Changhao Xu,Samuel A Solomon,Wei Gao
Changhao Xu
Skin-interfaced electronics is gradually changing medical practices by enabling continuous and noninvasive tracking of physiological and biochemical information. With the rise of big data and digital medicine, next-generation electronic ski...
Reconstructing growth and dynamic trajectories from single-cell transcriptomics data [0.03%]
从单细胞转录组学数据中重构生长和动态轨迹
Yutong Sha,Yuchi Qiu,Peijie Zhou et al.
Yutong Sha et al.
Time-series single-cell RNA sequencing (scRNA-seq) datasets provide unprecedented opportunities to learn dynamic processes of cellular systems. Due to the destructive nature of sequencing, it remains challenging to link the scRNA-seq snapsh...
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence [0.03%]
利用人工智能中保护隐私的合作来推进COVID-19的诊断
Xiang Bai,Hanchen Wang,Liya Ma et al.
Xiang Bai et al.
Artificial intelligence provides a promising solution for streamlining COVID-19 diagnoses; however, concerns surrounding security and trustworthiness impede the collection of large-scale representative medical data, posing a considerable ch...
Immunology: Meta-learning for T cell-receptor binding specificity and beyond [0.03%]
免疫学：元学习在T细胞受体结合特异性中的应用及展望
Duolin Wang,Fei He,Yang Yu et al.
Duolin Wang et al.
Predicting whether T-cell receptors bind to specific peptides is a challenging problem as the majority of binding examples in the training data involves only a few peptides. A new approach employs meta-learning to improve predictions for bi...
Predicting metabolomic profiles from microbial composition through neural ordinary differential equations [0.03%]
通过神经常微分方程从微生物组成预测代谢组学特征
Tong Wang,Xu-Wen Wang,Kathleen A Lee-Sarwar et al.
Tong Wang et al.
Characterizing the metabolic profile of a microbial community is crucial for understanding its biological function and its impact on the host or environment. Metabolomics experiments directly measuring these profiles are difficult and expen...
Generalizability of an acute kidney injury prediction model across health systems [0.03%]
急性肾损伤预测模型在不同医疗系统中的适用性
Jie Cao,Xiaosong Zhang,Vahakn Shahinian et al.
Jie Cao et al.
Delays in the identification of acute kidney injury (AKI) in hospitalized patients are a major barrier to the development of effective interventions to treat AKI. A recent study by Tomasev and colleagues at DeepMind described a model that a...
Yasha Ektefaie,George Dasoulas,Ayush Noori et al.
Yasha Ektefaie et al.
Artificial intelligence for graphs has achieved remarkable success in modeling complex systems, ranging from dynamic networks in biology to interacting particle systems in physics. However, the increasingly heterogeneous graph datasets call...
Emergent behaviour and neural dynamics in artificial agents tracking odour plumes [0.03%]
人工嗅觉代理追踪气味羽流的行为和神经动力学研究
Satpreet H Singh,Floris van Breugel,Rajesh P N Rao et al.
Satpreet H Singh et al.
Tracking an odour plume to locate its source under variable wind and plume statistics is a complex task. Flying insects routinely accomplish such tracking, often over long distances, in pursuit of food or mates. Several aspects of this rema...
Deep neural networks with controlled variable selection for the identification of putative causal genetic variants [0.03%]
可控变量选择的深度神经网络在寻找潜在致病基因变异中的应用
Peyman H Kassani,Fred Lu,Yann Le Guen et al.
Peyman H Kassani et al.
Deep neural networks (DNNs) have been successfully utilized in many scientific problems for their high prediction accuracy, but their application to genetic studies remains challenging due to their poor interpretability. Here we consider th...
Deep neural networks predict class I major histocompatibility complex epitope presentation and transfer learn neoepitope immunogenicity [0.03%]
深度神经网络预测I类主要组织相容性复合物表位呈递并转移学习新表位的免疫原性
Benjamin Alexander Albert,Yunxiao Yang,Xiaoshan M Shao et al.
Benjamin Alexander Albert et al.
Identifying neoepitopes that elicit an adaptive immune response is a major bottleneck to developing personalized cancer vaccines. Experimental validation of candidate neoepitopes is extremely resource intensive and the vast majority of cand...