منابع مشابه
Article SMO-FU
Smoothened (SMO) is a GPCR-related protein required for the transduction of Hedgehog (HH). The HH gradient leads to graded phosphorylation of SMO, mainly by the PKA and CKI kinases. How thresholds in HH morphogen regulate SMO to promote switch-like transcriptional responses is a central unsolved issue. Using the wing imaginal disc model in Drosophila, we identified novel SMO phosphosites that e...
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AB STRACT: Smoking pa tients show re duc tion of in flam ma tory clin i cal signs that might be as so ci ated with lo cal vasoconstriction and an in creased gingival ep i the lial thick ness. The pur pose of this work was to eval u ate the thick ness of the mar ginal gingival oral ep i the lium in smok ers and non-smok ers, with clin i cally healthy gingivae or with gin gi vi tis. Twenty bi op ...
متن کاملThe Planning-ahead SMO Algorithm
The sequential minimal optimization (SMO) algorithm and variants thereof are the de facto standard method for solving large quadratic programs for support vector machine (SVM) training. In this paper we propose a simple yet powerful modification. The main emphasis is on an algorithm improving the SMO step size by planning-ahead. The theoretical analysis ensures its convergence to the optimum. E...
متن کاملThe Smo/Smo model: hedgehog-induced medulloblastoma with 90% incidence and leptomeningeal spread.
Toward the goal of generating a mouse medulloblastoma model with increased tumor incidence, we developed a homozygous version of our ND2:SmoA1 model. Medulloblastomas form in 94% of homozygous Smo/Smo mice by 2 months of age. Tumor formation is, thus, predictable by age, before the symptomatic appearance of larger lesions. This high incidence and early onset of tumors is ideal for preclinical s...
متن کاملMultiple Kernel Learning and the SMO Algorithm
Our objective is to train p-norm Multiple Kernel Learning (MKL) and, more generally, linear MKL regularised by the Bregman divergence, using the Sequential Minimal Optimization (SMO) algorithm. The SMO algorithm is simple, easy to implement and adapt, and efficiently scales to large problems. As a result, it has gained widespread acceptance and SVMs are routinely trained using SMO in diverse re...
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ژورنال
عنوان ژورنال: Metodički obzori/Methodological Horizons
سال: 2012
ISSN: 1848-8455,1846-1484
DOI: 10.32728/mo.07.2.2012.14