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: Linear motifs are short, evolutionarily plastic components of regulatory proteins and provide low-affinity interaction interfaces. These compact modules play central roles in mediating every aspect of the regulatory functionality of the cell. They are particularly prominent in mediating cell signaling, controlling protein turnover and directing protein localization. Given their importance, our understanding of motifs is surprisingly limited, largely as a result of the difficulty of discovery, both experimentally and computationally. The Eukaryotic Linear Motif (ELM) resource at http:// elm.eu.org provides the biological community with a comprehensive database of known experimentally validated motifs, and an exploratory tool to discover putative linear motifs in user-submitted protein sequences. The current update of the ELM database comprises 1800 annotated motif instances representing 170 distinct functional classes, including approximately 500 novel instances and 24 novel classes. Several older motif class entries have been also revisited, improving annotation and adding novel instances. Furthermore, addition of full-text search capabilities, an enhanced interface and simplified batch download has improved the overall accessibility of the ELM data. The motif discovery portion of the ELM resource has added conservation, and structural attributes have been incorporated to aid users to discriminate biologically relevant motifs from stochastically occurring non-functional instances. Figure 5 . Schema of the ELM resource and data life cycle. Annotated ELM classes, and instances thereof, can be searched by database query. Via sequence search by the motif detection pipeline, annotated ELM classes yield putative instances in query sequences. By adding experimental evidence and references, these putative instances become candidate instances for annotation, and, with further curation, ultimately become fully annotated instances.

A: ELM-the database of eukaryotic linear motifs
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Q: Concepts are the most fundamental units of cognition in philosophy and how to learn concepts from various aspects in the real world is the main concern within the domain of conceptual knowledge presentation and processing. In order to improve efficiency and flexibility of concept learning, in this paper we discuss concept learning via granular computing from the point of view of cognitive computing. More precisely, cognitive mechanism of forming concepts is analyzed based on the principles from philosophy and cognitive psychology, including how to model concept-forming cognitive operators, define cognitive concepts and establish cognitive concept structure. Granular computing is then combined with the cognitive concept structure to improve efficiency of concept learning. Furthermore, we put forward a cognitive computing system which is the initial environment to learn composite concepts and can integrate past experiences into itself for enhancing flexibility of concept learning. Also, we investigate cognitive processes whose aims are to deal with the problem of learning one exact or two approximate cognitive concepts from a given object set, attribute set or pair of object and attribute sets.

A: Concept learning via granular computing: A cognitive viewpoint
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Q: Background: Human rhinoviruses (HRVs) are a well-recognized cause of long-term care home (LTCH) outbreaks of respiratory illness. However, there are limited data on the molecular epidemiology of the HRV types involved. Objectives: To determine whether a large respiratory outbreak in a LTCH was caused by a single type of HRV, and to describe the clinical impact of the outbreak. Study design: Nasopharyngeal swabs were collected from residents with one or more of the following: fever, cough, rhinitis, or congestion. Specimens were interrogated by multiplex PCR using the ResPlex II assay. Samples positive for HRV were then submitted for genotyping by partial sequence analysis of the 5 untranslated (UTR) and viral protein (VP) 1 capsid regions. Results: Of 71 screened, 56 residents were positive for a HRV during an outbreak that lasted 5.5 weeks; 27 healthcare workers also had respiratory symptoms. Three residents were transferred to hospital and 2 died. Seven units in two wings of the LTCH were affected, resulting in 3152.5 resident unit closure days. Three different HRV genotypes were identified, although HRV-A1 dominated. Conclusions: This large outbreak of HRVs among residents and healthcare workers in a LTCH was associated with substantial resident and staff morbidity as well as significant unit closures. Multiple types of HRV were implicated but an HRV-A1 type dominated, warranting further investigation into viral determinants for virulence and transmission.

A:
Co-circulation of multiple genotypes of human rhinovirus during a large outbreak of respiratory illness in a veterans' long-term care home
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