Results 251 to 260 of about 3,822,020 (321)
RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz +6 more
wiley +1 more source
Metformin mediates mitochondrial quality control in Leber's hereditary optic neuropathy (LHON) fibroblasts carrying mtDNA mutations. At therapeutic levels, metformin activates AMPK signaling to restore mitochondrial dynamics by promoting fusion and restraining fission, while preserving mitochondrial mass, enhancing autophagy/mitophagy and biogenesis ...
Chatnapa Panusatid +3 more
wiley +1 more source
Tandem VHH targeting distinct EGFR epitopes were engineered into a monovalent bispecific antibody (7D12‐EGA1‐Fc) with more potent ADCC without increasing affinity to EGFR. Structural modeling of 7D12‐EGA1‐Fc showed cross‐linking of separate EGFR domains to enhance CD16a engagement on NK cells.
Yuqiang Xu +5 more
wiley +1 more source
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2020
This chapter introduces linear mixed models, which have wide applicability in small area estimation due to their flexibility to combining different types of information and explaining sources of errors. Three of the most used fitting methods are presented under two parametrizations.
Domingo Morales +3 more
openaire +2 more sources
This chapter introduces linear mixed models, which have wide applicability in small area estimation due to their flexibility to combining different types of information and explaining sources of errors. Three of the most used fitting methods are presented under two parametrizations.
Domingo Morales +3 more
openaire +2 more sources
2007
Statistical models provide a framework in which to describe the biological process giving rise to the data of interest. The construction of this model requires balancing adequate representation of the process with simplicity. Experiments involving multiple (correlated) observations per subject do not satisfy the assumption of independence required for ...
Ann L, Oberg, Douglas W, Mahoney
openaire +2 more sources
Statistical models provide a framework in which to describe the biological process giving rise to the data of interest. The construction of this model requires balancing adequate representation of the process with simplicity. Experiments involving multiple (correlated) observations per subject do not satisfy the assumption of independence required for ...
Ann L, Oberg, Douglas W, Mahoney
openaire +2 more sources
2001
Observations often fall into groups or clusters. For example, longitudinal data consist of repeated observations on the same subjects. Hierarchical data sets typically consist of subjects nested in higher level units, such as families or GP practices.
Brian Everitt, Sophia Rabe-Hesketh
openaire +1 more source
Observations often fall into groups or clusters. For example, longitudinal data consist of repeated observations on the same subjects. Hierarchical data sets typically consist of subjects nested in higher level units, such as families or GP practices.
Brian Everitt, Sophia Rabe-Hesketh
openaire +1 more source
2012
In current clinical research repeated measures in a single subject are common. The problem with repeated measures is, that they are more close to one another than unrepeated measures. If this is not taken into account, then data analysis will lose power.
Ton J. Cleophas, Aeilko H. Zwinderman
openaire +1 more source
In current clinical research repeated measures in a single subject are common. The problem with repeated measures is, that they are more close to one another than unrepeated measures. If this is not taken into account, then data analysis will lose power.
Ton J. Cleophas, Aeilko H. Zwinderman
openaire +1 more source
Local Influence in Linear Mixed Models
Biometrics, 1998The linear mixed model has become an important tool in modelling, partially due to the introduction of the SAS procedure MIXED, which made the method widely available to practising statisticians. Its growing popularity calls for data-analytic methods to check the underlying assumptions and robustness. Here, the problem of detecting influential subjects
Lesaffre, Emmanuel, Verbeke, Geert
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2012
Fixed effects and random effects models are introduced with examples. Maximum likelihood (ML), restricted maximum likelihood (REML) and ANOVA methods of estimation of variance components are described, illustrating with the examples of one-way and two-way classification.
openaire +2 more sources
Fixed effects and random effects models are introduced with examples. Maximum likelihood (ML), restricted maximum likelihood (REML) and ANOVA methods of estimation of variance components are described, illustrating with the examples of one-way and two-way classification.
openaire +2 more sources

