Molecular processes of neuronal learning have been well described. However, learning
mechanisms of non-neuronal cells are not yet fully understood at the molecular level. Here …

Non-Markovian models of stochastic biochemical kinetics often incorporate explicit time
delays to effectively model large numbers of intermediate biochemical processes. Analysis …

Living systems maintain or increase local order by working against the second law of
thermodynamics. Thermodynamic consistency is restored as they consume free energy …

Biphasic amplitude dynamics (BAD) of oscillation have been observed in many biological
systems. However, the specific topology structure and regulatory mechanisms underlying …

Collective states of inanimate particles self-assemble through physical interactions and
thermal motion. Despite some phenomenological resemblance, including signatures of …

Microbial synthetic epigenetics offers significant opportunities for the design of synthetic
biology tools by leveraging reversible gene control mechanisms without altering DNA …

Gene expression in mammalian cells is highly variable and episodic, resulting in a series of
discontinuous bursts of mRNAs. A challenge is to understand how static promoter …

Identifying the sources of cell-to-cell variability in signaling dynamics is essential to
understand drug response variability and develop effective therapeutics. However, it is …

Gene expression has inherent stochasticity resulting from transcription's burst manners.
Single-cell snapshot data can be exploited to rigorously infer transcriptional burst kinetics …

Stochastic network dynamics are typically assumed to be memoryless. Involving prolonged
dwells interrupted by instantaneous transitions between nodes, such Markov networks stand …