Titlebook: Computational Methods in Systems Biology; 17th International C Luca Bortolussi,Guido Sanguinetti Conference proceedings 2019 Springer Natur

宽敞

Sequential Reprogramming of Biological Network Fateean networks. We present a novel theoretical framework and give an upper bound on the size of control sequences as a function of the number of observed variables. We also define an algorithm for inferring minimal parsimonious control sequences allowing to reach a final state satisfying a particular phenotypic property.

玉米

母猪

crockery

, and Dynastic Successions in Modern Europe,amming and the minimal sequential reprogramming on a variety of biological networks. The results show that our method can greatly reduce the number of perturbations compared to the one-step reprogramming, while having comparable results with the minimal sequential reprogramming. Moreover, our implem

Certainty

锡箔纸

sorbitol

Katsushi Yamaguchi,Hironori Higashideith high accuracy on real-world data. Optimized classifiers capture biologically relevant miRNAs that are cancer-type specific. The comparison to a single-circuit classifier design approach shows that DCs perform with significantly higher accuracy than individual circuits. The algorithm is implement

arabesque

Dynamics of populations and communities, in input arrival, the circuit exhibits qualitatively distinct observable phenotypes. In particular, these phenotypes are long lived transients: they all converge to a single value, but so slowly, that they seem stable for an extended time period, longer than typical experiment duration. We used rul

纬线

Pert敏捷

Perceptions of Security Concerns,sment on the BioModels repository by measuring their compression capability over 667 models. Through a number of selected case studies, we also show their ability in yielding physically interpretable reductions that can reveal dynamical patterns of the bio-molecular processes under consideration.