multimodal representations, indexing, unexpectedness and proteins
Complex systems, such as proteins, are inherently difficult to describe, analyse and interpret. A multimodal methodology which utilizes various diverse representations is needed to further our understanding of such intrinsically multifaceted systems. This paper presents a multimodal system designed to describe and interpret the content of the Protein Data Bank, a repository which contains tens of thousands of known proteins. We describe how complimentary modalities based on the amino acid sequence, the protein's backbone (or topology) and the envelope (the outer shape), are used when furthering our understanding of proteins' functionalities, behaviours and interactions. We illustrate our methodology against the human haemoglobin and show that the interplay between modalities allows our system to find unexpected, complimentary results with different domains of validity.
multimodal indexing unexpectedness protein amino acid sequences topology shape retrieval 3d