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".
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Question: 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

Answer: True


Question: Paragraph: Proteinchip profiling is a powerful and innovative proteomic technology for the discovery of biomarkers and the development of diagnostic/prognostic assays. On the basis of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), Ciphergen's proteinchip system offers a single, unified, and high throughput platform for a multitude of proteomic research applications. Proteins are the major functional components of the cell. The study of proteomics helps to better understand the mechanism of a disease. Remarkable findings in disease biomarkers have shed light on the early diagnosis, monitoring, and prognosis of various diseases, especially for cancer. In this paper, the development and technology of SELDI-TOF MS are introduced. The research progress and encouraging research results in malignancies, infectious diseases, neurological diseases, and diabetes mellitus using SELDI-TOF MS are reviewed. This paper concludes by evaluating the pros and cons, and the future perspectives are also expounded. 
 Title: Research Progress in SELDI-TOF MS and Its Clinical Applications

Answer: True


Question: Paragraph: Using a =P complementary DNA (cDNA) prepared against the A59 nucleocapsid protein messenger RNA, we have investigated the extent of homology between A59 and four other strains of murine hepatitis virus (MHV). Analysis by hybridization kinetics of the annealing between A59 [S2P]cDNA and infected cell RNA from the other four MHV strains demonstrated 7040% homology. By gel transfer analysis, the A59 [S2P]eDNA was able to detect subgenomic-size virus-specific RNAs in cells infected with all of the five MHV strains. A similar pattern of seven viral RNAs was detected in cells infected with A59, MHV-1, MHV-3, and JHM. In contrast, cells infected with MHV-S contained seven virusspecific RNAs, of which only the two smallest species comigrated with RNAs from the other four strains. The results suggest that as previously shown with A59 (S. Cheley, R. Anderson, M. J. Cupples, E. C. M. Lee Chan, and V. L. Morris (1981) Virdogy, 112,596-604), all MHV strains tested encode a nested set of subgenomic RNAs. Analysis of [?l]methionine-labeled viral proteins by SDS-polyacrylamide gel electrophoresis revealed that each strain of MHV specified four major viral polypeptides with apparent molecular weights very similar to those previously reported for the E2, N, El, and PEl polypeptides of A59. The strong degree of interstrain homology among the five MHV strains investigated was confirmed by comparative chymotryptic peptide mapping of the viral N proteins. A majority of the chymotryptic peptides from each of the [35S$nethioninelabeled N proteins was found to coelute by high-performance liquid chromatography. Moreover, this technique of peptide mapping indicated a particularly strong relatedness between MHV-1 and MHV-S and among MHV3, JHM, and A59. 
 Title: RNA and Polypeptide Homology among Murine Coronaviruses

Answer:
False