Results 111 to 120 of about 325,444 (301)

Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment

Molecular Oncology, EarlyView.
This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley   +1 more source

Towards a Sustainable Disruptive Growth Model: Integrating Foresight, Wild Cards and Weak Signals Analysis

Foresight and STI Governance
This paper introduces epistemological and methodological innovations for analyzing non-linear dynamics in sustainability systems, such as deforestation tipping points, exponential renewable adoption, and protests driving global reform.
Rafael Popper, Yuli Villarroel, Raimund Popper   +2 more
doaj   +1 more source

Dimension reduction results (Movie dataset).

, 2019
Dimension reduction results (Movie dataset).
Hsien-Hsiu Chen (6804179), Ching-Hsue Cheng (6166625)   +1 more
core   +1 more source

Circular RNA expression landscapes in myelodysplastic neoplasms: Associations with mutational signatures and disease progression

Molecular Oncology, EarlyView.
In this explorative study, the abundance of circular RNA molecules in bone marrow stem cells was found to be elevated in patients with high‐risk myelodysplastic neoplasms, and to be associated with an increased risk of progression to acute myeloid leukemia.
Eileen Wedge, Morten Tulstrup, Gabriele Todisco, Pedro Moura, Christophe Côme, Jakob Werner Hansen, Jakob Schmidt Jespersen, Balthasar Schlotmann, Maria Creignou, Mette Dahl, Claudia Schöllkopf, Klas Raaschou‐Jensen, Krister Wennerberg, Bo Porse, Joachim Weischenfeldt, Eva Hellström‐Lindberg, Lasse Sommer Kristensen, Kirsten Grønbæk   +17 more
wiley   +1 more source

Sparse sufficient dimension reduction

Existing sufficient dimension reduction methods suffer from the fact that each dimension reduction component is a linear combination of all the original predictors, so that it is difficult to interpret the resulting estimates.
Lexin Li
core   +1 more source

Studies on dimension reduction and feature spaces : [PDF]

, 2011
Today's world produces and stores huge amounts of data, which calls for methods that can tackle both growing sizes and growing dimensionalities of data sets. Dimension reduction aims at answering the challenges posed by the latter.
Parviainen, Eli
core  

Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers

Molecular Oncology, EarlyView.
This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel, Peyman Zarrineh, Nathnael T. Tuffa, Jigar H. Sheth, Sumitra Mohan, Mudassar Iqbal, Sankari Nagarajan   +6 more
wiley   +1 more source

MaGIC-Analytics/magic-dimension-reduction: V1 release

<p>Initial release</p ...
Alex Lemenze
core   +1 more source

Dimethyl fumarate combined with cisplatin at subcytotoxic doses sensitizes cervical cancer toward ferroptosis and apoptosis through GSH restriction and p53 (re)activation

Molecular Oncology, EarlyView.
Dimethyl fumarate (DMF) reduces growth of HPV‐positive cervical cancer spheroids and induces ferroptosis in cervical cancer cells via blocking SLC7A11/Glutathione (GSH) axis. Combination of subcytotoxic doses of DMF and cisplatin (CDDP) further suppresses spheroid growth and drives cell death in 2D culture models.
Carolina Punziano, Giuseppina Minopoli, Simona Romano, Laura Marrone, Katia Aquilano, Maria Lina Tornesello, Raffaella Faraonio   +6 more
wiley   +1 more source

Dimension selection criteria for predictor envelopes in univariate regression

, 2020
Ordinary Least Squares is a ubiquitous multivariate statistical technique. Predictor envelopes have the potential to result in multifold gains in efficiency over OLS. Envelopes achieve these gains by partitioning the variability of the predictions into
Bales, Sam
core