Results 111 to 120 of about 1,835,018 (264)

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, Shinya Sugimoto, Toshiro Sato   +2 more
wiley   +1 more source

FT K-Means: A High-Performance K-Means on GPU with Fault Tolerance

2024 IEEE International Conference on Cluster Computing (CLUSTER)
K-means is a widely used algorithm in clustering, however, its efficiency is primarily constrained by the computational cost of distance computing. Existing implementations suffer from suboptimal utilization of computational units and lack resilience against soft errors.
Shixun Wu, Yitong Ding, Yujia Zhai, Jinyang Liu 0003, Jiajun Huang 0001, Zizhe Jian, Huangliang Dai, Sheng Di, Bryan M. Wong, Zizhong Chen, Franck Cappello   +10 more
openaire   +2 more sources

PARK(ing) time–How park deficiency affects the biological clock in a Drosophila model of Parkinson's disease

FEBS Letters, EarlyView.
Drosophila park mutants serve as a model for Parkinson's disease. We used this strain to investigate the connection between oxidative stress and the circadian clock mechanism. We showed that increased oxidative stress affects the physiology of pacemaker cells, disrupting their daily structural plasticity. Lack of rhythmic signaling from pacemaker cells
Kamila Zientara, Kinga Skoczek, Elzbieta Pyza, Milena Damulewicz   +3 more
wiley   +1 more source

Global k-means++: an effective relaxation of the global k-means clustering algorithm

Applied Intelligence
The $k$-means algorithm is a prevalent clustering method due to its simplicity, effectiveness, and speed. However, its main disadvantage is its high sensitivity to the initial positions of the cluster centers. The global $k$-means is a deterministic algorithm proposed to tackle the random initialization problem of k-means but its well-known that ...
Georgios Vardakas, Aristidis Likas
openaire   +2 more sources

Penerapan Metode K-Means Untuk Clustering Mahasiswa Berdasarkan Nilai Akademik Dengan Weka Interface Studi Kasus Pada Jurusan Teknik Informatika UMM Magelang

Semesta Teknika, 2016
The selection process among outstanding students in a department has a big problem. This process is not fair because only involve one criteria and ignore the other criteria.
Asroni Asroni, Ronald Adrian
doaj  

A review of unsupervised k-value selection techniques in clustering algorithms

Journal of Industrial Engineering and Management
Purpose: 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, Antonio Lorenzo-Espejo, Jesús Muñuzuri, Alejandro Escudero-Santana   +3 more
doaj   +1 more source

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, Junho Jeong, Chae Yeong Lee, Hyunjoon Cho, Man Hwan Oh, Je Chul Lee, Jee‐Young Lee, Yangmee Kim   +7 more
wiley   +1 more source

Three phosphatase families form a community: The phosphohydrolases that act upon inositol pyrophosphates

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

Face detection based on K-medoids clustering and associated with convolutional neural networks

Heliyon
Over 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

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, Xinqi Yan, Lucas F. Jansen Klomp, Stefano Schivo, Janine N. Post   +4 more
wiley   +1 more source