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Data on whole length myosin binding protein C stabilizes myosin S2 as measured by gravitational force spectroscopy (open access)

Data on whole length myosin binding protein C stabilizes myosin S2 as measured by gravitational force spectroscopy

This article relates to the research article entitled "Whole length myosin binding protein C stabilized myosin subfragment-2 (s2) flexibility as measured by gravitational force spectroscopy" (Singh et al., 2018) [1]. The data exhibited the purified skeletal myosin binding protein (MyBPC) from rabbit back muscle was of slow skeletal type confirmed by chromatography and in unphosphorylated state based on its isoelectric point (pI) by chromatofocussing.
Date: December 4, 2017
Creator: Singh, Rohit R.; Dunn, James W.; Qadan, Motamed M.; Hall, Nakiuda; Wang, Kathy K. & Root, Douglas D.
System: The UNT Digital Library
Agronomic Performance and Lignin Content of HCT Down-Regulated Alfalfa (Medicago sativa L.) (open access)

Agronomic Performance and Lignin Content of HCT Down-Regulated Alfalfa (Medicago sativa L.)

This article evaluates HCT down-regulated alfalfa plants for their forage composition and agronomic performance in the greenhouse and under field conditions.
Date: May 5, 2018
Creator: Bhattarai, Kishor; Rajasekar, Shanmugam; Dixon, R. A. & Monteros, Maria J.
System: The UNT Digital Library
Generalized molecular solvation in non-aqueous solutions by a single parameter implicit solvation scheme (open access)

Generalized molecular solvation in non-aqueous solutions by a single parameter implicit solvation scheme

Article presenting a systematic parametrization protocol for the Self-Consistent Continuum Solvation (SCCS) model resulting in optimized parameters for 67 non-aqueous solvents. The parametrization is based on a collection of ≈6000 experimentally measured partition coefficients, which were collected in the Solv@TUM database presented here. The accuracy of the optimized SCCS model is comparable to the well-known universal continuum solvation model (SMx) family of methods, while relying on only a single fit parameter and thereby largely reducing statistical noise.
Date: August 3, 2018
Creator: Acree, William E. (William Eugene); Hille, Christoph; Ringe, Stefan; Deimel, Martin; Kunkel, Christian; Reuter, Karsten et al.
System: The UNT Digital Library