We will discuss about "Inferring Regulatory Networks from Expression Data Using Tree-Based Methods," Huynh-Thu et al., PLoS ONE (2010). Abstract: One of the pressing open problems of computational systems biology is the elucidation of the topology of genetic regulatory networks (GRNs) using high throughput genomic data, in particular microarray gene expression data. The Dialogue for …

We will discuss about "Hidden Markov models for monitoring circadian rhythmicity in telemetric activity data", Huang, Qi, Journal of The Royal Society Interface 15.139 (2018): 20170885. Abstract: Wearable computing devices allow collection of densely sampled real-time information on movement enabling researchers and medical experts to obtain objective and non-obtrusive records of actual activity of a …

We will discuss about "Physics-informed neural networks for PDE-constrained optimization and control", Barry-Straume, Jostein, et al., arXiv preprint arXiv:2205.03377 (2022). Abstract: A fundamental problem of science is designing optimal control policies that manipulate a given environment into producing a desired outcome. Control PhysicsInformed Neural Networks simultaneously solve a given system state, and its respective optimal …

We will discuss about "Cell clustering for spatial transcriptomics data with graph neural networks", Li, J., Chen, S., Pan, X. et al., Nat Comput Sci 2, 399–408 (2022) Abstract: Spatial transcriptomics data can provide high-throughput gene expression profiling and the spatial structure of tissues simultaneously. Most studies have relied on only the gene expression information but …

We will discuss about "Absolute concentration robustness in networks with low-dimensional stoichiometric subspace", Meshkat, Nicolette, Anne Shiu, and Angelica Torres., Vietnam Journal of Mathematics 50.3 (2022): 623-651. Abstract: A reaction system exhibits “absolute concentration robustness” (ACR) in some species if the positive steady-state value of that species does not depend on initial conditions. Mathematically, this …