Titlebook: Automated Reasoning for Systems Biology and Medicine; Pietro Liò,Paolo Zuliani Book 2019 Springer Nature Switzerland AG 2019 Model Selecti

ascetic

改良

面包屑

謙卑

Automated Reasoning for the Synthesis and Analysis of Biological Programs. Predictions of untested behaviour are generated based on all consistent models, without requiring time-consuming simulation or state space exploration, and the method can be used to identify additional components, topological ‘switches’ that allow cell state changes, and to predict gene-level dyna

cortisol

Statistical Model Checking-Based Analysis of Biological Networkslized to hybrid automata?by exploiting the given distribution over the initial states and the—much more sophisticated—system dynamics to associate a Markov chain?with the hybrid automaton. We then establish a strong relationship between the behaviors of the hybrid automaton and its associated Markov

綠州

使人煩燥

Using State Space Exploration to Determine How Gene Regulatory Networks Constrain Mutation Order in odel of ER-negative breast cancer. We show that there are differing levels of constraint in the order of mutations?for different combinations of oncogenes, and that the effects of ErbB2/HER2 over-expression depend on the preceding mutations.

輪流

饑荒

Logic and Linear Programs to Understand Cancer Response interaction rule. In this work, our aim is first to review previously proposed logic programs to discover key components in the graph-based causal models that distinguish different variants of cell types. These variants represent either cancerous versus healthy cell types, multiple cancer cell line

Bravado

Metastable Regimes and Tipping Points of Biochemical Networks with Potential Applications in Precisithe network. In particular, we show that for model parameters representing protein concentrations, the protein differential level between tumors of different types is reasonably reflected in the sensitivity scores, with sensitive parameters corresponding to differential proteins.