CLASPP: A unified model for predicting post-translational modifications [0.03%]
CLASPP：预测蛋白质翻译后修饰的统一模型
Nathan Gravel,Zhongliang Zhou,Ruili Fang et al.
Nathan Gravel et al.
Post-Translational Modifications (PTMs) are a fundamental mechanism for regulating cellular pathways and increasing the functional diversity of the proteome. Accurately predicting the PTM types that are likely to occur at a given site in th...
CLASPP: A unified model for predicting post-translational modifications [0.03%]
CLASPP：一种统一的蛋白质修饰位点预测模型
Nathan Gravel,Zhongliang Zhou,Ruili Fang et al.
Nathan Gravel et al.
Post-Translational Modifications (PTMs) are a fundamental mechanism for regulating cellular pathways and increasing the functional diversity of the proteome. Accurately predicting the PTM types that are likely to occur at a given site in th...
REvolutionH-tl 2.0: A fast and robust tool for decoding evolutionary gene histories [0.03%]
REvolutionH-tl 2.0：一个用于解码进化基因历史的快速且稳健工具
José Antonio Ramírez-Rafael,Annachiara Korchmaros,Katia Aviña-Padilla et al.
José Antonio Ramírez-Rafael et al.
REvolutionH-tl is a fast, scalable, and integrated software platform for inferring orthology relationships, gene trees, species trees, and reconciled evolutionary scenarios directly from sequence data. Built upon the formal framework of bes...
Evaluation of short-term multi-target respiratory forecasts over winter 2024-25 in England using sub-ensemble contribution analyses [0.03%]
基于子集合贡献分析的英格兰2024-2025年冬季多目标短期呼吸系统疾病预报评估
Jack Kennedy,William Ferguson,Owen Jones et al.
Jack Kennedy et al.
Background: Epidemic forecasting research often assesses ensembles and their component models using probabilistic scoring rules. Quantifying how individual models affect ensemble performance is challenging, particularly a...
Evaluation of short-term multi-target respiratory forecasts over winter 2024-25 in England using sub-ensemble contribution analyses [0.03%]
基于子集合贡献分析的英格兰2024-2025年冬季多目标短期呼吸系统疾病预测评估
Jack Kennedy,William Ferguson,Owen Jones et al.
Jack Kennedy et al.
Background: Epidemic forecasting research often assesses ensembles and their component models using probabilistic scoring rules. Quantifying how individual models affect ensemble performance is challenging, particularly a...
A benchmarking study of feature screening approaches across type 1 diabetes omics studies classification settings [0.03%]
一种基准研究：在1型糖尿病综合分类设置中筛查特征的方法
Erik D VonKaenel,Lisa M Bramer,Javier E Flores et al.
Erik D VonKaenel et al.
In recent years, high dimensional omics analyses have become more commonplace for investigating complex biological systems. Typically, these studies attempt to identify key biomolecules associated with a particular biological process. Often...
Assessing the reliability of cellular decision making from noisy, multidimensional single-cell TNF-NF-κB signaling data [0.03%]
基于噪声多维单细胞TNF-NF-κB信号数据的细胞决策可靠性的评估
Ali Emadi,Tomasz Lipniacki,Andre Levchenko et al.
Ali Emadi et al.
Cells make hard calls under noise. When signaling is abnormal, those calls can go wrong and drive pathological conditions and diseases. In this research, we develop a Neyman-Pearson (NP) detection-theory framework that maximizes probability...
Toward reliable machine learning models for neural circuit inference: A diagnostic study of CNNs on spike trains [0.03%]
面向可靠的机器学习模型的神经回路推理：CNN在脉冲列车上的诊断研究
Xiaoqian Sun,Hui Lu,Chen Zeng et al.
Xiaoqian Sun et al.
Understanding neuronal topology-how neurons are connected-is essential for uncovering neural computation principles and functional organization. However, accurately reconstructing such connectivity remains challenging due to the indirect na...
An alignment-free strategy for circulating tumor DNA detection and tumor fraction estimation from whole-genome sequencing data [0.03%]
一种基于全基因组测序数据的循环肿瘤DNA检测和肿瘤分数估计的无比对策略
Carmen Oroperv,Amanda Frydendahl,Tenna Vesterman Henriksen et al.
Carmen Oroperv et al.
Circulating tumor DNA (ctDNA) is emerging as a promising biomarker for postoperative monitoring of cancer patients. Precise estimation of circulating tumor fraction is crucial for evaluating treatment effects and timely detection of disease...
RareCapsNet: An explainable capsule network enables robust discovery of rare cell populations from large-scale single-cell transcriptomics [0.03%]
稀有细胞群落的稳健发现方法：一种可解释胶囊网络模型罕见细胞群落的稳健发现方法：一种可解释胶囊网络模型
Sumanta Ray,Snehalika Lall
Sumanta Ray
Large-scale single-cell RNA sequencing has created new opportunities for computational identification of rare cell populations from complex transcriptomic data. Improvements in sequencing throughput now enable the profiling of tens of thous...