may have different cell fates i...
Fabio Urbina,Sean Ekins
Fabio Urbina
Anyone involved in designing or finding molecules in the life sciences over the past few years has witnessed a dramatic change in how we now work due to the COVID-19 pandemic. Computational technologies like artificial intelligence (AI) see...
Novel computational models offer alternatives to animal testing for assessing eye irritation and corrosion potential of chemicals [0.03%]
新型计算模型为化学品眼睛刺激和腐蚀潜力评估提供动物试验替代方法
Arthur C Silva,Joyce V V B Borba,Vinicius M Alves et al.
Arthur C Silva et al.
Eye irritation and corrosion are fundamental considerations in developing chemicals to be used in or near the eye, from cleaning products to ophthalmic solutions. Unfortunately, animal testing is currently the standard method to identify co...
An in silico pipeline for the discovery of multitarget ligands: A case study for epi-polypharmacology based on DNMT1/HDAC2 inhibition [0.03%]
一种针对多靶标配体发现的计算机模拟研究流程：基于DNMT1/HDAC2抑制作用表观多药理学的研究案例分析
Fernando D Prieto-Martínez,Eli Fernández-de Gortari,José L Medina-Franco et al.
Fernando D Prieto-Martínez et al.
The search for novel therapeutic compounds remains an overwhelming task owing to the time-consuming and expensive nature of the drug development process and low success rates. Traditional methodologies that rely on the one drug-one target p...
Corrigendum to "Machine Learning Based Prediction of COVID-19 Mortality Suggests Repositioning of Anticancer Drug for Treating Severe Cases"[Artificial Intelligence in Life Sciences] 1(2021), 100020 [0.03%]
关于“基于机器学习的COVID-19死亡率预测建议将抗肿瘤药物重新定位以治疗重症患者”的勘误说明[生命科学人工智能]1(2021)100020
Thomas Linden,Frank Hanses,Daniel Domingo-Fernández et al.
Thomas Linden et al.
[This corrects the article DOI: 10.1016/j.ailsci.2021.100020.]. © 2022 The Authors.
Machine Learning Based Prediction of COVID-19 Mortality Suggests Repositioning of Anticancer Drug for Treating Severe Cases [0.03%]
基于机器学习的COVID-19死亡率预测建议将抗癌药物重新定位以治疗重症患者
Thomas Linden,Frank Hanses,Daniel Domingo-Fernández et al.
Thomas Linden et al.
Despite available vaccinations COVID-19 case numbers around the world are still growing, and effective medications against severe cases are lacking. In this work, we developed a machine learning model which predicts mortality for COVID-19 p...