Results 41 to 50 of about 74,247 (264)
Structural insights and therapeutic targets in Acinetobacter baumannii capsule biosynthesis
Hypervirulent KL49 A. baumannii's capsular polysaccharide contains the nonulosonic acid 8‐epi‐Leg5,7Ac2, synthesized by epimerization via ElaA, ElaB, and ElaC. Crystal structures of ElaA, ElaB, and ElaC reveal their role in CMP‐Leg5,7Ac2 synthesis and regioselective C8 epimerization.
Woo Cheol Lee +7 more
wiley +1 more source
Communication-Efficient Distributed Learning for High-Dimensional Support Vector Machines
Distributed learning has received increasing attention in recent years and is a special need for the era of big data. For a support vector machine (SVM), a powerful binary classification tool, we proposed a novel efficient distributed sparse learning ...
Xingcai Zhou, Hao Shen
doaj +1 more source
Conserved binding mode but diverse interfaces of MreC‐PBP2 interactions
The crystal structure of abMreC reveals a conserved two β‐barrel architecture and provides structural insights into its role within the bacterial elongasome. The abMreC–abPBP2 complex model identifies the molecular basis of MreC‐mediated PBP2 recognition, contributing to the regulation of peptidoglycan synthesis.
Hyunseok Jang +4 more
wiley +1 more source
Bird Species Recognition Using Support Vector Machines
Automatic identification of bird species by their vocalization is studied in this paper. Bird sounds are represented with two different parametric representations: (i) the mel-cepstrum parameters and (ii) a set of low-level signal parameters, both of ...
Seppo Fagerlund
doaj +1 more source
CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3
PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh +12 more
wiley +1 more source
Modelling Proteolytic Enzymes With Support Vector Machines
The strong activity felt in proteomics during the last decade created huge amounts of data, for which the knowledge is limited. Retrieving information from these proteins is the next step. For that, computational techniques are indispensable.
Morgado Lionel +3 more
doaj +1 more source
Mean-Variance optimal portfolio selection integrated with support vector and fuzzy support vector machines [PDF]
This study introduces a novel approach integrating a support vector machine (SVM) with an optimal portfolio construction model. Leveraging the Radial Basis Function (RBF) kernel, the SVM identifies assets with higher growth potential.
Simrandeep Kaur +2 more
doaj +1 more source
Many patients with urothelial cancer do not benefit from treatment with pembrolizumab, while at risk of severe side effects. Changes in the levels of circulating tumor DNA early during treatment, measured by a simple and affordable assay that can be easily implemented in the clinic, can be used as a prognostic tool to identify these patients.
Youssra Salhi +14 more
wiley +1 more source
MITF maintains genome stability in nonmelanocyte lineages
MITF is essential for melanocyte survival and acts as an oncogene in 10%–20% of melanomas. We show that MITF depletion causes genome instability in nonmelanocytic cells, leading to LATS2‐mediated P53 activation, cell cycle arrest, and apoptosis. This study highlights the role of MITF as a genome maintenance factor beyond the melanocyte lineage. Created
Drifa H. Gudmundsdottir +13 more
wiley +1 more source
Support vector machines for TEC seismo-ionospheric anomalies detection [PDF]
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

