Results 51 to 60 of about 1,011,171 (338)
Vacuolar transport and function of Saccharomyces cerevisiae sterol ester hydrolase Tgl1
FEBS Letters, EarlyView.Tgl1, one of yeast sterol ester hydrolases, had been found on the lipid droplets where sterol esters are mainly stored. This study revealed that Tgl1 is transported into the vacuole depending on the ESCRT‐I–III complex, and that it exhibits intra‐vacuolar sterol ester hydrolase activity.
Takumi Nakatsuji +5 more
wiley +1 more source
A fault diagnosis method of rolling bearing
Gong-kuang zidonghua, 2014 For parameter optimization of support vector machine in fault diagnosis method of rolling bearing based on support vector machine, an improved fruit fly optimization algorithm was proposed which took accuracy rate of pattern classification as taste ...
DONG Jianping, YANG Cheng, LU Xiaoli
doaj +1 more source
Molecular Oncology, EarlyView.CDK11 inhibition stabilises the tumour suppressor p53 and triggers the production of an alternative p21WAF1 splice variant p21L, through the inactivation of the spliceosomal protein SF3B1. Unlike the canonical p21WAF1 protein, p21L is localised in the cytoplasm and has reduced cell cycle‐blocking activity.
Radovan Krejcir +12 more
wiley +1 more source
A novel deformation forecasting method utilizing comprehensive observation data
Advances in Mechanical Engineering, 2018 Mine disasters often happen unpredictably and it is necessary to find an effective deformation forecasting method. A model between deformation data and the factors data that affected deformation is built in this study.
Sunwen Du, Yao Li
doaj +1 more source
Hyper-parameter Tuning for Quantum Support Vector Machine
Advances in Electrical and Computer Engineering, 2022 In recent years, the positive effect of quantum techniques on machine learning methods have been studied. Especially in training big data, quantum computing is beneficial in terms of speed.
DEMIRTAS, F., TANYILDIZI, E.
doaj +1 more source
The Stata Journal: Promoting communications on statistics and Stata, 2016 Support vector machines are statistical- and machine-learning techniques with the primary goal of prediction. They can be applied to continuous, binary, and categorical outcomes analogous to Gaussian, logistic, and multinomial regression. We introduce a new command for this purpose, svmachines.
Nick Guenther, Matthias Schonlau
openaire +1 more source
, 2017 We generalize a support vector machine to a support spinor machine by using the mathematical structure of wedge product over vector machine in order to extend field from vector field to spinor field.
Bartoš, Erik +3 more
core +1 more source
Mean field variational Bayesian inference for support vector machine classification [PDF]
, 2013 A mean field variational Bayes approach to support vector machines (SVMs) using the latent variable representation on Polson & Scott (2012) is presented.
Luts, Jan, Ormerod, John T.
core +2 more sources
Molecular Oncology, EarlyView.We developed and validated a DNA methylation–based biomarker panel to distinguish pleural mesothelioma from other pleural conditions. Using the IMPRESS technology, we translated this panel into a clinically applicable assay. The resulting two classifier models demonstrated excellent performance, achieving high AUC values and strong diagnostic accuracy.
Janah Vandenhoeck +12 more
wiley +1 more source
FEBS Open Bio, EarlyView.The relationship between anabolic and catabolic processes governing lung cancer cell growth is nuanced. We show that ATG4B, an autophagy regulator, is elevated in lung cancer and that high ATG4B is associated with worse patient outcomes. Targeting ATG4B in cells reduces growth, protein synthesis, and mTORC1 activity, demonstrating a new relationship ...
Patrick J. Ryan +6 more
wiley +1 more source