Results 151 to 160 of about 13,094,494 (259)
Degradation mechanism of the von Willebrand factor A2 domain by nattokinase
FEBS Letters, EarlyView.Nattokinase, a natto‐derived protease, exhibits potent antithrombotic effects. This study demonstrates that nattokinase directly cleaves the von Willebrand factor (vWF) A2 domain in vitro. Unlike the native regulator ADAMTS13, nattokinase degrades folded vWF independently of shear stress.
Ryuichi Hyakumoto +3 more
wiley +1 more source
A review of unsupervised k-value selection techniques in clustering algorithms
Journal of Industrial Engineering and ManagementPurpose: Automatic grouping of data according to certain characteristics is made possible by clustering algorithms, which makes them an essential tool when working with large datasets. However, although they are unsupervised tools, they generally require
Ana Pegado-Bardayo +3 more
doaj +1 more source
FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
FEBS Letters, EarlyView.Proteostasis and the gut microbiota play a key role in shaping host physiology. Microbiota‐derived metabolites, vitamins, and RNA modulate host proteostasis. Findings from model systems, including C. elegans, indicate microbes can either stabilize or disrupt host proteostasis.
Abhishek Anil Dubey, Maria Ermolaeva
wiley +1 more source
MODIFIKASI K-MEANS BERBASIS ORDERED WEIGHTED AVERAGING (OWA) UNTUK KASUS KLASTERING
Agrointek, 2016 K-means clustering method based on Ordered Weighted Averaging (OWA) was developed by Cheng et al (2009) to resolve problem in classification using integrating k-means clustering and OWA.
Millatul Ulya Millatul Ulya
doaj
Face detection based on K-medoids clustering and associated with convolutional neural networks
HeliyonOver the last several years, the COVID-19 epidemic has spread over the globe. People have become used to the novel standard, which involves working from home, chatting online, and keeping oneself clean, to stop the spread of COVID-19.
Potharla Ramadevi, Raja Das
doaj +1 more source
, 2014 One of techniques popular inData Mining is clustering. Defenition clustering in scientific from data miningis some of data or objectsin one group or clusters into cluster so each cluster will containthedataas closely aspossibleanddifferent objects in ...
Nainggolan, Rena
core
Unsupervised classification of epileptic EEG signals with multi scale K-means algorithm
, 2013 Most epileptic EEG classification algorithms are supervised and require large training data sets, which hinders its use in real time applications. This paper proposes an unsupervised multi-scale K-means (MSK-means) algorithm to distinguish epileptic EEG ...
Zhu, Guohun +10 more
core +1 more source
From mice to humans—divergent strategies for intestinal homeostasis and regeneration
FEBS Letters, EarlyView.Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa +2 more
wiley +1 more source
Intrusion detection system using hybird gsa-k-means [PDF]
, 2013 Security is an important aspect in our daily life. Intrusion Detection Systems (IDS) are developed to be the defense against security threats. Current signature based IDS like firewalls and antiviruses, which rely on labeled training data, generally ...
Aslahi Shahri, Bibi Masoomeh
core