Results 101 to 110 of about 797,470 (304)

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 Jansen Klomp, Stefano Schivo, Janine N. Post   +4 more
wiley   +1 more source

rEMM: Extensible Markov Model for Data Stream Clustering in R [PDF]

Clustering streams of continuously arriving data has become an important application of data mining in recent years and efficient algorithms have been proposed by several researchers. However, clustering alone neglects the fact that data in a data stream
Michael Hahsler, Margaret H. Dunham
core   +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, İsmail Güderer, Yi Wang, Tayyaba Alvi, Prasoon Pandey, Handan Melike Dönertaş   +5 more
wiley   +1 more source

Mixed‐class J‐domain protein scaffolds promote expanded aggregate handling and multivalent Hsp70 engagement during functional disaggregase assembly

FEBS Letters, EarlyView.
Protein aggregates threaten proteostasis and cell health. In human cells, Hsp70–J‐domain protein‐based disaggregases remove aggregates, but how they assemble remains unclear. Our biochemical findings show that DNAJA2‐ and DNAJB1‐containing disaggregase scaffolds enhance luciferase aggregate targeting, and that Hsp70 recruitment by both J‐domain ...
Anna Szlachcic, Nadinath B. Nillegoda
wiley   +1 more source

Approximating a similarity matrix by a latent class model: A reappraisal of additive fuzzy clustering [PDF]

, 2009
Let Q be a given n×n square symmetric matrix of nonnegative elements between 0 and 1, similarities. Fuzzy clustering results in fuzzy assignment of individuals to K clusters.
Braak, C.J.F., ter, Kourmpetis, Y.I.A., Kiers, H.A.L., Bink, M.C.A.M.   +3 more
core   +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, Christoph Pamminger, Rudolf Winter-Ebmer, Andrea Weber   +3 more
core   +3 more sources

Parsimonious Bayesian model-based clustering with dissimilarities

Machine Learning with Applications
Clustering techniques are used to group observations and discover interesting patterns within data. Model-based clustering is one such method that is often an attractive choice due to the specification of a generative model for the given data and the ...
Samuel Morrissette, Saman Muthukumarana, Maxime Turgeon   +2 more
doaj   +1 more source

Investigating transcription factor dynamics in health and disease using FRAP

FEBS Letters, EarlyView.
FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj, Carolina Vazquez Garzon, Jose Joaquin Velasco, Janine N. Post   +3 more
wiley   +1 more source

Mutual information based clustering of market basket data for profiling users [PDF]

, 2010
Attraction and commercial success of web sites depend heavily on the additional values visitors may find. Here, individual, automatically obtained and maintained user profiles are the key for user satisfaction.
Ende, Bartholomäus, Brause, Rüdiger W.
core  

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics [PDF]

, 2013
Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper,
Muhammad F Bari, Bari Muhammad F., Sirinukunwattana Korsuk, Bari, Muhammad F., Muhammad F. Bari, Savage, Richard S., David R. J. Snead, David R. J. Snead (475600), Richard S Savage, Richard S. Savage, Rajpoot Nasir M., Muhammad F. Bari (417733), Snead, David R. J., David R J Snead, Richard S. Savage (341629), Nasir M. Rajpoot, Korsuk Sirinukunwattana (475599), Rajpoot, Nasir M., Sirinukunwattana, Korsuk, Korsuk Sirinukunwattana, Snead, David R.J., Snead David R. J., Nasir M. Rajpoot (185555), Nasir M Rajpoot, Savage Richard S.   +24 more
core   +1 more source