We will discuss about “Uncovering specific mechanisms across cell types in dynamical models”, Hauber, Adrian Lukas, Marcus Rosenblatt, and Jens Timmer., bioRxiv (2023): 2023-01. Abstract Ordinary differential equations are frequently employed for mathematical modeling of biological systems. The identification of mechanisms that are specific to certain cell types is crucial for building useful models and to …

We will discuss about “The energy cost and optimal design of networks for biological discrimination”, Yu, Qiwei, Anatoly B. Kolomeisky, and Oleg A. Igoshin., Journal of the Royal Society Interface 19.188 (2022): 20210883. Abstract Many biological processes discriminate between correct and incorrect substrates through the kinetic proofreading mechanism that enables lower error at the cost of …

We will discuss about “Wearable data science for personalized digital medicine” Abstract Millions of people currently use wearables such as the Apple Watch to monitor their physical activity, heart rate, and other physiological signals, generating an unprecedented amount of wearable data. This presents an opportunity for digital medicine to advance precision medicine. However, the noisy …

We will discuss about “scPrisma infers, filters and enhances topological signals in single-cell data using spectral template matching”, Karin, Jonathan, Yonathan Bornfeld, and Mor Nitzan., Nature Biotechnology (2023): 1-10. Abstract Single-cell RNA sequencing has been instrumental in uncovering cellular spatiotemporal context. This task is challenging as cells simultaneously encode multiple, potentially cross-interfering, biological signals. Here we …

We will discuss about “The singularity response reveals entrainment properties of the plant circadian clock”, Masuda, Kosaku, et al., Nature Communications 12.1 (2021): 864. Abstract Circadian clocks allow organisms to synchronize their physiological processes to diurnal variations. A phase response curve allows researchers to understand clock entrainment by revealing how signals adjust clock genes differently …