Deciphering regulatory architectures of bacterial promoters from synthetic expression patterns [0.03%]
从合成表达模式中解析细菌启动子的调控结构
Rosalind Wenshan Pan,Tom Röschinger,Kian Faizi et al.
Rosalind Wenshan Pan et al.
For the vast majority of genes in sequenced genomes, there is limited understanding of how they are regulated. Without such knowledge, it is not possible to perform a quantitative theory-experiment dialogue on how such genes give rise to ph...
A multivalent binding model infers antibody Fc species from systems serology [0.03%]
多价结合模型从系统免疫学中推断抗体Fc物种
Armaan A Abraham,Zhixin Cyrillus Tan,Priyanka Shrestha et al.
Armaan A Abraham et al.
Systems serology aims to broadly profile the antigen binding, Fc biophysical features, immune receptor engagement, and effector functions of antibodies. This experimental approach excels at identifying antibody functional features that are ...
Adolescent and adult mice use both incremental reinforcement learning and short term memory when learning concurrent stimulus-action associations [0.03%]
青春期和成年期的小鼠在学习同时性刺激-行动关联时会使用增量增强学习和短期记忆
Juliana Chase,Liyu Xia,Lung-Hao Tai et al.
Juliana Chase et al.
Computational modeling has revealed that human research participants use both rapid working memory (WM) and incremental reinforcement learning (RL) (RL+WM) to solve a simple instrumental learning task, relying on WM when the number of stimu...
Multicellular model of neuroblastoma proposes unconventional therapy based on multiple roles of p53 [0.03%]
多细胞神经母细胞瘤模型提出了基于p53多种功能的非常规治疗方法
Kenneth Y Wertheim,Robert Chisholm,Paul Richmond et al.
Kenneth Y Wertheim et al.
Neuroblastoma is the most common extra-cranial solid tumour in children. Over half of all high-risk cases are expected to succumb to the disease even after chemotherapy, surgery, and immunotherapy. Although the importance of MYCN amplificat...
Estimating the distribution of parameters in differential equations with repeated cross-sectional data [0.03%]
基于重复横截面数据估计微分方程中的参数分布
Hyeontae Jo,Sung Woong Cho,Hyung Ju Hwang
Hyeontae Jo
Differential equations are pivotal in modeling and understanding the dynamics of various systems, as they offer insights into their future states through parameter estimation fitted to time series data. In fields such as economy, politics, ...
Sensitivity analysis of closed-loop one-chamber and four-chamber models with baroreflex [0.03%]
具有压力感受性反射的闭环单心室和四心室模型的敏感度分析
Karolina Tlałka,Harry Saxton,Ian Halliday et al.
Karolina Tlałka et al.
The baroreflex is one of the most important control mechanisms in the human cardiovascular system. This work utilises a closed-loop in silico model of baroreflex regulation, coupled to pulsatile mechanical models with (i) one heart chamber ...
Machine learning mathematical models for incidence estimation during pandemics [0.03%]
大流行期间发病率估计的机器学习数学模型
Oscar Fajardo-Fontiveros,Mattia Mattei,Giulio Burgio et al.
Oscar Fajardo-Fontiveros et al.
Accurate estimates of the incidence of infectious diseases are key for the control of epidemics. However, healthcare systems are often unable to test the population exhaustively, especially when asymptomatic and paucisymptomatic cases are w...
Predicting the infecting dengue serotype from antibody titre data using machine learning [0.03%]
基于抗体滴度数据使用机器学习预测感染的登革热血清型
Bethan Cracknell Daniels,Darunee Buddhari,Taweewun Hunsawong et al.
Bethan Cracknell Daniels et al.
The development of a safe and efficacious vaccine that provides immunity against all four dengue virus serotypes is a priority, and a significant challenge for vaccine development has been defining and measuring serotype-specific outcomes a...
Integration of partially observed multimodal and multiscale neural signals for estimating a neural circuit using dynamic causal modeling [0.03%]
基于动态因果模型利用部分观测的多模态、跨尺度神经信号估计神经环路
Jiyoung Kang,Hae-Jeong Park
Jiyoung Kang
Integrating multiscale, multimodal neuroimaging data is essential for a comprehensive understanding of neural circuits. However, this is challenging due to the inherent trade-offs between spatial coverage and resolution in each modality, ne...
Evaluation and comparison of methods for neuronal parameter optimization using the Neuroptimus software framework [0.03%]
基于神经优化软件框架的神经元参数优化方法的评估与比较
Máté Mohácsi,Márk Patrik Török,Sára Sáray et al.
Máté Mohácsi et al.
Finding optimal parameters for detailed neuronal models is a ubiquitous challenge in neuroscientific research. In recent years, manual model tuning has been gradually replaced by automated parameter search using a variety of different tools...