Results 51 to 60 of about 2,646,945 (311)
A Method of Maximum-Likelihood Estimation
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1961 SUMMARY Knowledge of one or more of the parameters in a maximum-likelihood problem sometimes results in a very considerable simplification, the analysis becoming almost trivial. A method of obtaining maximum-likelihood estimates and their asymptotic covariance matrix is given which makes it possible to capitalize on simplifications of ...
openaire +2 more sources
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 +2 more
wiley +1 more source
Estimating a Bounded Normal Mean Relative to Squared Error Loss Function [PDF]
Journal of Sciences, Islamic Republic of Iran, 2011 Let be a random sample from a normal distribution with unknown mean and known variance The usual estimator of the mean, i.e., sample mean is the maximum likelihood estimator which under squared error loss function is minimax and admissible ...
A. Karimnezhad
doaj
Maximum-Likelihood Estimation of Relatedness
Genetics, 2003 Abstract Relatedness between individuals is central to many studies in genetics and population biology. A variety of estimators have been developed to enable molecular marker data to quantify relatedness. Despite this, no effort has been given to characterize the traditional maximum-likelihood estimator in relation to the remainder. This
openaire +2 more sources
FEBS Letters, EarlyView.Ascidian Ciona larvae initially show strong clockwise tail twisting, which is largely corrected during development. However, a small residual twist remains. This study shows that organized helical myofibrils in tail muscles mechanically stabilize this residual asymmetry, preventing complete restoration of bilateral symmetry and revealing how embryos ...
Yuki S. Kogure +3 more
wiley +1 more source
A note on the maximum likelihood estimator in the gamma regression model [PDF]
Opuscula Mathematica, 2009 This paper considers a nonlinear regression model, in which the dependent variable has the gamma distribution. A model is considered in which the shape parameter of the random variable is the sum of continuous and algebraically independent functions. The
Jerzy P. Rydlewski
doaj +1 more source
FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Reconstructing enzyme evolution by protein engineering
FEBS Letters, EarlyView.Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler +2 more
wiley +1 more source
Parametric estimation of P(X > Y) for normal distributions in the context of probabilistic environmental risk assessment [PDF]
PeerJ, 2015 Estimating the risk, P(X > Y), in probabilistic environmental risk assessment of nanoparticles is a problem when confronted by potentially small risks and small sample sizes of the exposure concentration X and/or the effect concentration Y.
Rianne Jacobs +3 more
doaj +2 more sources