TASK DEFINITION: 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".
PROBLEM: Paragraph: Background: Newcastle Disease virus (NDV) causes severe and economically significant disease in almost all birds. However, factors that affect NDV replication in host cells are poorly understood. NDV generates long double-stranded RNA (dsRNA) molecules during transcription of single-stranded genomic RNA. Protein kinase R (PKR) is activated by dsRNA. The aim of this study was to elucidate the role of PKR in NDV infection. Results: NDV infection led to the activation of dsRNA-dependent PKR and phosphorylation of its substrate, translation initiation factor eIF2α, in a dose-dependent manner by either the lentogenic strain LaSota or a velogenic strain Herts/33. PKR activation coincided with the accumulation of dsRNA induced by NDV infection. PKR knockdown remarkably decreased eIF2α phosphorylation as well as IFN-β mRNA levels, leading to the augmentation of extracellular virus titer. Furthermore, siRNA knockdown or phosphorylation of eIF2α or okadaic acid treatment significantly impaired NDV replication, indicating the critical role of the PKR/eIF2α signaling cascade in NDV infection. Conclusion: PKR is activated by dsRNA generated by NDV infection and inhibits NDV replication by eIF2α phosphorylation. This study provides insight into NDV-host interactions for the development of candidate antiviral strategies. 
 Title: Activation of the PKR/eIF2α signaling cascade inhibits replication of Newcastle disease virus

SOLUTION: False

PROBLEM: Paragraph: Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy, and generate large amounts of 2 of 55 high-dimensional and complex experimental data. Open source processing and analysis tools are of major interest in light of innovative, open and reproducible science. The scientific community has developed a wide range of open source software, providing freely available advanced processing and analysis approaches. The programming and statistics environment R has emerged as one of the most popular environments to process and analyse Metabolomics datasets. A major benefit of such an environment is the possibility of connecting different tools into more complex workflows. Combining reusable data processing R scripts with the experimental data thus allows for open, reproducible research. This review provides an extensive overview of existing packages in R for different steps in a typical computational metabolomics workflow, including data processing, biostatistics, metabolite annotation and identification, and biochemical network and pathway analysis. Multifunctional workflows, possible user interfaces and integration into workflow management systems are also reviewed. In total, this review summarises more than two hundred metabolomics specific packages primarily available on CRAN, Bioconductor and GitHub. 
 Title: metabolites H OH OH The metaRbolomics Toolbox in Bioconductor and beyond

SOLUTION: True

PROBLEM: Paragraph: The CVTree web server (http://tlife.fudan.edu.cn/ cvtree) presented here is a new implementation of the whole genome-based, alignment-free composition vector (CV) method for phylogenetic analysis. It is more efficient and user-friendly than the previously published version in the 2004 web server issue of Nucleic Acids Research. The development of whole genome-based alignment-free CV method has provided an independent verification to the traditional phylogenetic analysis based on a single gene or a few genes. This new implementation attempts to meet the challenge of ever increasing amount of genome data and includes in its database more than 850 prokaryotic genomes which will be updated monthly from NCBI, and more than 80 fungal genomes collected manually from several sequencing centers. This new CVTree web server provides a faster and stable research platform. Users can upload their own sequences to find their phylogenetic position among genomes selected from the server's inbuilt database. All sequence data used in a session may be downloaded as a compressed file. In addition to standard phylogenetic trees, users can also choose to output trees whose monophyletic branches are collapsed to various taxonomic levels. This feature is particularly useful for comparing phylogeny with taxonomy when dealing with thousands of genomes. 
 Title: CVTree update: a newly designed phylogenetic study platform using composition vectors and whole genomes

SOLUTION:
False