Results 61 to 70 of about 305,651 (314)

Rab14 regulates the transport of human papillomavirus to the trans‐Golgi network for infectious cell entry

open access: yesFEBS Letters, EarlyView.
This study reveals that the small GTPase Rab14 is necessary for human papillomavirus (HPV) infection and plays an essential role in the transport of virions to the trans‐Golgi network (TGN). HPV in the early endosome (EE), which harbors GTP‐bound Rab14, is transported to the TGN through the switch of Rab14 from its GTP‐bound to GDP‐bound form.
Yoshiyuki Ishii, Iwao Kukimoto
wiley   +1 more source

Greedy Algorithm for Deriving Decision Rules from Decision Tree Ensembles

open access: yesEntropy
This study introduces a greedy algorithm for deriving decision rules from decision tree ensembles, targeting enhanced interpretability and generalization in distributed data environments.
Evans Teiko Tetteh, Beata Zielosko
doaj   +1 more source

Phosphoinositides and inositol phosphates as molecular glues

open access: yesFEBS Letters, EarlyView.
Inositol phosphates (IPs) and phosphoinositides (PIPs) regulate diverse eukaryotic processes. Beyond recruiting signaling proteins or acting as structural cofactors, recent studies suggest they mediate protein–protein interactions as natural molecular glues.
Aleshia Seaton‐Terry   +9 more
wiley   +1 more source

Probabilistic Decision Trees using SVM for Multi-class Classification [PDF]

open access: yes, 2013
In the automotive repairing backdrop, retrieving from previously solved incident the database features that could support and speed up the diagnostic is of great usefulness.
BOUAMAMA, Karima   +9 more
core   +1 more source

Establishment of a humanized patient‐derived xenograft mouse model of high‐grade serous ovarian cancer for preclinical evaluation of combination immunotherapy

open access: yesMolecular Oncology, EarlyView.
We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric   +10 more
wiley   +1 more source

Hyperparameter Optimization Using Iterative Decision Tree (IDT)

open access: yesIEEE Access, 2022
Machine learning and deep learning have gained a lot of attention from researchers because of their promising predictive performance and the availability of extensive high-dimensional data and high-performance computational hardware.
Narith Saum   +2 more
doaj   +1 more source

Bivariate decision trees [PDF]

open access: yes, 1997
Decision tree methods constitute an important and much used technique for classification problems. When such trees are used in a Datamining and Knowledge Discovery context, ease of interpretation of the resulting trees is an important requirement to be met.
Bioch, JC (Cor)   +2 more
openaire   +3 more sources

Extension of Decision Tree Algorithm for Stream Data Mining Using Real Data [PDF]

open access: yes, 2009
Recently, because of increasing amount of data in the society, data stream mining targeting large scale data has attracted attention. The data mining is a technology of discovery new knowledge and patterns from the massive amounts of data, and what the ...
Konishi, Osamu   +3 more
core  

Heterozygous loss‐of‐function alleles associate the conserved 3′‐5′ exoribonuclease EXOSC10 with hypersensitivity to the anticancer drug 5‐fluorouracil

open access: yesMolecular Oncology, EarlyView.
EXOSC10, an essential nuclear RNA exosome‐associated 3′‐5′ exoribonuclease, is inhibited by the anticancer drug 5‐fluorouracil (5‐FU), and EXOSC10 depletion increases 5‐FU sensitivity. The colon‐cancer variant EXOSC10S402T, located in a proteolysis motif, is stable and nuclear but nonfunctional in vivo.
Radhika Sain   +10 more
wiley   +1 more source

Decision Tree Algorithm Considering Distances Between Classes

open access: yesIEEE Access, 2022
Decision tree algorithm (DT) is a commonly used data mining method for classification and regression. DT repeatedly divides a dataset into pure subsets based on impurity measurements such as entropy and Gini.
Sangyong Lee   +3 more
doaj   +1 more source

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