Reusability report: Leveraging supervised learning to uncover phenotype-relevant biology from single-cell RNA sequencing data [0.03%]
基于单细胞RNA测序数据的监督学习再利用报告：揭示与表型相关的生物学规律
Yingying Cao,Tian-Gen Chang,Sahil Sahni et al.
Yingying Cao et al.
Recent advances in single-cell transcriptome sequencing and computational analysis methods have improved our understanding of cellular heterogeneity. However, associating different cell subsets with phenotypes remains challenging. Recently,...
Error-controlled non-additive interaction discovery in machine learning models [0.03%]
可控的机器学习模型中非加性相互作用的发现算法
Winston Chen,Yifan Jiang,William Stafford Noble et al.
Winston Chen et al.
Machine learning (ML) models are powerful tools for detecting complex patterns, yet their 'black-box' nature limits their interpretability, hindering their use in critical domains like healthcare and finance. Interpretable ML methods aim to...
Conditional generation of real antigen-specific T cell receptor sequences [0.03%]
生成条件下的抗原特异性T细胞受体序列生成
Dhuvarakesh Karthikeyan,Sarah N Bennett,Amy G Reynolds et al.
Dhuvarakesh Karthikeyan et al.
Despite recent advances in T cell receptor (TCR) engineering, designing functional TCRs against arbitrary targets remains challenging due to complex rules governing cross-reactivity and limited paired data. Here we present TCR-TRANSLATE, a ...
Modelling neural coding in the auditory midbrain with high resolution and accuracy [0.03%]
高精度和高分辨率的听觉中脑神经编码建模研究
Fotios Drakopoulos,Lloyd Pellatt,Shievanie Sabesan et al.
Fotios Drakopoulos et al.
Computational models of auditory processing can be valuable tools for research and technology development. Models of the cochlea are highly accurate and widely used, but models of the auditory brain lag far behind in both performance and pe...
Toward a framework for risk mitigation of potential misuse of artificial intelligence in biomedical research [0.03%]
迈向人工智能在生物医学研究中潜在误用风险缓解框架的第一步
Artem A Trotsyuk,Quinn Waeiss,Raina Talwar Bhatia et al.
Artem A Trotsyuk et al.
The rapid advancement of artificial intelligence (AI) in biomedical research presents considerable potential for misuse, including authoritarian surveillance, data misuse, bioweapon development, increase in inequity and abuse of privacy. We...
Mohammad Hosseini,Christopher R Donohue
Mohammad Hosseini
High-level visual representations in the human brain are aligned with large language models [0.03%]
人类大脑中的高级视觉表征与大型语言模型一致
Adrien Doerig,Tim C Kietzmann,Emily Allen et al.
Adrien Doerig et al.
The human brain extracts complex information from visual inputs, including objects, their spatial and semantic interrelations, and their interactions with the environment. However, a quantitative approach for studying this information remai...
Histopathology-based protein multiplex generation using deep learning [0.03%]
基于深度学习的免疫组化病理图像多路蛋白信号生成技术
Sonali Andani,Boqi Chen,Joanna Ficek-Pascual et al.
Sonali Andani et al.
Multiplexed protein imaging offers valuable insights into interactions between tumours and their surrounding tumour microenvironment, but its widespread use is limited by cost, time and tissue availability. Here we present HistoPlexer, a de...
Sparse learned kernels for interpretable and efficient medical time series processing [0.03%]
可解释且高效的医疗时间序列处理的稀疏学习核函数
Sully F Chen,Zhicheng Guo,Cheng Ding et al.
Sully F Chen et al.
Rapid, reliable and accurate interpretation of medical time series signals is crucial for high-stakes clinical decision-making. Deep learning methods offered unprecedented performance in medical signal processing but at a cost: they were co...
An end-to-end recurrent compressed sensing method to denoise, detect and demix calcium imaging data [0.03%]
一种端到端的递归压缩感知钙成像数据去噪、检测和解混方法
Kangning Zhang,Sean Tang,Vivian Zhu et al.
Kangning Zhang et al.
Two-photon calcium imaging provides large-scale recordings of neuronal activities at cellular resolution. A robust, automated and high-speed pipeline to simultaneously segment the spatial footprints of neurons and extract their temporal act...