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CSSEC: An adaptive approach integrating consensus and specific self-expressive coefficients for multi-omics cancer subtyping.
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Department of Computer Science and Engineering, School of Information Science and Engineering, Yunnan University, Kunming, 650504, Yunnan, China. Electronic address:
Cancer is a complex and heterogeneous disease, and accurate cancer subtyping can significantly improve patient survival rates. The complexity of cancer spans multiple omics levels, and analyzing multi-omics data for cancer subtyping is a focus of considerable attention. However, extracting complementary information from different omics data sources and adaptively integrating them remains a major challenge.
View Article and Find Full Text PDFElucidating the impact of S-adenosylmethionine and histamine binding on N-methyltransferase conformational dynamics: Insights from an in silico study.
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Tianjin Institute of Industrial Biotechnology of Chinese Academy of Sciences, National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China. Electronic address:
S-adenosylmethionine (SAM)-dependent histamine N-methyltransferase (HNMT) is a crucial enzyme involved in histamine methylation, playing an important role in the epigenetic modification of biology. It entails the addition of methyl groups to histamine molecules, thereby regulating gene expression, cellular signal transduction, and other biological processes. Therefore, gaining a profound understanding of the detailed mechanism underlying HNMT-mediated methylation reactions is instrumental in elucidating the role of histamine methylation in biology.
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Unit of Excellence in Computational Molecular Science and Catalysis, and Division of Chemistry, School of Science, University of Phayao, Phayao, 56000, Thailand. Electronic address:
Monomer insertion, leading to the formation of an activated monomer complex, is a critical step in cationic ring-opening polymerization (CROP) of cyclic monomers, such as ε-caprolactone (CL). In this study, Density Functional Theory (DFT) calculations were employed to investigate the structural and electronic properties of four activated complexes at two Zr:B ratios (1:2 and 1:1), where Zr is the cationic zirconocene catalyst, Cp₂ZrMe⁺, and B is the borate cocatalyst, [MeB(CF)] or [B(CF)]. Steric hindrance at the reactive site was analyzed using topographic steric maps, while inter- and intramolecular interactions of the complex systems were examined through the Quantum Theory of Atoms in Molecules (QTAIM) and non-covalent interaction (NCI) analyses.
View Article and Find Full Text PDFO-H/N-H bond dissociation energies in 1,4-hydroquinone, 4-hydroxydiphenylamine, N,N'-diphenyl-1,4-phenylenediamine, and their phenoxyl and aminyl radicals.
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Federal Research Center of Problems of Chemical Physics and Medicinal Chemistry of the Russian Academy of Sciences, 1 Academician Semenov Avenue, 142432, Chernogolovka, Russian Federation.
Gas phase bond dissociation energies (BDE) O-H/N-H in hydroquinone (HQ), 4-aminophenol (AP), 1,4-phenylenediamine (PDA), 4-hydroxydiphenylamine (HDPA), N,N'-diphenyl-1,4-phenylenediamine (DPPDA) as well as in their phenoxyl/aminyl radicals have been determined using a combined technique of quantum chemical calculation. The technique included a series of DFT (PBE1PBE, TPSSTPSS, M06-2X), ab initio (DLPNO-CCSD(T)) methods with valence 3ξ-basis sets, composite methods of Gaussian family (G4) and Weizmann theory with ab initio Brueckner Doubles (W1BD), as well as reference reactions of different levels of structural similarity. W1BD method was used in combination with isodesmic reactions for BDE estimation (kJ∙mol) of compounds with the only aromatic fragment: BDE = 352.
View Article and Find Full Text PDFBayesian Analysis of Exponential Random Graph Models Using Stochastic Gradient Markov Chain Monte Carlo.
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June 2024
Department of Statistics, Purdue University, West Lafayette, IN 47907, USA.
The exponential random graph model (ERGM) is a popular model for social networks, which is known to have an intractable likelihood function. Sampling from the posterior for such a model is a long-standing problem in statistical research. We analyze the performance of the stochastic gradient Langevin dynamics (SGLD) algorithm (also known as noisy Longevin Monte Carlo) in tackling this problem, where the stochastic gradient is calculated via running a short Markov chain (the so-called inner Markov chain in this paper) at each iteration.
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