Results 151 to 160 of about 11,198,889 (292)
Structural insights and therapeutic targets in Acinetobacter baumannii capsule biosynthesis
FEBS Letters, EarlyView.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
, 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
A divisive hierarchical k-means based algorithm for image segmentation
, 2010 In this paper we present a divisive hierarchical method for the analysis and segmentation of visual images. The proposed method is based on the use of the k-means method embedded in a recursive algorithm to obtain a clustering at each node of the ...
Gómez González, Daniel +2 more
core +1 more source
FEBS Letters, EarlyView.Inositol pyrophosphates are energy‐rich signaling molecules that perform critical functions in cells. Three different families of phosphatases hydrolyze the β phosphate of the inositol pyrophosphate molecules: two have narrow specificities and one is promiscuous.
Ronda J. Rolfes
wiley +1 more source
A study on learning-augmented k-means clustering
reservedClustering is a practical approach for extracting meaningful information from unstructured data. With the exponential growth of data, it is essential to develop efficient methods for computing clusters.
PEPAJ, MARIA TERESA
core
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
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
Research on Site Selection and Capacity Determination of Electric Vehicle Public Charging Stations by Integrating K-Means++ and Improved RODDPSO [PDF]
RadioengineeringTo address the suboptimal spatial distribution and low comprehensive utilization of existing electric vehicle (EV) public charging infrastructure, this study proposes an innovative charging station placement and capacity determination methodology ...
B. Huang +5 more
doaj
Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Quantum k-Means Clustering Using Hadamard-Test-Based Similarity Estimation
ComputersRecently, the volume of the generated data has increased significantly, leading to the need for computational techniques capable of handling such data efficiently.
Mohammadhadi Alaeiyan +2 more
doaj +1 more source