Results 51 to 60 of about 427,183 (276)
Bayesian Nonlinear Support Vector Machines for Big Data
, 2017 We propose a fast inference method for Bayesian nonlinear support vector machines that leverages stochastic variational inference and inducing points. Our experiments show that the proposed method is faster than competing Bayesian approaches and scales ...
Deutsch, Matthaeus +3 more
core +1 more source
Support Vector Machines for predicting protein structural class
BMC Bioinformatics, 2001 Background We apply a new machine learning method, the so-called Support Vector Machine method, to predict the protein structural class. Support Vector Machine method is performed based on the database derived from SCOP, in which protein domains are ...
Xu Xue-biao +3 more
doaj +1 more source
Semi-supervised learning paradigm analysis for classification of multimodal data
Науковий вісник Ужгородського університету. Серія: Математика і інформатика, 2021 The paper considers machine learning algorithms. The focus is on semi-controlled learning, which seems to be the balance between teaching accuracy with a teacher and the cost of teaching methods without a teacher.
Н. Бойко
doaj +1 more source
Evolutionarily divergent DUF4465 domains have a common vitamin B12‐binding function
FEBS Open Bio, EarlyView.We show that DUF4465 family proteins, widespread across bacteria from gut microbiomes, hydrothermal vents, and soil, share a common vitamin B12‐binding function. These augmented β‐jellyroll proteins bind vitamin B12 via extended loops. Our findings establish sequence‐diverse DUF4465 proteins as a widespread class of B12‐binding proteins, highlighting ...
Charlea Clarke +4 more
wiley +1 more source
Robustness and Regularization of Support Vector Machines [PDF]
, 2008 We consider regularized support vector machines (SVMs) and show that they are precisely equivalent to a new robust optimization formulation. We show that this equivalence of robust optimization and regularization has implications for both algorithms, and
Caramanis, Constantine +2 more
core
Support vector machines for TEC seismo-ionospheric anomalies detection [PDF]
Annales Geophysicae, 2013 Using time series prediction methods, it is possible to pursue the behaviors of earthquake precursors in the future and to announce early warnings when the differences between the predicted value and the observed value exceed the predefined threshold ...
M. Akhoondzadeh
doaj +1 more source
FEBS Open Bio, EarlyView.Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane +11 more
wiley +1 more source
Multiclass latent locally linear support vector machines [PDF]
, 2013 Kernelized Support Vector Machines (SVM) have gained the status of off-the-shelf classifiers, able to deliver state of the art performance on almost any problem.
CAPUTO, BARBARA +2 more
core +1 more source
Transmembrane protein topology prediction using support vector machines
BMC Bioinformatics, 2009 Background Alpha-helical transmembrane (TM) proteins are involved in a wide range of important biological processes such as cell signaling, transport of membrane-impermeable molecules, cell-cell communication, cell recognition and cell adhesion. Many are
Nugent Timothy, Jones David T
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Mass spectrometry based identification of AMP‐O‐Tris generated by Thermococcus onnurineus Cas10
FEBS Open Bio, EarlyView.Isolated Thermococcus onnurineus Cas10 generates the noncanonical ATP‐derived product AMP‐O‐Tris while in Tris‐containing buffer as identified via mass spectrometry, revealing relaxed nucleophile selectivity under isolated conditions. These findings suggest that multiprotein Csm complex assembly restricts Cas10 reactivity toward canonical cyclic ...
Su‐Jin Lee +6 more
wiley +1 more source