In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

[Q]: Paragraph: Using sequence data to infer population dynamics is playing an increasing role in the analysis of outbreaks. The most common methods in use, based on coalescent inference, have been widely used but not extensively tested against simulated epidemics. Here, we use simulated data to test the ability of both parametric and non-parametric methods for inference of effective population size (coded in the popular BEAST package) to reconstruct epidemic dynamics. We consider a range of simulations centred on scenarios considered plausible for pandemic influenza, but our conclusions are generic for any exponentially growing epidemic. We highlight systematic biases in non-parametric effective population size estimation. The most prominent such bias leads to the false inference of slowing of epidemic spread in the recent past even when the real epidemic is growing exponentially. We suggest some sampling strategies that could reduce (but not eliminate) some of the biases. Parametric methods can correct for these biases if the infected population size is large. We also explore how some poor sampling strategies (e.g. that over-represent epidemiologically linked clusters of cases) could dramatically exacerbate bias in an uncontrolled manner. Finally, we present a simple diagnostic indicator, based on coalescent density and which can easily be applied to reconstructed phylogenies, that identifies time-periods for which effective population size estimates are less likely to be biased. We illustrate this with an application to the 2009 H1N1 pandemic. Pandemic growth rates from sequences E. de Silva et al. 1799 Pandemic growth rates from sequences E. de Silva et al. 1807  
 Title: Inferring pandemic growth rates from sequence data
[A]: True


[Q]: Paragraph: The outbreak of a new coronavirus (SARS-CoV-2) disease has become pandemic. To be more effectively controlling the disease, it is critical to set up an optimal quarantine period so that about 95% of the cases developing symptoms will be retained for isolation. At the moment, the WHO-established quarantine period is 14 days based on previous reports which had studied small sizes of hospitalized cases (10 and ~100, respectively), however, over 80% of adult-and 95% of child-cases were not necessary to stay in hospitals, and therefore, had not been hospitalized. Therefore, we are questioning if the current-inferred median incubation time is representative for the whole Covid-19 population, and if the current quarantine period is optimal. We compiled and analyzed the patient-level information of 2015 laboratory-confirmed Covid-19 cases including 99 children in 28 Chinese provinces. This cohort represents a wide-range spectrum of Covid-19 disease with both hospitalized and non-hospitalized cases. The full range of incubation periods of the Covid-19 cases ranged from 0 to 33 days among 2015 cases. There were 6 (0.13%) symptom-free cases including 4 females with a median age of 25.5 years and 2 males with a median age of 36 years. The median incubation period of both male and female adults was similar (7-day) but significantly shorter than that (9-day) of child cases (P=0.02). This cohort contained 4 transmission generations, and incubation periods of the cases between generations were not significantly different, suggesting that the virus has not been rapidly adapted to human beings. Interestingly, incubation periods of 233 cases (11.6%) were longer than the WHO-established quarantine period (14 days). Data modeling suggested that if adults take an extra 4-day or 7-day of isolation (i.e., a quarantine period of 18 or 21 days), 96.2% or 98.3%, respectively, of the people who are developing symptoms will be more effectively quarantined. Patients transmitted via lunch/dinner parties (i.e., gastrointestinal tract infection . CC-BY-NC 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity. is the (which was not peer-reviewed) The copyright holder for this preprint . 
 Title: Is a 14-day quarantine period optimal for effectively controlling coronavirus disease 2019 (COVID-19)?
[A]: False


[Q]: Paragraph: Members of the family Coronaviridae have the largest genomes of all RNA viruses, typically in the region of 30 kilobases. Several coronaviruses, such as Severe acute respiratory syndrome-related coronavirus (SARS-CoV) and Middle East respiratory syndrome-related coronavirus (MERS-CoV), are of medical importance, with high mortality rates and, in the case of SARS-CoV, significant pandemic potential. Other coronaviruses, such as Porcine epidemic diarrhea virus and Avian coronavirus, are important livestock pathogens. Ribosome profiling is a technique which exploits the capacity of the translating ribosome to protect around 30 nucleotides of mRNA from ribonuclease digestion. Ribosome-protected mRNA fragments are purified, subjected to deep sequencing and mapped back to the transcriptome to give a global "snap-shot" of translation. Parallel RNA sequencing allows normalization by transcript abundance. Here we apply ribosome profiling to cells infected with Murine coronavirus, mouse hepatitis virus, strain A59 (MHV-A59), a model coronavirus in the same genus as SARS-CoV and MERS-CoV. The data obtained allowed us to study the kinetics of virus transcription and translation with exquisite precision. We studied the timecourse of positive and negative-sense genomic and subgenomic viral RNA production and the relative translation efficiencies of the different virus ORFs. Virus mRNAs were not found to be translated more efficiently than host mRNAs; rather, virus translation dominates host translation at later time points due to high levels of virus transcripts. Triplet phasing of the profiling data allowed precise determination of translated reading frames and revealed several translated short open reading frames upstream of, or embedded within, known virus protein-coding regions. Ribosome pause sites were identified in the virus replicase polyprotein pp1a ORF and investigated experimentally. Contrary to expectations, ribosomes were not found to pause at the ribosomal frameshift site. To our knowledge this is the first application of ribosome profiling to an RNA virus. Ribosome profiling is emerging as a powerful technique to monitor translation in living cells at sub-codon resolution. It has particular applicability to virology, with the capacity to identify viral mRNAs that are being translated during infection and to provide new insights into virus gene expression, regulation and host-virus interactions. In this work, we carried out the first ribosome profiling analysis of an RNA virus, using as a model system the murine coronavirus strain MHV-A59, a betacoronavirus in the same genus as the medically important SARS-CoV and MERS-CoV. Parallel ribosome profiling and RNA sequencing of infected-cell time points was performed during the course of MHV replication in mouse tissue culture cells and used to determine virus gene expression kinetics and the relative translational efficiencies of virus and host mRNAs. The sensitivity and precision of the approach permitted us to uncover several unanticipated features of coronavirus translation, giving insights into ribosomal frameshifting, ribosome pausing, and the utilisation of short, potentially regulatory, upstream open reading frames. We also identified some challenges associated with the technique that are of general relevance to the ribosome profiling technique and developed bioinformatic strategies to address these. complement) during synthesis of subgenomic negative-sense templates that then give rise to the positive-sense mRNAs. The process of discontinuous transcription during negative-strand RNA synthesis takes place via polymerase "jumping" at specific "transcription regulatory sequences" (TRSs) on the gRNA template. In MHV, mRNAs 2 to 7 encode, respectively, proteins 2 and haemagglutinin-esterase (HE), spike (S), protein 4, protein 5 and envelope (E), membrane (M), nucleocapsid (N) and internal protein (I), with mRNAs 5 and 7 being functionally bicistronic (Fig 1A) [6]. In the laboratory-adapted strain (MHV-A59) employed in the present study, however, expression of HE and protein 4 is defective. Fig 1. MHV RNA synthesis and translation. (A) Transcript map of the 31335-nt MHV-A59 genome. Polyproteins pp1a and pp1b are translated from the genomic RNA, with pp1b being expressed as a transframe fusion with pp1a (i.e. pp1ab) via −1 programmed ribosomal frameshifting (−1 PRF). The 3 0 ORFs are expressed from a series of subgenomic RNAs produced during infection. Each subgenomic RNA contains a 5 0 leader sequence that is identical to the 5 0 leader of the genome, appended via polymerase "jumping" between body transcription regulatory sequences (TRSs) (green diamonds) and the leader TRS (orange diamond) during negative-strand synthesis. Due to mutations present in this laboratory-adapted strain, the hemagglutinin-esterase and ORF4 gene fragments (HE and 4; grey boxes) are not expected to be translated. (B) RiboSeq CHX (red) and RNASeq (green) densities at 5 h p.i. (repeat 1) in reads per million mapped reads (RPM). Read densities are plotted on a log(1+x) scale to cover the wide range in expression across the genome. Histograms show the positions of the 5 0 ends of reads with a +12 nt offset to map (for RPFs) approximate P-site positions. Negative-sense reads are shown in dark blue below the horizontal axis. (C) The positive-sense RiboSeq/RNASeq ratio, after first applying a 15-nt running mean (RM) filter to each individual distribution. 
 Title: High-Resolution Analysis of Coronavirus Gene Expression by RNA Sequencing and Ribosome Profiling
[A]:
True