J. Robert Michael, PhD

J. Robert Michael, PhD

Nashville, Tennessee, United States
3K followers 500+ connections

About

A passionate yet patient leader with a people-first mentality and a strong desire to…

Articles by J. Robert

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Experience

  • Roche Graphic
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    Oak Ridge, Tennessee, United States

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    Oak Ridge, Tennessee, United States

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    Memphis, Tennessee, United States

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    Greater Memphis Area

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    Greater Memphis Area

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    Memphis, TN

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Education

  • Middle Tennessee State University (MTSU) Graphic

    Middle Tennessee State University

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    Computational Science with an emphasis in Computational Quantum Physics. Investigation of the dynamic Electron Density and methods related to uncertainty quantification on the related static Electron Density in thermal equilibrium. The methods involve advanced mathematics and High Performance Computing to simulate molecular vibrations and data mine the results to obtain meaningful conclusions about the vibrations of atoms in molecules.

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Licenses & Certifications

Volunteer Experience

  • High Hopes Development Center Graphic

    Photographer

    High Hopes Development Center

    - 2 years 1 month

    Education

    Photography of children and events for both internal and external dissemination of news, updates, and fundraising.

Publications

  • St. Jude Cloud-a Pediatric Cancer Genomic Data Sharing Ecosystem

    Cancer Discovery

    Effective data sharing is key to accelerating research to improve diagnostic precision, treatment efficacy, and long-term survival of pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data sharing ecosystem for accessing, analyzing and visualizing genomic data from >10,000 pediatric cancer patients and long-term survivors, and >800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabytes…

    Effective data sharing is key to accelerating research to improve diagnostic precision, treatment efficacy, and long-term survival of pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data sharing ecosystem for accessing, analyzing and visualizing genomic data from >10,000 pediatric cancer patients and long-term survivors, and >800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabytes are freely available, including 12,104 whole genomes, 7,697 whole exomes and 2,202 transcriptomes. The resource is expanding rapidly with regular data uploads from St. Jude's prospective clinical genomics programs. Three interconnected apps within the ecosystem-Genomics Platform, Pediatric Cancer Knowledgebase and Visualization Community-enable simultaneously performing advanced data analysis in the cloud and enhancing the pediatric cancer knowledgebase. We demonstrate the value of the ecosystem through use cases that classify 135 pediatric cancer subtypes by gene expression profiling and map mutational signatures across 35 pediatric cancer subtypes.

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  • Compositional adaptability in NPM1-SURF6 scaffolding networks enabled by dynamic switching of phase separation mechanisms

    Nature Communications

    The nucleolus, the site for ribosome biogenesis contains hundreds of proteins and several types of RNA. The functions of many non-ribosomal nucleolar proteins are poorly understood, including Surfeit locus protein 6 (SURF6), an essential disordered protein with roles in ribosome biogenesis and cell proliferation. SURF6 co-localizes with Nucleophosmin (NPM1), a highly abundant protein that mediates the liquid-like features of the granular component region of the nucleolus through phase…

    The nucleolus, the site for ribosome biogenesis contains hundreds of proteins and several types of RNA. The functions of many non-ribosomal nucleolar proteins are poorly understood, including Surfeit locus protein 6 (SURF6), an essential disordered protein with roles in ribosome biogenesis and cell proliferation. SURF6 co-localizes with Nucleophosmin (NPM1), a highly abundant protein that mediates the liquid-like features of the granular component region of the nucleolus through phase separation. Here, we show that electrostatically-driven interactions between disordered regions of NPM1 and SURF6 drive liquid-liquid phase separation. We demonstrate that co-existing heterotypic (NPM1-SURF6) and homotypic (NPM1-NPM1) scaffolding interactions within NPM1-SURF6 liquid-phase droplets dynamically and seamlessly interconvert in response to variations in molecular crowding and protein concentrations. We propose a mechanism wherein NPM1-dependent nucleolar scaffolds are modulated by non-ribosomal proteins through active rearrangements of interaction networks that can possibly contribute to the directionality of ribosomal biogenesis within the liquid-like nucleolus.

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  • On the error in the nucleus-centered multipolar expansion of molecular electron density and its topology: A direct-space computational study

    The Journal of Chemical Physics

    The convergence of nucleus-centered multipolar expansion of the quantum-chemical electron density (QC-ED), gradient, and Laplacian is investigated in terms of numerical radial functions derived by projecting stockholder atoms onto real spherical harmonics at each center. The partial sums of this exact one-center expansion are compared with the corresponding Hansen-Coppens pseudoatom (HC-PA) formalism [Hansen, N. K. and Coppens, P., “Testing aspherical atom refinements on small-molecule data…

    The convergence of nucleus-centered multipolar expansion of the quantum-chemical electron density (QC-ED), gradient, and Laplacian is investigated in terms of numerical radial functions derived by projecting stockholder atoms onto real spherical harmonics at each center. The partial sums of this exact one-center expansion are compared with the corresponding Hansen-Coppens pseudoatom (HC-PA) formalism [Hansen, N. K. and Coppens, P., “Testing aspherical atom refinements on small-molecule data sets,” Acta Crystallogr., Sect. A 34, 909–921 (1978)] commonly utilized in experimental electron density studies. It is found that the latter model, due to its inadequate radial part, lacks pointwise convergence and fails to reproduce the local topology of the target QC-ED even at a high-order expansion. The significance of the quantitative agreement often found between HC-PA-based (quadrupolar-level) experimental and extended-basis QC-EDs can thus be challenged.

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  • Computational analysis of thermal-motion effects on the topological properties of the electron density

    Acta Cryst. A

    The distributions of bond topological properties (BTPs) of the electron density upon thermal vibrations of the nuclei are computationally examined to estimate different statistical figures, especially uncertainties, of these properties. The statistical analysis is based on a large ensemble of BTPs of the electron densities for thermally perturbed nuclear geometries of the formamide molecule. Each bond critical point (BCP) is found to follow a normal distribution whose covariance correlates with…

    The distributions of bond topological properties (BTPs) of the electron density upon thermal vibrations of the nuclei are computationally examined to estimate different statistical figures, especially uncertainties, of these properties. The statistical analysis is based on a large ensemble of BTPs of the electron densities for thermally perturbed nuclear geometries of the formamide molecule. Each bond critical point (BCP) is found to follow a normal distribution whose covariance correlates with the displacement amplitudes of the nuclei involved in the bond. The BTPs are found to be markedly affected not only by normal modes of the significant bond-stretching component but also by modes that involve mainly hydrogen-atom displacements. Their probability distribution function can be decently described by Gumbel-type functions of positive (negative) skewness for the bonds formed by non-hydrogen (hydrogen) atoms.

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  • Density- and wavefunction-normalized Cartesian spherical harmonics for l [less-than or equal to] 20

    Acta Cryst. A

    The widely used pseudoatom formalism [Stewart (1976). Acta Cryst. A32, 565– 574; Hansen & Coppens (1978). Acta Cryst. A34, 909–921] in experimental X-ray charge-density studies makes use of real spherical harmonics when describing the angular component of aspherical deformations of the atomic electron density in molecules and crystals. The analytical form of the density- normalized Cartesian spherical harmonic functions for up to l 􏰌 7 and the corresponding normalization coefficients were…

    The widely used pseudoatom formalism [Stewart (1976). Acta Cryst. A32, 565– 574; Hansen & Coppens (1978). Acta Cryst. A34, 909–921] in experimental X-ray charge-density studies makes use of real spherical harmonics when describing the angular component of aspherical deformations of the atomic electron density in molecules and crystals. The analytical form of the density- normalized Cartesian spherical harmonic functions for up to l 􏰌 7 and the corresponding normalization coefficients were reported previously by Paturle & Coppens [Acta Cryst. (1988), A44, 6–7]. It was shown that the analytical form for normalization coefficients is available primarily for l 􏰌 4 [Hansen & Coppens, 1978; Paturle & Coppens, 1988; Coppens (1992). International Tables for Crystallography, Vol. B, Reciprocal space, 1st ed., edited by U. Shmueli, ch. 1.2. Dordrecht: Kluwer Academic Publishers; Coppens (1997). X-ray Charge Densities and Chemical Bonding. New York: Oxford University Press]. Only in very special cases it is possible to derive an analytical representation of the normalization coefficients for 4 < l 􏰌 7 (Paturle & Coppens, 1988). In most cases for l > 4 the density normalization coefficients were calculated numerically to within seven significant figures. In this study we review the literature on the density-normalized spherical harmonics, clarify the existing notations, use the Paturle–Coppens (Paturle & Coppens, 1988) method in the Wolfram Mathematica software to derive the Cartesian spherical harmonics for l 􏰌 20 and determine the density normalization coefficients to 35 significant figures, and computer-generate a Fortran90 code. The article primarily targets researchers who work in the field of experimental X-ray electron density, but may be of some use to all who are interested in Cartesian spherical harmonics.

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  • Validation of convolution approximation to the thermal-average electron density

    Journal of Mathematical Chemistry

    Analytic evaluation of the dynamic (thermally smeared) molecular electron density (ED) is described within the LCAO-MO and harmonic-convolution approximations. The key step is to assign vibration probability density functions (PDFs) to the two-center products of Gaussian basis functions used in quantum chemical models, if the PDFs of the nuclear centers are known. Based on internal modes of vibrations of small molecules it is demonstrated how the convoluted ED relates to the stationary (static)…

    Analytic evaluation of the dynamic (thermally smeared) molecular electron density (ED) is described within the LCAO-MO and harmonic-convolution approximations. The key step is to assign vibration probability density functions (PDFs) to the two-center products of Gaussian basis functions used in quantum chemical models, if the PDFs of the nuclear centers are known. Based on internal modes of vibrations of small molecules it is demonstrated how the convoluted ED relates to the stationary (static) ED, as well as to that of the average over an ensemble of static EDs calculated for near-equilibrium nuclear geometries using clamped Hamiltonians. The overall effect of neglecting correlated nuclear motions on the convoluted ED is also illuminated.

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Courses

  • Abstract Algebra

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  • Adv. Differential Equations I

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  • Adv. Linear Algebra

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  • Algebraic Topology

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  • Combinatorics and Graph Theory

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  • Complex Variables

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  • Computational Chemistry I

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  • Computational Chemistry II

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  • Computational Science

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  • Computer Systems

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  • Data Mining

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  • Mathematical Modeling

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  • Numerical Analysis

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  • Numerical Methods

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  • Parallel Processing

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  • Scientific Computing

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  • Sets and Logic

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  • Topology

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  • Visualization and Databases

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