Discovery and Characterization of Rubrinodin Provide Clues into the Evolution of Lasso Peptides.
Sign Up to like & getrecommendations! Published in 2022 at "Biochemistry"
DOI: 10.1021/acs.biochem.2c00029
Abstract: Lasso peptides are unique natural products that comprise a class of ribosomally synthesized and post-translationally modified peptides. Their defining three-dimensional structure is a lariat knot, in which the C-terminal tail is threaded through a macrolactam… read more here.
Keywords: lasso peptides; lasso; lasso peptide; rubrinodin ... See more keywords
Cell-Free Biosynthesis to Evaluate Lasso Peptide Formation and Enzyme-Substrate Tolerance.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of the American Chemical Society"
DOI: 10.1021/jacs.1c01452
Abstract: Lasso peptides are ribosomally synthesized and post-translationally modified peptide (RiPP) natural products that display a unique lariat-like, threaded conformation. Owing to a locked three-dimensional structure, lasso peptides can be unusually stable toward heat and proteolytic… read more here.
Keywords: lasso peptides; cfb; lasso peptide; cell free ... See more keywords
Interval LASSO regression based extreme learning machine for nonlinear multivariate calibration of near infrared spectroscopic datasets
Sign Up to like & getrecommendations! Published in 2018 at "Analytical Methods"
DOI: 10.1039/c8ay00466h
Abstract: As a nonlinear multivariate calibration method, extreme learning machine (ELM) has recently received increasing attention for its fast learning speed and excellent generalized performance. However, it is implemented normally under the empirical risk minimization scheme,… read more here.
Keywords: based elm; nonlinear multivariate; elm; lasso ... See more keywords
Rational generation of lasso peptides based on biosynthetic gene mutations and site-selective chemical modifications
Sign Up to like & getrecommendations! Published in 2021 at "Chemical Science"
DOI: 10.1039/d1sc02695j
Abstract: Lasso peptides are a unique family of natural products whose structures feature a specific threaded fold, which confers these peptides the resistance to thermal and proteolytic degradation. This stability gives lasso peptides excellent pharmacokinetic properties,… read more here.
Keywords: lasso peptides; site selective; lasso; generation ... See more keywords
Using Lasso and Adaptive Lasso to Identify DIF in Multidimensional 2PL Models.
Sign Up to like & getrecommendations! Published in 2022 at "Multivariate behavioral research"
DOI: 10.1080/00273171.2021.1985950
Abstract: Differential item functioning (DIF) analysis refers to procedures that evaluate whether an item's characteristic differs for different groups of persons after controlling for overall differences in performance. DIF is routinely evaluated as a screening step… read more here.
Keywords: lasso; adaptive lasso; lasso adaptive; regularization methods ... See more keywords
Robust adaptive Lasso for variable selection
Sign Up to like & getrecommendations! Published in 2017 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2015.1019138
Abstract: ABSTRACT The adaptive least absolute shrinkage and selection operator (Lasso) and least absolute deviation (LAD)-Lasso are two attractive shrinkage methods for simultaneous variable selection and regression parameter estimation. While the adaptive Lasso is efficient for… read more here.
Keywords: robust adaptive; adaptive lasso; lad lasso; lasso ... See more keywords
Algorithms for Fitting the Constrained Lasso
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Computational and Graphical Statistics"
DOI: 10.1080/10618600.2018.1473777
Abstract: ABSTRACT We compare alternative computing strategies for solving the constrained lasso problem. As its name suggests, the constrained lasso extends the widely used lasso to handle linear constraints, which allow the user to incorporate prior… read more here.
Keywords: constrained lasso; fitting constrained; algorithms fitting; lasso ... See more keywords
Robust Huber-LASSO for improved prediction of protein, metabolite and gene expression levels relying on individual genotype data
Sign Up to like & getrecommendations! Published in 2021 at "Briefings in Bioinformatics"
DOI: 10.1093/bib/bbaa230
Abstract: Abstract Least absolute shrinkage and selection operator (LASSO) regression is often applied to select the most promising set of single nucleotide polymorphisms (SNPs) associated with a molecular phenotype of interest. While the penalization parameter λ… read more here.
Keywords: protein metabolite; lasso; robust huber; expression ... See more keywords
Hi-LASSO: High-performance python and apache spark packages for feature selection with high-dimensional data
Sign Up to like & getrecommendations! Published in 2022 at "PLOS ONE"
DOI: 10.1101/2022.04.22.489133
Abstract: High-dimensional LASSO (Hi-LASSO) is a powerful feature selection tool for high-dimensional data. Our previous study showed that Hi-LASSO outperformed the other state-of-the-art LASSO methods. However, the substantial cost of bootstrapping and the lack of experiments… read more here.
Keywords: lasso; feature selection; dimensional data; high dimensional ... See more keywords
Beamforming With Small-Spacing Microphone Arrays Using Constrained/Generalized LASSO
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2020.2971790
Abstract: In this letter, we develop an approach to the design of beamformers with small-spacing uniform linear microphone arrays by incorporating sparseness constraints for attenuating scattered interference incident from some pre-specified ranges of directions of arrival.… read more here.
Keywords: microphone arrays; beamforming small; lasso; small spacing ... See more keywords
An Augmented High-Dimensional Graphical Lasso Method to Incorporate Prior Biological Knowledge for Global Network Learning
Sign Up to like & getrecommendations! Published in 2021 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2021.760299
Abstract: Biological networks are often inferred through Gaussian graphical models (GGMs) using gene or protein expression data only. GGMs identify conditional dependence by estimating a precision matrix between genes or proteins. However, conventional GGM approaches often… read more here.
Keywords: lasso; augmented high; method; network ... See more keywords