Plurigon: three dimensional visualization and classification of high-dimensionality data

Abstract

High-dimensionality data is rapidly becoming the norm for biomedical sciences and many other analytical disciplines. Not only is the collection and processing time for such data becoming problematic, but it has become increasingly difficult to form a comprehensive appreciation of high-dimensionality data. Though data analysis methods for coping with multivariate data are well-documented in technical fields such as computer science, little effort is currently being expended to condense data vectors that exist beyond the realm of physical space into an easily interpretable and aesthetic form. To address this important need, we have developed Plurigon, a data visualization and classification tool for the integration of high-dimensionality visualization algorithms with a user-friendly, interactive graphical interface. Unlike existing data visualization methods, which are focused on an ensemble of data points, Plurigon places a strong emphasis upon the visualization of a single data point and its determining characteristics. Multivariate data vectors are represented in the form of a deformed sphere with a distinct topology of hills, valleys, plateaus, peaks, and crevices. The gestalt structure of the resultant Plurigon object generates an easily-appreciable model. User interaction with the Plurigon is extensive; zoom, rotation, axial and vector display, feature extraction, and anaglyph stereoscopy are currently supported. With Plurigon and its ability to analyze high-complexity data, we hope to see a unification of biomedical and computational sciences as well as practical applications in a wide array of scientific disciplines. Increased accessibility to the analysis of high-dimensionality data may increase the number of new discoveries and breakthroughs, ranging from drug screening to disease diagnosis to medical literature mining.

GIT2 Acts as a Systems-Level Coordinator of Neurometabolic Activity and Pathophysiological Aging

“…Intensively complex, multidimensional events such as whole somatic aging are likely to be coordinated by a series of differential protein hierarchies, in which lower-dimensionality protein functions, e.g., simple mitogen-activated protein kinase (MAPK) cascades are orchestrated and connected to other linear pathways by master-controlling “keystone” or “hub” proteins ( 13 ). Experimental research into the potential molecular interactions that regulate aging across an organisms life span quickly engenders signaling complexity issues comparable to the mathematical difficulties of optimally solving NP-hard (Non-deterministic Polynomial-time hard) or NP-complete calculations ( 112 , 113 ). Therefore, a more pragmatic approach to the investigation of hyper complex signaling architectures, both for mechanistic knowledge and for eventual therapeutic manipulation of highly complex systems, is to identify the central coordinators of these complex systems.…”

Delineation of a Conserved Arrestin-Biased Signaling Repertoire In Vivo

“…Thus, we assessed indices indicative of the overall data structure, i.e., the coordinates of its ultimate center of mass converted from spherical coordinates to Cartesian coordinates r, q, and h (see Supplemental Material), as well as surface features such as deformation variability, i.e., range and number of surface deformation magnitudes. The extraction of these two feature types gives both a holistic structural analysis that integrates data from all the respective data points linked together, and an appreciation of differential surface topologies representing smaller scale transcriptomic features (Watts and Strogatz, 1998;Martin et al, 2013). We found that Omnimorph structures created from hPTH(1-34) and bPTH(7-34) data sets possessed significant differences with respect to both their holistic global structure (i.e., their center of mass location; specifically, the Cartesian r transformation) and their degree of surface structure variability [i.e., bPTH(7-34) data sets generated structures with larger numbers of stronger surface deformations than hPTH(1-34)] (Fig.…”

β-Arrestin Based Receptor Signaling Paradigms: Potential Therapeutic Targets for Complex Age-Related Disorders

“…Proteins being targeted for drug development are amyloid β, γ-secretase and the amyloid β precursor protein (APP). The aberrant processing of these proteins has been identified as a hallmark of AD development ( Martin et al, 2013 ; Thathiah et al, 2013 ; Zhang et al, 2017 ).…”

“…Further investigating this interaction between β-arrestin2 and APH1A, the tri-cyclic antidepressant amitriptyline (Elavil ® ) has previously shown to cause strongly neurotrophic pharmacological activities, and is thus a possible treatment of neurodegenerative disorders such as AD. Acute cellular treatment of human neurons showed alteration in the physical interaction between the neurotrophic tyrosine kinase receptor 2 (NTRK2), and APP, and APH1A and β-arrestin2, suggesting that changes in this multi-protein complex may be associated with the beneficial therapeutic actions of amitriptyline ( Martin et al, 2013 ).…”