Results 161 to 170 of about 11,198,889 (292)
CT10 regulator of kinase (CRK) and CRK‐Like (CRKL) are signaling adaptors driving cell adhesion, motility, differentiation, and proliferation. SH2‐domain containing (SH) proteins are enriched in YXXP motifs which when phosphorylated create preferred binding sites for CRK family SH2 domains.
Phoebe M. Cousens +8 more
wiley +1 more source
K-means (K = 3) for different exosomes’ proteins expression at timepoints 0 (a) and 3 (b).
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
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
Reconstructing enzyme evolution by protein engineering
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
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
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
Klustering Dengan K-Means Berbasis LVQ Dan K-Means Berbasis OWA
Dian Eka Ratnawati, Indriati .
doaj +1 more source
Investigating transcription factor dynamics in health and disease using FRAP
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
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
Implementasi KD-Tree K-Means Clustering untuk Klasterisasi Dokumen
Klasterisasi dokumen adalah suatu proses pengelompokan dokumen secara otomatis dan unsupervised. Klasterisasi dokumen merupakan permasalahan yang sering ditemui dalam berbagai bidang seperti text mining dan sistem temu kembali informasi.
Eric Budiman Gosno +2 more
doaj

