Given a question and a context passage, generate the answer having the word or phrase from the context passage. Here, the answer should be a shortest continous span from the passage.

Input: Consider Input: Context: Imatinib mesylate is a new drug that can inhibit the tyrosine kinase activity of Bcr-Abl, the receptors for platelet-derived growth factor receptor(PDGF) and stem cell factor, or c-kit. Chronic myeloid leukemia (CML) is distinguished by the presence of a reciprocal translocation between chromosomes 9 and 22 that results in a shortened chromosome 22, termed the Philadelphia(Ph) chromosome. As a result of the translocation, a fusion gene called the Bcr-Abl gene is created from two normal cellular genes, encoding a chimeric Bcr-Abl protein with a deregulated tyrosine kinase activity. The expression of Bcr-Abl tyrosine kinase has been shown to be necessary and sufficient for the transformed phenotype of CML cells. Imatinib can block the kinase activity of Bcr-Abl, thus inhibiting the proliferation of Ph-positive progenitors, and has shown activity against all phases of CML, though responses are most substantial and durable in patients in the chronic phase. An international phase III study which compared the efficacy of imatinib with that of interferon alpha combined with low-dose cytarabine in newly diagnosed chronic-phase CML showed the rate of major cytogenetic response at 24 months was 90%, including 82% of complete cytogenetic response. These results indicated that imatinib was superior to interferon-containing treatment as a first-line therapy. More than 10,000 patients worldwide, including those in Japan, have been treated with imatinib in clinical trials, and a lot of information has been accumulated on the use of this drug. The aim of this article is to review the use of this drug and the practical management of patients with chronic myeloid leukemia. 
 Question: What tyrosine kinase, involved in a Philadelphia- chromosome positive chronic myelogenous leukemia, is the target of Imatinib (Gleevec)?

Output: bcr-abl


Input: Consider Input: Context: Villa Wartholz was designed by Heinrich von Ferstel in the historicist style in the years 1870 to 1872 for Archduke Karl Ludwig of Austria. 
 Question: What is the name of the Villa Wartholz architect?

Output: heinrich von ferstel


Input: Consider Input: Context: MicroRNAs (miRNAs) are non-coding, short (21-23nt) regulators of protein-coding genes that are generally transcribed first into primary miRNA (pri-miR), followed by the generation of precursor miRNA (pre-miR). This finally leads to the production of the mature miRNA. A large amount of information is available on the pre- and mature miRNAs. However, very little is known about the pri-miRs, due to a lack of knowledge about their transcription start sites (TSSs). Based on the genomic loci, miRNAs can be categorized into two types --intragenic (intra-miR) and intergenic (inter-miR). While it is already an established fact that intra-miRs are commonly transcribed in conjunction with their host genes, the transcription machinery of inter-miRs is poorly understood. Although it is assumed that miRNA promoters are similar in structure to gene promoters, since both are transcribed by RNA polymerase II (Pol II), computational validations exhibit poor performance of gene promoter prediction methods on miRNAs. In this paper, we concentrate on the problem of TSS prediction for miRNAs. The present study begins with the identification of positive and negative promoter samples from recently published data stemming from RNA-sequencing studies. From these samples of experimentally validated miRNA TSSs, a number of standard sequence features are extracted. Furthermore, to account for potential footprints related to promoter regulation by CpG dinucleotide targeted DNA methylation, a number of novel features are defined. We develop a support vector machine (SVM) with RBF kernel for the prediction of miRNA TSSs trained on human miRNA promoters. A novel feature reduction technique based on archived multi-objective simulated annealing (AMOSA) identifies the final set of features. The resulting model trained on miRNA promoters shows improved performance over the one trained on protein-coding gene promoters in terms of classification accuracy, sensitivity and specificity. Results are also reported for a completely independent biologically validated test set. In a part of the investigation, the proposed approach is used to predict protein-coding gene TSSs. It shows a significantly improved performance when compared to previously published gene TSS prediction methods. 
 Question: Which polymerase transcribes pri-miRNAs?


Output: rnapii