Contextual Motifs: Increasing the Utility of Motifs using Contextual Data

Motifs are a powerful tool for analyzing physiological waveform data. Standard motif methods, however, ignore important contextual information (e.g., what the patient was doing at the time the data were collected). We hypothesize that these additional contextual data could increase the utility of motifs. Thus, we propose an extension to motifs, contextual motifs, that incorporates context. Recognizing that, oftentimes, context may be unobserved or unavailable, we focus on methods to jointly infer motifs and context. Applied to both simulated and real physiological data, our proposed approach improves upon existing motif methods in terms of the discriminative utility of the discovered motifs. In particular, we discovered contextual motifs in continuous glucose monitor (CGM) data collected from patients with type 1 diabetes. Compared to their contextless counterparts, these contextual motifs led to better predictions of hypo- and hyperglycemic events. Our results suggest that even when inferred, context is useful in both a long- and short-term prediction horizon when processing and interpreting physiological waveform data.Comment: 10 pages, 7 figures, accepted for oral presentation at KDD '1

Motivated proteins: a web application for studying small three-dimensional protein motifs

<b>BACKGROUND:</b> Small loop-shaped motifs are common constituents of the three-dimensional structure of proteins. Typically they comprise between three and seven amino acid residues, and are defined by a combination of dihedral angles and hydrogen bonding partners. The most abundant of these are alphabeta-motifs, asx-motifs, asx-turns, beta-bulges, beta-bulge loops, beta-turns, nests, niches, Schellmann loops, ST-motifs, ST-staples and ST-turns.We have constructed a database of such motifs from a range of high-quality protein structures and built a web application as a visual interface to this. <b>DESCRIPTION:</b> The web application, Motivated Proteins, provides access to these 12 motifs (with 48 sub-categories) in a database of over 400 representative proteins. Queries can be made for specific categories or sub-categories of motif, motifs in the vicinity of ligands, motifs which include part of an enzyme active site, overlapping motifs, or motifs which include a particular amino acid sequence. Individual proteins can be specified, or, where appropriate, motifs for all proteins listed. The results of queries are presented in textual form as an (X)HTML table, and may be saved as parsable plain text or XML. Motifs can be viewed and manipulated either individually or in the context of the protein in the Jmol applet structural viewer. Cartoons of the motifs imposed on a linear representation of protein secondary structure are also provided. Summary information for the motifs is available, as are histograms of amino acid distribution, and graphs of dihedral angles at individual positions in the motifs. <b>CONCLUSION:</b> Motivated Proteins is a publicly and freely accessible web application that enables protein scientists to study small three-dimensional motifs without requiring knowledge of either Structured Query Language or the underlying database schem

Digital Motif Design Inspired By Paksi Naga Liman

Nowadays the use of motifs has been widely used in all aspects of life, especially in fabrics. Looking at current technological developments, pattern design techniques can easily be done digitally. In Indonesia, there have been innovations in motif processing sofware, namely JBatik. According to Hariardi and Lukman (2013) JBatik Is a software that is builds using Java Programming with GUI and user friendliness for designers/ artists. By using JBatik, batik or motif design with fractal concept can be made easily. The methods used to collect data this study are in the form of literature studies about motifs and development of patterns, interviews with Batik Fractal Chief Designer Officers (CDO) and observations of vector and JBatik sofware to create motifs and compositions. This study also carried out experimental methods in a quantitative way in the form of formula variables used in making compositions with JBatik’s Lsystem and qualitative compositions in designing visual motifs and compositions. This study aims to combine the potential of vector-based and fractal-based software to process variations of motifs and fractal formulas to make pattern compositions that have efficiency and diverse visualization from the inspiration of Paksi Naga Liman which is a chariot from Keraton Kesepuhan Cirebon. Keywords Digital Motifs, JBatik, Paksi Naga Liman

Motifs in Temporal Networks

Networks are a fundamental tool for modeling complex systems in a variety of domains including social and communication networks as well as biology and neuroscience. Small subgraph patterns in networks, called network motifs, are crucial to understanding the structure and function of these systems. However, the role of network motifs in temporal networks, which contain many timestamped links between the nodes, is not yet well understood. Here we develop a notion of a temporal network motif as an elementary unit of temporal networks and provide a general methodology for counting such motifs. We define temporal network motifs as induced subgraphs on sequences of temporal edges, design fast algorithms for counting temporal motifs, and prove their runtime complexity. Our fast algorithms achieve up to 56.5x speedup compared to a baseline method. Furthermore, we use our algorithms to count temporal motifs in a variety of networks. Results show that networks from different domains have significantly different motif counts, whereas networks from the same domain tend to have similar motif counts. We also find that different motifs occur at different time scales, which provides further insights into structure and function of temporal networks

Composite structural motifs of binding sites for delineating biological functions of proteins

Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs which represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures.Comment: 34 pages, 7 figure

Pure motives with representable Chow groups

Let $k$ be an algebraically closed field. We show using Kahn's and Sujatha's theory of birational motives that a Chow motive over $k$ whose Chow groups are all representable belongs to the full and thick subcategory of motives generated by the twisted motives of curves. -- Motifs purs dont les groupes de Chow sont repr\'esentables. Soit $k$ un corps alg\'ebriquement clos. Nous prouvons, en nous servant de la th\'eorie des motifs birationnels d\'evelopp\'ee par Kahn et Sujatha, qu'un motif de Chow d\'efini sur $k$ dont les groupes de Chow sont tous repr\'esentables appartient \`a la sous-cat\'egorie pleine et \'epaisse des motifs engendr\'ee par les motifs de courbes tordus.Comment: 7 page