Seminar

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 …

We will discuss about “ The Internal Model Principle for Biomolecular Control Theory ”, Gupta, Ankit, and Mustafa Khammash., IEEE Open Journal of Control Systems 2 (2023): 63-69.   Abstract The well-known Internal Model Principle (IMP) is a cornerstone of modern control theory. It stipulates the necessary conditions for asymptotic robustness of disturbance-prone dynamical systems …

We will discuss about “ Decomposing predictability to identify dominant causal drivers in complex ecosystems ”,Suzuki, Kenta, Shin-ichiro S. Matsuzaki, and Hiroshi Masuya., Proceedings of the National Academy of Sciences 119.42 (2022): e2204405119.   Abstract Ecosystems are complex systems of various physical, biological, and chemical processes. Since ecosystem dynamics are composed of a mixture of …

We will discuss about “Generalized Michaelis–Menten rate law with time-varying molecular concentrations”, Lim, Roktaek, et al.,bioRxiv (2022): 2022-01   Abstract The Michaelis–Menten (MM) rate law has been the dominant paradigm of modeling biochemical rate processes for over a century with applications in biochemistry, biophysics, cell biology, and chemical engineering. The MM rate law and its …

We will discuss about “Exact solution of a three-stage model of stochastic gene expression including cell-cycle dynamics”, Wang, Yiling, et al., bioRxiv (2023): 2023-08.   Abstract The classical three-stage model of stochastic gene expression predicts the statistics of single cell mRNA and protein number fluctuations as a function of the rates of promoter switching, transcription, translation, …