Results 91 to 100 of about 2,104,160 (282)

Approximate selective inference via maximum likelihood

, 2020
This article considers a conditional approach to selective inference via approximate maximum likelihood for data described by Gaussian models. There are two important considerations in adopting a post-selection inferential perspective.
Panigrahi, Snigdha, Taylor, Jonathan
core  

Maximum likelihood estimation in log-linear models

, 2012
We study maximum likelihood estimation in log-linear models under conditional Poisson sampling schemes. We derive necessary and sufficient conditions for existence of the maximum likelihood estimator (MLE) of the model parameters and investigate ...
Fienberg, Stephen E., Rinaldo, Alessandro   +1 more
core   +3 more sources

Structural insights into an engineered feruloyl esterase with improved MHET degrading properties

FEBS Letters, EarlyView.
A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa, Konstantinos Makryniotis, Theofani‐Iosifina Sousani, Evangelos Topakas, Vangelis Daskalakis, Maria Dimarogona   +5 more
wiley   +1 more source

A Maximum Entropy Procedure to Solve Likelihood Equations

Entropy, 2019
In this article, we provide initial findings regarding the problem of solving likelihood equations by means of a maximum entropy (ME) approach. Unlike standard procedures that require equating the score function of the maximum likelihood problem at zero,
Antonio Calcagnì, Livio Finos, Gianmarco Altoé, Massimiliano Pastore   +3 more
doaj   +1 more source

Maximum likelihood signature estimation [PDF]

Maximum-likelihood estimates are discussed which are based on an unlabeled sample of observations, of unknown parameters in a mixture of normal distributions. Several successive approximation procedures for obtaining such maximum-likelihood estimates are
Walker, H. F.
core   +1 more source

The Maximum Likelihood Threshold of a Graph [PDF]

, 2015
The maximum likelihood threshold of a graph is the smallest number of data points that guarantees that maximum likelihood estimates exist almost surely in the Gaussian graphical model associated to the graph.
Gross, Elizabeth, Sullivant, Seth
core  

Diluted maximum-likelihood algorithm for quantum tomography

, 2007
We propose a refined iterative likelihood-maximization algorithm for reconstructing a quantum state from a set of tomographic measurements. The algorithm is characterized by a very high convergence rate and features a simple adaptive procedure that ...
A. I. Lvovsky, D. T. Smithey, E. Knill, G. M. D’Ariano, G. T. Herman, Jaroslav Řeháček, Y. Vardi, Z. Hradil, Zdeněk Hradil   +8 more
core   +1 more source

A methionine‐lined active site governs carbocation stabilization and product specificity in a bacterial terpene synthase

FEBS Letters, EarlyView.
This study reveals a unique active site enriched in methionine residues and demonstrates that these residues play a critical role by stabilizing carbocation intermediates through novel sulfur–cation interactions. Structure‐guided mutagenesis further revealed variants with significantly altered product profiles, enhancing pseudopterosin formation. These
Marion Ringel, Carl P. O. Helmer, Shani Zev, Ronja Driller, Emily Buhr, Markus Reinbold, Renana Schwartz, Gabriel Foley, Mikael Boden, Daniel Garbe, Gerhard Schenk, Dan Thomas Major, Bernhard Loll, Thomas Brück   +13 more
wiley   +1 more source

Valosin‐containing protein counteracts ATP‐driven dissolution of FUS condensates through its ATPase activity in vitro

FEBS Letters, EarlyView.
Biomolecular condensates formed by fused in sarcoma (FUS) are dissolved by high ATP concentrations yet persist in cells. Using a reconstituted system, we demonstrate that valosin‐containing protein (VCP), an AAA+ ATPase, counteracts ATP‐driven dissolution of FUS condensates through its D2 ATPase activity.
Hitomi Kimura, Shin‐ichi Tate, Kyota Yasuda   +2 more
wiley   +1 more source

Copula Approximate Bayesian Computation Using Distribution Random Forests

Stats
Ongoing modern computational advancements continue to make it easier to collect increasingly large and complex datasets, which can often only be realistically analyzed using models defined by intractable likelihood functions.
George Karabatsos
doaj   +1 more source