Results 51 to 60 of about 642,813 (313)
Pitfalls of supervised feature selection [PDF]
Bioinformatics, 2009 Pitfalls of supervised feature selection Pawel Smialowski1,2,∗, Dmitrij Frishman1,2 and Stefan Kramer3 1Department of Genome Oriented Bioinformatics, Technische Universitat Munchen Wissenschaftszentrum Weihenstephan, Am Forum 1, 85350 Freising, 2Helmholtz Zentrum Munich, National Research Center for Environment and Health, Institute for Bioinformatics,
Smialowski, P., Frishman, D., Kramer, S.
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FEBS Letters, EarlyView.In vivo IL‐10 produced by tissue‐resident tolDC is involved in maintaining/inducing tolerance. Depending on the agent used for ex vivo tolDC generation, cells acquire common features but prime T cells towards anergy, FOXP3+ Tregs, or Tr1 cells according to the levels of IL‐10 produced. Ex vivo‐induced tolDC were administered to patients to re‐establish/
Konstantina Morali +3 more
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, 2019 This study reviews two different problems of routed wavelength assignment optical network which are; static network RWA in this type the connection requests already given in advance, and dynamic network RWA where the requests of connection randomly arrived.
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Feature selection in bioinformatics [PDF]
SPIE Proceedings, 2012 In bioinformatics, there are often a large number of input features. For example, there are millions of single nucleotide polymorphisms (SNPs) that are genetic variations which determine the dierence between any two unrelated individuals. In microarrays, thousands of genes can be proled in each test. It is important to nd out which input features (e.g.,
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FoxO1 signaling in B cell malignancies and its therapeutic targeting
FEBS Letters, EarlyView.FoxO1 has context‐specific tumor suppressor or oncogenic character in myeloid and B cell malignancies. This includes tumor‐promoting properties such as stemness maintenance and DNA damage tolerance in acute leukemias, or regulation of cell proliferation and survival, or migration in mature B cell malignancies.
Krystof Hlavac +3 more
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Feature Selection in Hierarchical Feature Spaces [PDF]
, 2014 Feature selection is an important preprocessing step in data mining, which has an impact on both the runtime and the result quality of the subsequent processing steps. While there are many cases where hierarchic relations between features exist, most existing feature selection approaches are not capable of exploiting those relations.
Ristoski, Petar, Paulheim, Heiko
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Max-Margin feature selection [PDF]
Pattern Recognition Letters, 2017 Many machine learning applications such as in vision, biology and social networking deal with data in high dimensions. Feature selection is typically employed to select a subset of features which im- proves generalization accuracy as well as reduces the computational cost of learning the model.
Kanad K. Biswas +2 more
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Bayesian screening for feature selection
Journal of Biopharmaceutical Statistics, 2022 Biomedical applications such as genome-wide association studies screen large databases with high-dimensional features to identify rare, weakly expressed, and important continuous-valued features for subsequent detailed analysis. We describe an exact, rapid Bayesian screening approach with attractive diagnostic properties using a Gaussian random mixture
A. Lawrence Gould +2 more
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Insights into PI3K/AKT signaling in B cell development and chronic lymphocytic leukemia
FEBS Letters, EarlyView.This Review explores how the phosphoinositide 3‐kinase and protein kinase B pathway shapes B cell development and drives chronic lymphocytic leukemia, a common blood cancer. It examines how signaling levels affect disease progression, addresses treatment challenges, and introduces novel experimental strategies to improve therapies and patient outcomes.
Maike Buchner
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Making tau amyloid models in vitro: a crucial and underestimated challenge
FEBS Letters, EarlyView.This review highlights the challenges of producing in vitro amyloid assemblies of the tau protein. We review how accurately the existing protocols mimic tau deposits found in the brain of patients affected with tauopathies. We discuss the important properties that should be considered when forming amyloids and the benchmarks that should be used to ...
Julien Broc, Clara Piersson, Yann Fichou
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