instruction:
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".
question:
Paragraph: Our ability to uncover complex network structure and dynamics from data is fundamental to understanding and controlling collective dynamics in complex systems. Despite recent progress in this area, reconstructing networks with stochastic dynamical processes from limited time series remains to be an outstanding problem. Here we develop a framework based on compressed sensing to reconstruct complex networks on which stochastic spreading dynamics take place. We apply the methodology to a large number of model and real networks, finding that a full reconstruction of inhomogeneous interactions can be achieved from small amounts of polarized (binary) data, a virtue of compressed sensing. Further, we demonstrate that a hidden source that triggers the spreading process but is externally inaccessible can be ascertained and located with high confidence in the absence of direct routes of propagation from it. Our approach thus establishes a paradigm for tracing and controlling epidemic invasion and information diffusion in complex networked systems. ½S i ðt 2 Þ þ S i ðt 6 Þ=2 and hS i ðt 2 þ 1Þi ¼ ½S i ðt 12 Þ þ S i ðt 14 Þ=2 based on the remaining strings marked in different colours (see Methods for more details). CST can be used to reconstruct the neighbouring vector X of node 2 from Y and U from Y ¼ U . X. 
 Title: ARTICLE Reconstructing propagation networks with natural diversity and identifying hidden sources
answer:
False


question:
Paragraph: Increasing numbers of H5N1 influenza viruses (IVs) are responsible for human deaths, especially in North Africa and Southeast Asian. The binding of hemagglutinin (HA) on the viral surface to host sialic acid (SA) receptors is a requisite step in the infection process. Phylogenetic analysis reveals that H5N1 viruses can be divided into 10 clades based on their HA sequences, with most human IVs centered from clade 1 and clade 2.1 to clade 2.3. Protein sequence alignment in various clades indicates the high conservation in the receptor-binding domains (RBDs) is essential for binding with the SA receptor. Two glycosylation sites, 158N and 169N, also participate in receptor recognition. In the present work, we attempted to construct a serial H5N1 HA models including diverse glycosylated HAs to simulate the binding process with various SA receptors in silico. As the SA-a-2,3-Gal and SA-a-2,6-Gal receptor adopted two distinctive topologies, straight and fishhooklike, respectively, the presence of N-glycans at 158N would decrease the affinity of HA for all of the receptors, particularly SA-a-2,6-Gal analogs. The steric clashes of the huge glycans shown at another glycosylation site, 169N, located on an adjacent HA monomer, would be more effective in preventing the binding of SA-a-2,3-Gal analogs. 
 Title: Two Glycosylation Sites in H5N1 Influenza Virus Hemagglutinin That Affect Binding Preference by Computer-Based Analysis
answer:
False


question:
Paragraph: High-throughput molecular profiling and computational biology are changing the face of virology, providing a new appreciation of the importance of the host in viral pathogenesis and offering unprecedented opportunities for better diagnostics, therapeutics and vaccines. Here, we provide a snapshot of the evolution of systems virology, from global gene expression profiling and signatures of disease outcome, to geometry-based computational methods that promise to yield novel therapeutic targets, personalized medicine and adeeper understanding of how viruses cause disease. To realize these goals, pipets and petri dishes need to join forces with the powers of mathematics and computational biology. 
 Title: SYSTEMS VIROLOGY: HOST-DIRECTED APPROACHES TO VIRAL PATHOGENESIS AND DRUG TARGETING
answer:

False