Results 51 to 60 of about 156,516 (263)
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
Multi-View Enhancement Graph-Level Clustering Network
IEEE AccessGraph-level clustering is a fundamental and significant task in data mining. The advancement of graph neural networks has provided substantial impetus to this area of research.
Zeyi Li +4 more
doaj +1 more source
Central Clustering of Attributed Graphs [PDF]
Machine Learning, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Brijnesh J. Jain, Fritz Wysotzki
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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
A Short Text Clustering Algorithm Based on Spectral Cut [PDF]
Jisuanji gongcheng, 2016 Short text has the characteristics of sparsity and high dimension,and the existing clustering algorithm for the large-scale short text has low accuracy and efficiency.Aiming at this problem,a novel clustering method based on spectral clustering theory ...
LI Xiaohong,XIE Meng,MA Huifang,HE Tingnian
doaj +1 more source
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
Clustering graph data: the roadmap to spectral techniques
Discover Artificial IntelligenceGraph data models enable efficient storage, visualization, and analysis of highly interlinked data, by providing the benefits of horizontal scalability and high query performance.
Rahul Mondal +5 more
doaj +1 more source
Generalized Graph Clustering: Recognizing (p,q)-Cluster Graphs [PDF]
, 2010 CLUSTER EDITING is a classical graph theoretic approach to tackle the problem of data set clustering: it consists of modifying a similarity graph into a disjoint union of cliques, i.e, clusters. As pointed out in a number of recent papers, the cluster editing model is too rigid to capture common features of real data sets.
Pinar Heggernes +4 more
openaire +1 more source
Golgi enzymes are retrieved from the plasma membrane to the trans‐Golgi network
FEBS Letters, EarlyView.Golgi enzymes are traditionally considered resident proteins retained within the Golgi apparatus. Here, we demonstrate that a subset transiently reaches the cell surface and is subsequently retrieved to the trans‐Golgi network via retrograde transport. Using a nanobody‐based toolkit, we uncover a dynamic trafficking cycle of several Golgi enzymes.
Dominik P. Buser, Tina Junne
wiley +1 more source
FDC-LGL: Fast Discrete Clustering with Local Graph Learning for Large-Scale Datasets
MathematicsGraph-based clustering is a fundamental task in unsupervised machine learning and has been extensively applied to complex data mining scenarios, such as pattern recognition and data classification. However, most existing graph clustering algorithms still
Shenfei Pei, Ruiyu Huang, Zengwei Zheng
doaj +1 more source