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Abstract

Abstract. The investigation of relations between protein tertiary structure and amino acid sequence is a topic of tremendous importance in molecular biology. The automated discovery of recurrent patterns of structure and sequence is an essential part of this investigation. These patterns, known as protein motifs, are abstractions of fragments drawn from proteins of known sequence and tertiary structure. This paper has two objectives. The first is to introduce and define protein motifs, and provide a survey of previous research on protein motif discovery. The second is to present and apply a novel approach to protein motif representation and discovery, which is based on a spatial description logic and the symbolic machine learning paradigm of structured concept formation. A large database of protein fragments is processed using this approach, and several interesting and significant protein motifs are discovered.

Three Reconstructions of ‘Effectiveness’: Some Implications for State Continuity and Sea-level Rise

“…The absence of legal protections for such individuals is both crucial and exacerbated by the unique context of sea-level rise. 171 International law currently possesses no formal protections for individuals displaced across borders due to climate change. 172 In particular, according to the 'dominant view' of the Refugee Convention, 173 populations forced into migration due to climate change do not qualify for refugee status independently from other triggering factors.…”