Results 91 to 100 of about 3,134 (144)
Description of unilateral kidney embolism and contralateral nephrectomy as a less invasive remnant kidney model in cats; a proof-of-concept study. [PDF]
Animal Model Exp MedSchmiedt CW +7 more
europepmc +1 more source
The Flipped Classroom in Medical Education: Systematic Review and Meta-Analysis.
J Med Internet ResSpaic D +14 more
europepmc +1 more source
Some of the next articles are maybe not open access.
Markov models — hidden Markov models
Nature Methods, 2019“Everything we see hides another thing, we always want to see what is hidden by what we see” — Rene ...
Jasleen K. Grewal +2 more
openaire +1 more source
Nature Methods, 2019
You can look back there to explain things, but the explanation disappears. You’ll never find it there. Things are not explained by the past. They’re explained by what happens now.
Jasleen K. Grewal +2 more
openaire +1 more source
You can look back there to explain things, but the explanation disappears. You’ll never find it there. Things are not explained by the past. They’re explained by what happens now.
Jasleen K. Grewal +2 more
openaire +1 more source
2014
This section reviews the relation between the continuous dynamics of a molecular system in thermal equilibrium and the kinetics given by a Markov State Model (MSM). We will introduce the dynamical propagator, an error-less, alternative description of the continuous dynamics, and show how MSMs result from its discretization.
Marco, Sarich +2 more
openaire +2 more sources
This section reviews the relation between the continuous dynamics of a molecular system in thermal equilibrium and the kinetics given by a Markov State Model (MSM). We will introduce the dynamical propagator, an error-less, alternative description of the continuous dynamics, and show how MSMs result from its discretization.
Marco, Sarich +2 more
openaire +2 more sources
Current Opinion in Structural Biology, 1996
'Profiles' of protein structures and sequence alignments can detect subtle homologies. Profile analysis has been put on firmer mathematical ground by the introduction of hidden Markov model (HMM) methods. During the past year, applications of these powerful new HMM-based profiles have begun to appear in the fields of protein-structure prediction and ...
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'Profiles' of protein structures and sequence alignments can detect subtle homologies. Profile analysis has been put on firmer mathematical ground by the introduction of hidden Markov model (HMM) methods. During the past year, applications of these powerful new HMM-based profiles have begun to appear in the fields of protein-structure prediction and ...
openaire +2 more sources
Computer Graphics and Image Processing, 1980
Publisher Summary This chapter reviews the Markov Mesh models as originally given in the works of Abend, Harley, and Kanal. It also presents some inputs on some related references and developments of Markov Random Fields (MRF) models. The Markov Mesh models presented in the works of these authors sought to incorporate spatial dependence in reducing ...
openaire +1 more source
Publisher Summary This chapter reviews the Markov Mesh models as originally given in the works of Abend, Harley, and Kanal. It also presents some inputs on some related references and developments of Markov Random Fields (MRF) models. The Markov Mesh models presented in the works of these authors sought to incorporate spatial dependence in reducing ...
openaire +1 more source
Canadian Journal of Statistics, 1975
AbstractFor the general linear model Y = X$sZ + e in which e has a singular dispersion matrix $sG2A, $sG > 0, where A is n x n and singular, Mitra [2] considers the problem of testing F$sZ, where F is a known q x q matrix and claims that the sum of squares (SS) due to hypothesis is not distributed (as a x2 variate with degrees of freedom (d.
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AbstractFor the general linear model Y = X$sZ + e in which e has a singular dispersion matrix $sG2A, $sG > 0, where A is n x n and singular, Mitra [2] considers the problem of testing F$sZ, where F is a known q x q matrix and claims that the sum of squares (SS) due to hypothesis is not distributed (as a x2 variate with degrees of freedom (d.
openaire +2 more sources