In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Example Input: Genome Detective is a web-based, user-friendly software application to quickly and accurately assemble all known virus genomes from next generation sequencing datasets. This application allows the identification of phylogenetic clusters and genotypes from assembled genomes in FASTA format. Since its release in 2019, we have produced a number of typing tools for emergent viruses that have caused large outbreaks, such as Zika and Yellow Fever Virus in Brazil. Here, we present The Genome Detective Coronavirus Typing Tool that can accurately identify the novel severe acute respiratory syndrome (SARS) related coronavirus (SARS-CoV-2) sequences isolated in China and around the world. The tool can accept up to 2,000 sequences per submission and the analysis of a new whole genome sequence will take approximately one minute. The tool has been tested and validated with hundreds of whole genomes from ten coronavirus species, and correctly classified all of the SARS-related coronavirus (SARSr-CoV) and all of the available public data for SARS-CoV-2. The tool also allows tracking of new viral mutations as the outbreak expands globally, which may help to accelerate the development of novel diagnostics, drugs and vaccines to stop the COVID-19 disease.
Example Output: Genome Detective Coronavirus Typing Tool for rapid identification and characterization of novel coronavirus genomes

Example Input: The purpose of this study was to compare the biochemical and biological properties of nonstructural protein (nsp) 15 among mouse hepatitis virus (MHV), severe acute respiratory syndrome coronavirus (SARS-CoV) and transmissible gastroenteritis virus (TGEV) in virus-infected and ectopically expressed cells. In virus-infected cells, MHV nsp15 distributed unevenly throughout the cytoplasm but predominantly in the perinuclear region. When expressed as N-terminal enhanced green fluorescence protein (EGFP) fusion, it predominantly formed speckles in the cytoplasm. In contrast, SARS-CoV and TGEV EGFP-nsp15s distributed smoothly in the whole cell and did not form speckles. Deletion mapping experiments identified two domains responsible for the speckle formation in MHV EGFP-nsp15: Domain I (aa101-150) and Domain III (aa301-374). Interestingly, Domain II (aa151-250) had an inhibitory effect on Domain IIIbut not on Domain I-mediated speckle formation. Expression of a small (35aa) sequence in Domain III alone was sufficient to form speckles for all 3 viral nsp15s. However, addition of surrounding sequences in Domain III abolished the speckle formation for TGEV nsp15 but not for MHV and SARS-CoV nsp15s. Further domain swapping experiments uncovered additional speckle-inducing and -suppressive elements in nsp15s of SARS-CoV and TGEV. Homotypic interaction involving Domain III of MHV nsp15 was further demonstrated biochemically. Moreover, the biological functions of the expressed nsp15s were assessed in MHV-infected cells. It was found that the effects of EGFP-nsp15s on MHV replication were both virus species-and nsp15 domain-dependent. Collectively these results thus underscore the differential biochemical and biological functions among the nsp15s of MHV, TGEV and SARS-CoV in host cells.
Example Output: Comparative in vivo analysis of the nsp15 endoribonuclease of murine, porcine and severe acute respiratory syndrome coronaviruses

Example Input: The SIJR model, simplified from the SEIJR model, is adopted to analyze the important parameters of the model of SARS epidemic such as the transmission rate, basic reproductive number. And some important parameters are obtained such as the transmission rate by applying this model to analyzing the situation in Hong Kong, Singapore and Canada at the outbreak of SARS. Then forecast of the transmission of SARS is drawn out here by the adjustment of parameters (such as quarantined rate) in the model. It is obvious that inflexion lies on the crunode of the graph, which indicates the big difference in transmission characteristics between the epidemic under control and not under control. This model can also be used in the comparison of the control effectiveness among different regions. The results from this model match well with the actual data in Hong Kong, Singapore and Canada and as a by-product, the index of the effectiveness of control in the later period can be acquired. It offers some quantitative indexes, which may help the further research in epidemic diseases.
Example Output:
SARS epidemical forecast research in mathematical model