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: cDNA, synthesized on bovine coronavirus (BCV) genomic RNA templates, could be used to detect very small quantities (i .e . 1 pg) of viral RNA by hybridization with either radioisotopic-labelled or biotinylated recombinant plasmids . Virus was optimally attached to nitrocellulose membranes when spotted in 1 x SSC, whereas 20 x SSC was superior for viral RNA. Denaturation and RNA fixation of both RNA, still encapsidated in virus particles and isolated genomic RNA, was achieved by baking of the blots in vacuum . Virus detection in the supernatant of infected HRT-18 cells was feasible, but improved significantly after proteinase K treatment . No homology was observed between virus cDNA with either plasmid DNA or nucleic acid isolated from non-infected HRT-18 cells . Hybridization with radioisotopic-labelled probes in higher formamide concentrations (up to 60%) increased the detection signals, possibly by reducing reassociation of the probe . Significant detection amplification (30-50 times) was achieved in the case of biotinylated probes by stimulation of hyperpolymer formation on already hybridized target sequences, by additional hybridization with biotinylated pUC-19 . A detection amplification was also obtained when hybridization was done with two probes (pBC-52 and pBC-247), containing non-overlapping viral sequences . Although the detectability was surpassed by biotinylated probes, sensitivity was superior in radioisotopic virus detection .
Title: Biotinylated and radioactive cDNA probes in the detection by hybridization of bovine enteric coronavirus

Answer: True

Question: Paragraph: Host-pathogen interactions provide a fascinating example of two or more active genomes directly exerting mutual influence upon each other. These encounters can lead to multiple outcomes from symbiotic homeostasis to mutual annihilation, undergo multiple cycles of latency and lysogeny, and lead to coevolution of the interacting genomes. Such systems pose numerous challenges but also some advantages to modeling, especially in terms of functional, mathematical genome representations. The main challenges for the modeling process start with the conceptual definition of a genome for instance in the case of hostintegrated viral genomes. Furthermore, hardly understood influences of the activity of either genome on the other(s) via direct and indirect mechanisms amplify the needs for a coherent description of genome activity. Finally, genetic and local environmental heterogeneities in both the host's cellular and the pathogen populations need to be considered in multiscale modeling efforts. We will review here two prominent examples of host-pathogen interactions at the genome level, discuss the current modeling efforts and their shortcomings, and explore novel ideas of representing active genomes which promise being particularly adapted to dealing with the modeling challenges posed by host-pathogen interactions.
Title: Critical Dynamics in Host-Pathogen Systems

Answer: True

Question: Paragraph: We compare established docking programs, AutoDock Vina and Schrodinger's Glide, to the recently published NNScore scoring functions. As expected, the best protocol to use in a virtual-screening project is highly dependent on the target receptor being studied. However, the mean screening performance obtained when candidate ligands are docked with Vina and rescored with NNScore 1.0 is not statistically different than the mean performance obtained when docking and scoring with Glide. We further demonstrate that the Vina and NNScore docking scores both correlate with chemical properties like small-molecule size and polarizability. Compensating for these potential biases leads to improvements in virtual screen performance. Composite NNScore-based scoring functions suited to a specific receptor further improve performance. We are hopeful that the current study will prove useful for those interested in computer-aided drug design.
Title: Comparing Neural-Network Scoring Functions and the State of the Art: Applications to Common Library Screening

Answer:
False