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Missing values are a major issue in quantitative proteomics analysis. While many methods have been developed for imputing missing values in high-throughput proteomics data, a comparative assessment of imputation accuracy remains inconclusive, mainly because mechanisms contributing to true missing values are complex and existing evaluation methodologies are imperfect. Moreover, few studies have provided an outlook of future methodological development. We first re-evaluate the performance of eight representative methods targeting three typical missing mechanisms. These methods are compared on both simulated and masked missing values embedded within real proteomics datasets, and performance is evaluated using three quantitative measures. We then introduce fused regularization matrix factorization, a low-rank global matrix factorization framework, capable of integrating local similarity derived from additional data types. We also explore a biologically-inspired latent variable modeling strategy—convex analysis of mixtures—for missing value imputation and present preliminary experimental results. While some winners emerged from our comparative assessment, the evaluation is intrinsically imperfect because performance is evaluated indirectly on artificial missing or masked values not authentic missing values. Nevertheless, we show that our fused regularization matrix factorization provides a novel incorporation of external and local information, and the exploratory implementation of convex analysis of mixtures presents a biologically plausible new approach.

A finite-element analysis of the equations governing the large-amplitude, free, flexural oscillations of laminated, anisotropic, rectangular plates is presented. The equations account for transverse shear strains as well as large rotations. Numerical results of nonlinear fundamental frequencies are presented for rectangular plates of both angle-ply and cross-ply constructions. The effects of amplitude, boundary conditions, transverse shear, aspect ratio, orientation of layers, and materials anisotrophy on natural frequencies are investigated. The present finite element results agree with other approximate solutions available in the literature.

A photoinduced iron-catalyzed ipso-nitration of aryl halides with KNO 2 has been developed, in which aryl iodides, bromides, and some of aryl chlorides are feasible. The mechanism investigations show that the in situ formed iron complex by FeSO 4 , KNO 2 , and 1,10-phenanthroline acts as the light-harvesting photocatalyst with a longer lifetime of the excited state, and the reaction undergoes a photoinduced single-electron transfer (SET) process. This work represents an example for the photoinduced iron-catalyzed Ullmann-type couplings.