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Articles 1 - 4 of 4
Full-Text Articles in Biochemistry, Biophysics, and Structural Biology
Awegnn: Auto-Parametrized Weighted Element-Specific Graph Neural Networks For Molecules., Timothy Szocinski, Duc Duy Nguyen, Guo-Wei Wei
Awegnn: Auto-Parametrized Weighted Element-Specific Graph Neural Networks For Molecules., Timothy Szocinski, Duc Duy Nguyen, Guo-Wei Wei
Mathematics Faculty Publications
While automated feature extraction has had tremendous success in many deep learning algorithms for image analysis and natural language processing, it does not work well for data involving complex internal structures, such as molecules. Data representations via advanced mathematics, including algebraic topology, differential geometry, and graph theory, have demonstrated superiority in a variety of biomolecular applications, however, their performance is often dependent on manual parametrization. This work introduces the auto-parametrized weighted element-specific graph neural network, dubbed AweGNN, to overcome the obstacle of this tedious parametrization process while also being a suitable technique for automated feature extraction on these internally complex …
Functional Role Of The N-Terminal Domain In Connexin 46/50 By In Silico Mutagenesis And Molecular Dynamics Simulation, Umair Khan
University Honors Theses
Connexins form intercellular channels known as gap junctions that facilitate diverse physiological roles, from long-range electrical and chemical coupling to nutrient exchange. Recent structural studies on Cx46 and Cx50 have defined a novel and stable open state and implicated the amino-terminal (NT) domain as a major contributor to functional differences between connexin isoforms. This thesis presents two studies which use molecular dynamics simulations with these new structures to provide mechanistic insight into the function and behavior of the NTH in Cx46 and Cx50. In the first, residues in the NTH that differ between Cx46 and Cx50 are swapped between the …
Algebraic Graph-Assisted Bidirectional Transformers For Molecular Property Prediction, Dong Chen, Kaifu Gao, Duc Duy Nguyen, Xin Chen, Yi Jiang, Guo-Wei Wei, Feng Pan
Algebraic Graph-Assisted Bidirectional Transformers For Molecular Property Prediction, Dong Chen, Kaifu Gao, Duc Duy Nguyen, Xin Chen, Yi Jiang, Guo-Wei Wei, Feng Pan
Mathematics Faculty Publications
The ability of molecular property prediction is of great significance to drug discovery, human health, and environmental protection. Despite considerable efforts, quantitative prediction of various molecular properties remains a challenge. Although some machine learning models, such as bidirectional encoder from transformer, can incorporate massive unlabeled molecular data into molecular representations via a self-supervised learning strategy, it neglects three-dimensional (3D) stereochemical information. Algebraic graph, specifically, element-specific multiscale weighted colored algebraic graph, embeds complementary 3D molecular information into graph invariants. We propose an algebraic graph-assisted bidirectional transformer (AGBT) framework by fusing representations generated by algebraic graph and bidirectional transformer, as well as …
Modeling The Bidirectional Glutamine/ Ammonium Conversion Between Cancer Cells And Cancer-Associated Fibroblasts, Peter Hinow, Gabriella Pinter, Wei Yan, Shizhen Emily Wang
Modeling The Bidirectional Glutamine/ Ammonium Conversion Between Cancer Cells And Cancer-Associated Fibroblasts, Peter Hinow, Gabriella Pinter, Wei Yan, Shizhen Emily Wang
Mathematical Sciences Faculty Articles
Like in an ecosystem, cancer and other cells residing in the tumor microenvironment engage in various modes of interactions to buffer the negative effects of environmental changes. One such change is the consumption of common nutrients (such as glutamine/Gln) and the consequent accumulation of toxic metabolic byproducts (such as ammonium/NH4). Ammonium is a waste product of cellular metabolism whose accumulation causes cell stress. In tumors, it is known that it can be recycled into nutrients by cancer associated fibroblasts (CAFs). Here we present monoculture and coculture growth of cancer cells and CAFs on different substrates: glutamine and ammonium. …