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The recently proposed target inhibition map approach can infer stationary pathway models from drug perturbation experiments, but the method is limited to a steady-state snapshot of the underlying dynamical model. We consider the inverse problem of possible dynamic models that can generate the static target inhibition map model. From a deterministic viewpoint, we analyze the inference of Boolean networks that can generate the observed binarized sensitivities under different target inhibition scenarios. From a stochastic perspective, we investigate the generation of Markov chain models that satisfy the observed target inhibition sensitivities.<\/jats:p>","DOI":"10.1186\/s13637-014-0014-1","type":"journal-article","created":{"date-parts":[[2014,9,24]],"date-time":"2014-09-24T18:46:51Z","timestamp":1411584411000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Inference of dynamic biological networks based on responses to drug perturbations"],"prefix":"10.1186","volume":"2014","author":[{"given":"Noah","family":"Berlow","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lara","family":"Davis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Charles","family":"Keller","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ranadip","family":"Pal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2014,9,25]]},"reference":[{"key":"14_CR1","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1038\/nature03095","volume":"432","author":"C Sawyers","year":"2004","unstructured":"Sawyers C: Targeted cancer therapy. 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