… analysis of edge signals. After reviewing the basic principles of algebraic topology, we derive
a sampling theory for signals of any order and emphasize the interplay between signals of …

… signaling networks are compared between tissue systems. Connectome focuses on
computational and graphical tools designed to analyze … the network topology of cell–cell signaling …

… shape of data and analyze it. Here, we review applications of topological data analysis (TDA)
to … TDA uses principles from algebraic topology to comprehensively measure shape in data …

… We ran the integrative topological analysis in each of these new datasets using the same
parameters than in the original analysis of the LGG cohort (Supplementary Table 3). …

… network topology is essential for improving the robustness of complex systems, like LN.
Networks’ resilience depends on their topology. … those of scale-free networks; in particular, while …

… In particular, we focus on topological data analysis (TDA), a set of methods grounded in the
mathematical field of algebraic topology that seeks to describe and harness features related …

… The overlapping of these balls form a unique topological characteristic that is unique to this
dataset, and hence we can use this unique topological characteristic to differentiate nuances …

… from the brain to social networks. Here we show that algebraic topology is a fundamental tool
… In particular we consider topological signals, ie, dynamical signals defined on simplices of …

… We report a chemical phosphoproteomics method to elucidate the topology of kinase-signaling
networks in mammalian cells. We identified >6,000 protein phosphorylation sites that can …

… topological structure of the brain network generated by EEG. Our findings provide a novel
solution for connectome-based biomarker analysis to … used in EEG topological analysis before. …