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".

Ex Input:
Paragraph: Delineation of the intricacies of protein function from macromolecular structure constitutes a continual obstacle in the study of cell and pathogen biology. Structure-based phylogenetic analysis has emerged as a powerful tool for addressing this challenge, allowing the detection and quantification of conserved architectural properties between proteins, including those with low or no detectable sequence homology. With a focus on viral protein structure, we highlight how a number of investigations have utilized this powerful method to infer common functionality and ancestry.
Title: Unraveling virus relationships by structure-based phylogenetic classification

Ex Output:
True

Ex Input:
Paragraph: The nucleoprotein-encoding gene (N) of murine hepatitis virus type 3 (MHV 3), from the Mill Hilt strain, was cloned and sequenced. It was compared to gene N from other routine coronaviruses and was found to share more similarities with N sequences from MHV 1 and MHV JHM strains than with the published MHV3 N sequence which is almost identical to MHVA59. We suggest that the evolution of some MHV N sequences resulted from a double recombination phenomenon between two ancestors. Furthermore, comparison of protein N from avian and mammalian coronaviruses leads to the hypothesis that horizontal transfer events of the virus from one host species to another have occurred.
Title: The gene encoding the nucleocapsid protein: sequence analysis in murine hepatitis virus type 3 and evolution in Coronaviridae

Ex Output:
True

Ex Input:
Paragraph: have set up a public forum on www.LAMP-Seq.org. The ongoing COVID-19 pandemic has already caused devastating losses. Early evidence shows that the exponential spread of COVID-19 can be slowed by restrictive isolation measures, but these place a tremendous burden on society. Moreover, once these restrictions are lifted, the exponential spread is likely to re-emerge. It has been suggested that populationscale testing can help break the cycle of isolation and spread, but current detection methods are not capable of such large-scale processing. Here we propose LAMP-Seq, a barcoded Reverse-Transcription Loop-mediated Isothermal Amplification (RT-LAMP) protocol that could dramatically reduce the cost and complexity of population-scale testing. In this approach, individual samples are processed in a single heat step, producing barcoded amplicons that can be shipped to a sequencing center, pooled, and analyzed en masse. Using unique barcode combinations per sample from a compressed barcode space enables extensive pooling, significantly reducing cost and organizational efforts. Given the low cost and scalability of next-generation sequencing, we believe that this method can be affordably scaled to analyze millions of samples per day using existing sequencing infrastructure.
Title: LAMP-Seq: Population-Scale COVID-19 Diagnostics Using a Compressed Barcode Space

Ex Output:
False