Results 31 to 40 of about 18,151,738 (262)

Abridged Symbolic Representation of Time Series for Clustering

Acta Universitatis Lodziensis. Folia Oeconomica, 2019
In recent years a couple of methods aimed at time series symbolic representation have been introduced or developed. This activity is mainly justified by practical considerations such memory savings or fast data base searching.
Jerzy Korzeniewski
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, Kiddle, Steven J, Denby, Katherine J, Denby, Katherine J., Mukherjee, Sach, Mead, Andrew, Windram, Oliver P F, Windram, Oliver P., Kiddle, Steven J., McHattie, Stuart, Mead, A. (Andrew), Beynon, Jim   +11 more
core   +1 more source

Unsupervised Multivariate Time Series Clustering [PDF]

, 2021
Clustering is widely used in unsupervised machine learning to partition a given set of data into non-overlapping groups. Many real-world applications require processing more complex multivariate time series data characterized by more than one dependent ...
Glandon, Alex, Vidyaratne, Lasitha, Iftekharuddin, Khan, Rahman, Md Monibor   +3 more
core   +1 more source

JET: Fast Estimation of Hierarchical Time Series Clustering

Engineering Proceedings
Clustering is an effective, unsupervised classification approach for time series analysis applications that suffer a natural lack of training data. One such application is the development of jet engines, which involves numerous test runs and failure ...
Phillip Wenig, Mathias Höfgen, Thorsten Papenbrock   +2 more
doaj   +1 more source

Optimised meta-clustering approach for clustering Time Series Matrices [PDF]

, 2018
The prognostics (health state) of multiple components represented as time series data stored in vectors and matrices were processed and clustered more effectively and efficiently using the newly devised ‘Meta-Clustering’ approach.
Movahdisavehmotlagh, A.
core  

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, İsmail Güderer, Yi Wang, Tayyaba Alvi, Prasoon Pandey, Handan Melike Dönertaş   +5 more
wiley   +1 more source

Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation

FEBS Letters, EarlyView.
Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang, Ruslana Romaniuk, Hristo L. Svilenov   +2 more
wiley   +1 more source

Time-series clustering via quasi U-statistics

, 2015
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The problem of time-series discrimination and classification is discussed. We propose a novel clustering algorithm based on a
Pinheiro, A, Valk, M
core   +1 more source

Developmental programmes drive cellular plasticity, disease progression and therapy resistance in lung adenocarcinoma

Molecular Oncology, EarlyView.
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska, Stephany Gallardo, Nur S. Zainal, Leena Arora, Matthew Ellis, Maria‐Antoinette Lopez, Judith Austine, Sai Pittla, Serena J Chee, Aiman Alzetani, Emily C Shaw, Christian H Ottensmeier, Gareth J Thomas, Christopher J Hanley   +13 more
wiley   +1 more source

Smart Meters Time Series Clustering for Demand Response Applications in the Context of High Penetration of Renewable Energy Resources

Energies, 2021
The variability in generation introduced in the electrical system by an increasing share of renewable technologies must be addressed by balancing mechanisms, demand response being a prominent one.
Santiago Bañales, Raquel Dormido, Natividad Duro   +2 more
doaj   +1 more source