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.

[Q]: Synthetic decapeptides (N 206) covering the entire sequence of mouse liver fumarylacetoacetate hydrolase (FAH) were used to analyze the specificities of the autoantibodies (autoAb) elicited towards this enzyme in mice infected with mouse hepatitis virus (MHV). These autoAb bound mainly to N-and C-terminal FAH peptides, the most reactive sequences being 1e50 and 390e420, respectively. Surprisingly, although FAH sequence 1e50 shares a high degree of homology with various MHV proteins, the C-terminal portion does not. Moreover, whereas the autoAb reacted with homologous peptides surrounding residues 70, 160 and 360, non-similar sequences around residues 130, 210, 240, 250, and 300 were also recognized, indicating that autoAb were not restricted to epitopes with sequence homologies. There was also a lack of correlation between the amount of anti-MHV or anti-FAH antibodies produced and the reactivity towards the peptides. Moreover, the spectrum of peptides recognized by the autoAb of a given mouse did not change significantly with time, which suggests that the MHV-elicited autoimmune response does not induce an epitope recognition spreading. Finally, anti-FAH Ab produced after immunization with rat liver FAH recognized essentially the same mouse FAH regions than autoAb from MHV-infected mice. Results indicated that the induction of the autoAb is not only related to molecular or structural mimicry, but rather supports the Danger model, in which any aggression, in this case the MHV infection, is susceptible to trigger the production of autoAb.
[A]: The peptide specificities of the autoantibodies elicited by mouse hepatitis virus A59

[Q]: The potential of DNA microarrays for detection of plant viruses is hampered by underutilization of sequence-independent amplification methods for target nucleic acid enrichment. A microarray system is described for an unbiased detection of plant viruses using both short (30 nt) and long (50 and 70 nt) oligonucleotide probes. The assay involves amplification of target nucleic acid using random primers followed by in vitro transcription whose cRNA product is labeled chemically, fragmented and used as target for hybridization. Initial optimization tests with Turnip vein clearing virus and Cauliflower mosaic virus showed increased hybridization efficiency with shorter cDNA targets (100 bp) and longer probes (50 and 70 nt). The system was validated in pure and mixed samples by detection of three Tymovirus species: Asclepias asymptomatic virus, Kennedya yellow mosaic virus and Turnip yellow mosaic virus. The method could detect sequence variants with 70-75% or higher sequence identity, indicating the possible utility of the approach for virus discovery. Array performance comparison of long probes demonstrated the competence of 50-mers to provide a satisfactory balance between detection sensitivity and specificity. The work described is a significant step towards a method to assess, in one assay, the presence of a large diversity of relatives of known viruses of plants.
[A]: Oligonucleotide-based microarray for detection of plant viruses employing sequence-independent amplification of targets

[Q]: Viruses evolve extremely quickly, so reliable methods for viral host prediction are necessary to safeguard biosecurity and biosafety alike. Novel human-infecting viruses are difficult to detect with standard bioinformatics workflows. Here, we predict whether a virus can infect humans directly from next-generation sequencing reads. We show that deep neural architectures significantly outperform both shallow machine learning and standard, homology-based algorithms, cutting the error rates in half and generalizing to taxonomic units distant from those presented during training. We propose a new approach for convolutional filter visualization to disentangle the information content of each nucleotide from its contribution to the final classification decision. Nucleotide-resolution maps of the learned associations between pathogen genomes and the infectious phenotype can be used to detect virulencerelated genes in novel agents, as we show here for the SARS-CoV-2 coronavirus, unknown before it caused a COVID-19 pandemic in 2020.
[A]:
Interpretable detection of novel human viruses from genome sequencing data