Results 161 to 170 of about 11,198,909 (310)

K-means (K = 3) for different exosomes’ proteins expression at timepoints 0 (a) and 3 (b).

open access: yes, 2019
K-means (K = 3) for different exosomes’ proteins expression at timepoints 0 (a) and 3 (b).
Francesca Bianchi (316618)   +14 more
core   +1 more source

MODIFIKASI K-MEANS BERBASIS ORDERED WEIGHTED AVERAGING (OWA) UNTUK KASUS KLASTERING

open access: yesAgrointek, 2016
K-means clustering method based on Ordered Weighted Averaging (OWA) was developed by Cheng et al (2009) to resolve problem in classification using integrating k-means clustering and OWA.
Millatul Ulya Millatul Ulya
doaj  

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

open access: yesFEBS 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

Klustering Dengan K-Means Berbasis LVQ Dan K-Means Berbasis OWA

open access: yesJurnal Teknologi Informasi dan Ilmu Komputer, 2015
Dian Eka Ratnawati, Indriati .
doaj   +1 more source

Reconstructing enzyme evolution by protein engineering

open access: yesFEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler   +2 more
wiley   +1 more source

Identification of a Shiga toxin A‐derived peptide internalized into Gb3 receptor‐bearing cells via interaction with the Shiga toxin B subunit

open access: yesFEBS Letters, EarlyView.
The process of internalization of the Shiga toxin A subunit via formation of a complex with the Shiga toxin B subunit, which specifically binds to the Gb3 receptor. The peptide is designed to act as a carrier of drugs into cancer cells. Here, we explored the potential of peptides derived from the catalytic A subunit of Shiga toxin (STxA) to be drug ...
Giulia Opassi   +6 more
wiley   +1 more source

A K-means-like algorithm for informetric data clustering

open access: yes, 2015
The K-means algorithm is one of the most often used clustering techniques. However, when it comes to discovering clusters in informetric data sets that consist of non-increasingly ordered vectors of not necessarily conforming lengths, such a method ...
Anna Cena (13497691)   +1 more
core  

Investigating transcription factor dynamics in health and disease using FRAP

open access: yesFEBS 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   +3 more
wiley   +1 more source

The role of miR‐335‐5p in the redifferentiation of BRAF p.V600E thyroid cancers

open access: yesMolecular Oncology, EarlyView.
The BRAF p.V600E mutation promotes thyroid cancer dedifferentiation and radioiodine resistance. Using a network approach, we identified miR‐335‐5p as a key regulator of BRAF‐mutated thyroid tumors. Restoring miR‐335‐5p increased thyroid‐specific gene expression and iodine uptake in cells and organoids.
Valeria Pecce   +11 more
wiley   +1 more source

Enhancing the performance of gradient boosting trees on regression problems

open access: yesJournal of Big Data
Gradient Boosting Trees (GBT) is a powerful machine learning technique that is based on ensemble learning methods that leverage the idea of boosting. GBT combines multiple weak learners sequentially to boost its prediction power proving its outstanding ...
Lydia Wahid Rizkallah
doaj   +1 more source

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