Stability theoryIn mathematics, stability theory addresses the stability of solutions of differential equations and of trajectories of dynamical systems under small perturbations of initial conditions. The heat equation, for example, is a stable partial differential equation because small perturbations of initial data lead to small variations in temperature at a later time as a result of the maximum principle. In partial differential equations one may measure the distances between functions using Lp norms or the sup norm, while in differential geometry one may measure the distance between spaces using the Gromov–Hausdorff distance.
Gene regulatory networkA gene (or genetic) regulatory network (GRN) is a collection of molecular regulators that interact with each other and with other substances in the cell to govern the gene expression levels of mRNA and proteins which, in turn, determine the function of the cell. GRN also play a central role in morphogenesis, the creation of body structures, which in turn is central to evolutionary developmental biology (evo-devo).
Lyapunov stabilityVarious types of stability may be discussed for the solutions of differential equations or difference equations describing dynamical systems. The most important type is that concerning the stability of solutions near to a point of equilibrium. This may be discussed by the theory of Aleksandr Lyapunov. In simple terms, if the solutions that start out near an equilibrium point stay near forever, then is Lyapunov stable. More strongly, if is Lyapunov stable and all solutions that start out near converge to , then is said to be asymptotically stable (see asymptotic analysis).
BuddingBudding or blastogenesis is a type of asexual reproduction in which a new organism develops from an outgrowth or bud due to cell division at one particular site. For example, the small bulb-like projection coming out from the yeast cell is known as a bud. Since the reproduction is asexual, the newly created organism is a clone and excepting mutations is genetically identical to the parent organism. Organisms such as hydra use regenerative cells for reproduction in the process of budding.
Mating of yeastThe yeast Saccharomyces cerevisiae is a simple single-celled eukaryote with both a diploid and haploid mode of existence. The mating of yeast only occurs between haploids, which can be either the a or α (alpha) mating type and thus display simple sexual differentiation. Mating type is determined by a single locus, MAT, which in turn governs the sexual behaviour of both haploid and diploid cells. Through a form of genetic recombination, haploid yeast can switch mating type as often as every cell cycle. S.
Markov chainA Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. Informally, this may be thought of as, "What happens next depends only on the state of affairs now." A countably infinite sequence, in which the chain moves state at discrete time steps, gives a discrete-time Markov chain (DTMC). A continuous-time process is called a continuous-time Markov chain (CTMC).
S phaseS phase (Synthesis Phase) is the phase of the cell cycle in which DNA is replicated, occurring between G1 phase and G2 phase. Since accurate duplication of the genome is critical to successful cell division, the processes that occur during S-phase are tightly regulated and widely conserved. G1/S transition Entry into S-phase is controlled by the G1 restriction point (R), which commits cells to the remainder of the cell-cycle if there is adequate nutrients and growth signaling.
Adoptive cell transferAdoptive cell transfer (ACT) is the transfer of cells into a patient. The cells may have originated from the patient or from another individual. The cells are most commonly derived from the immune system with the goal of improving immune functionality and characteristics. In autologous cancer immunotherapy, T cells are extracted from the patient, genetically modified and cultured in vitro and returned to the same patient. Comparatively, allogeneic therapies involve cells isolated and expanded from a donor separate from the patient receiving the cells.
Interaction informationThe interaction information is a generalization of the mutual information for more than two variables. There are many names for interaction information, including amount of information, information correlation, co-information, and simply mutual information. Interaction information expresses the amount of information (redundancy or synergy) bound up in a set of variables, beyond that which is present in any subset of those variables. Unlike the mutual information, the interaction information can be either positive or negative.
Conditional mutual informationIn probability theory, particularly information theory, the conditional mutual information is, in its most basic form, the expected value of the mutual information of two random variables given the value of a third. For random variables , , and with support sets , and , we define the conditional mutual information as This may be written in terms of the expectation operator: . Thus is the expected (with respect to ) Kullback–Leibler divergence from the conditional joint distribution to the product of the conditional marginals and .
