10 papers · ranked by Valyu relevance
Yuesong Wu, Haohao Su, Yuehua Cui
Cell-cell communication (CCC) is essential for maintaining tissue organization and driving biological progression, yet its inference from transcriptomic data has long been limited by the absence of spatial context. Advances in spatial transcriptomics (ST) now enable mechanistically grounded analyses of CCC by…
Eliezer Masliah
How transient neural representations become integrated and stable enough to function as internal neural models remains incompletely understood. Grounded in efficient coding, Bayesian and predictive frameworks, recurrent and attractor dynamics, neural state-space models, and systems neuroscience, the Principle of…
Yi Ren, Zimei Chen, Hayden Deans, Ying Nian Wu + 1 more
Extensive studies suggest the brain performs Bayesian inference to infer the latent world states. It is a fundamental neuroscience question that how canonical recurrent neural circuits in the brain implement Bayesian inference. Many existing theoretical studies focused on how the recurrent circuits compute the…
Lianne Gahan, Adélaïde Raguin, Partho Sakha De
Lignin’s complex and highly branched architecture plays a critical role in biomass utilisation. Yet, unravelling the intricate relation between lignin’s measurable structural features and the underlying biosynthesis dynamics remains a major challenge. This difficulty stems from the variability in monolignol and bond…
Jackie Rao, Muntadher Jihad, Giulia Biffi, Paul D.W. Kirk
Identifying cell types from single-cell RNA sequencing (scRNA-seq) data typically requires several separate and often uninterpretable steps: dimensionality reduction, batch-correction, clustering, marker-gene identification and the discovery of finer-grained structure. Here we introduce scFLAME (single-cell Factor…
Xiaoyue Hu, Yuhao Ma, Ruixing Ming, Heping Zhang + 1 more
Identifying essential biomarkers remains a core challenge in elucidating the pathogenic mechanisms and achieving precise diagnosis of complex diseases. Deep neural networks offer immense predictive power, yet their lack of interpretability severely limits downstream biological insight. Here, we introduce DeepVaris, an…
Maxime Lefèbvre, Arnaud Cléris, Mathieu Parmentier, Peter Van Loo + 2 more
Somatic mutations accumulate independently in the two parental genome copies of our cells throughout life and shape cancer evolution. Although local mutation rates are influenced by allele-specific features such as DNA sequence, epigenetic marks, and chromatin structure, whether these translate into genome-wide…
Linsui Deng, Kejun He, Xianyang Zhang
Mendelian randomization (MR) has been widely used to infer causal relationships between exposures and outcomes in epidemiological studies. However, classical MR assumptions can be violated when genetic variants are associated with outcomes through pathways other than the exposure, leading to uncorrelated and/or…
Arthur Zwaenepoel
We consider polygenic divergent selection in a mainland-island model, where our aim is to understand how patterns of genetic variation along the genome reflect the genetic architecture of postzygotic reproductive isolation. We derive a new expression for the effective migration rate (m_e_) at both neutral and…
Seiya Nishikawa, Satoshi Kuwana, Gen Honda, Hidenori Hashimura + 2 more
We investigate the mechanical principles underlying fruiting body morphogenesis in Dictyostelium discoideum. Quantitative shape analysis based on the Young–Laplace law, together with AFM indentation measurements, indicate surface tension as the dominant tissue-scale force acting on the culminating fruiting body. Based…