Results 81 to 90 of about 11,198,889 (292)
Apache Mahout's k-Means vs Fuzzy k-Means Performance Evaluation [PDF]
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Xhafa Xhafa, Fatos +3 more
openaire +2 more sources
Fluorescent probes allow dynamic visualization of phosphoinositides in living cells (left), whereas mass spectrometry provides high‐sensitivity, isomer‐resolved quantitation (right). Their synergistic use captures complementary aspects of lipid signaling. This review illustrates how these approaches reveal the spatiotemporal regulation and quantitative
Hiroaki Kajiho +3 more
wiley +1 more source
Comparison of the dissolved oxygen content forecasting values obtained by SC-K-means-RBF and other methods.
Qianqian Cheng (4872292) +4 more
core +1 more source
Protein pyrophosphorylation by inositol pyrophosphates — detection, function, and regulation
Protein pyrophosphorylation is an unusual signaling mechanism that was discovered two decades ago. It can be driven by inositol pyrophosphate messengers and influences various cellular processes. Herein, we summarize the research progress and challenges of this field, covering pathways found to be regulated by this posttranslational modification as ...
Sarah Lampe +3 more
wiley +1 more source
Equitable distribution of educational resources is an important prerequisite to ensure that all communities benefit from human resource development. Access to education through the availability of schools and teachers at every level, plays a role in ...
Hendrik Subaekti +3 more
doaj +1 more source
The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li +2 more
wiley +1 more source
A Comparative Study of K-means Clustering Algorithms Using Euclidean and Manhattan Distance for Climate Data. [PDF]
The K-means clustering algorithms (Random, K-means++, Canopy, and Farthest First) are unsupervised machine learning techniques designed to group data points based on their similarities. The study examined the effects of clustering algorithms and distance
Bakhshan Hamad
doaj +1 more source
We reconstituted Synechocystis glycogen synthesis in vitro from purified enzymes and showed that two GlgA isoenzymes produce glycogen with different architectures: GlgA1 yields denser, highly branched glycogen, whereas GlgA2 synthesizes longer, less‐branched chains.
Kenric Lee +3 more
wiley +1 more source
Color image segmentation using a spatial k-means clustering algorithm [PDF]
This paper details the implementation of a new adaptive technique for color-texture segmentation that is a generalization of the standard K-Means algorithm. The standard K-Means algorithm produces accurate segmentation results only when applied to images
Ilea, Dana E., Whelan, Paul F.
core
K-means clustering of differentially expressed genes changing over time (DEGots) from E6.5 to E17.5. The 5405 DEGots are clustered by K-means algorithm. n: number of genes in each cluster.
Joris A. van der Post (5775086) +5 more
core +1 more source

