Results 41 to 50 of about 810,691 (251)
A hidden Markov model-based algorithm for identifying tumour subtype using array CGH data
BMC Genomics, 2011 Background The recent advancement in array CGH (aCGH) research has significantly improved tumor identification using DNA copy number data. A number of unsupervised learning methods have been proposed for clustering aCGH samples.
Zhang Ke +5 more
doaj +1 more source
Methods in Ecology and Evolution, 2023 Transcriptome sequencing technologies have revolutionized the field of phylogenomics by facilitating the identification of homologous genes for species without whole genome sequences.
Jingting Shen +3 more
doaj +1 more source
Temporal clustering by affinity propagation reveals transcriptional modules in Arabidopsis thaliana [PDF]
, 2009 Motivation: Identifying regulatory modules is an important task in the exploratory analysis of gene expression time series data. Clustering algorithms are often used for this purpose.
Buchanan-Wollaston, Vicky +11 more
core +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Advanced Science, EarlyView.Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Labor Market Entry and Earnings Dynamics: Bayesian Inference Using Mixtures-of-Experts Markov Chain Clustering [PDF]
This paper analyzes patterns in the earnings development of young labor market entrants over their life cycle. We identify four distinctly different types of transition patterns between discrete earnings states in a large administrative data set. Further,
Sylvia Frühwirth-Schnatter +3 more
core +2 more sources
Application of clustering in statistical analysis of music data
Lietuvos Matematikos Rinkinys, 2012 In this article author analyses musical works of Lithuanian compositors using statistical methods. Markov chains are used to describe compositions. Stationary distributions are used as feature vectors for clustering. A few interpretations of clusters are
Mindaugas Kavaliauskas
doaj +1 more source
Dealing with Label Switching in Mixture Models Under Genuine Multimodality [PDF]
, 2008 The fitting of finite mixture models is an ill-defined estimation problem as completely different parameterizations can induce similar mixture distributions.
Leisch, Friedrich, Grün, Bettina
core +1 more source
Advanced Science, EarlyView.Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi +7 more
wiley +1 more source
INFORMATION TECHNOLOGY FOR STATISTICAL CLUSTER ANALYSIS OF INFORMATION IN COMPLEX NETWORKS
Компютерні системи та інформаційні технології, 2022 Information technology has been developed, which is used to collect, process and save large volumes of data from the web space. With the help of technology, the statistical characteristics of various segments of the web space and their cluster structure ...
OKSANA KYRYCHENKO
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Switching Spike Plasticity Shapes ACE2 Engagement Across SARS‐CoV‐2 Variants
Advanced Science, EarlyView.Conformational plasticity governs SARS‐CoV‐2 spike function and ACE2 recognition. Using high‐speed AFM and single‐molecule force spectroscopy, we analyzed the ancestral spike and nine variants, revealing progressive rigidification from Delta, variable plasticity in Omicron sublineages, and JN.1 compaction.
Sarah Stainer +17 more
wiley +1 more source