Results 151 to 160 of about 14,276,290 (299)
Structure‐forward targeting of claudins with synthetic binders
FEBS Letters, EarlyView.Claudins form the paracellular barriers between epithelial and endothelial tissues at tight junctions and are targets for molecular binders with the goal of modulating barrier permeability. Claudin‐binding molecules are relevant in drug delivery or in altering claudin interactions with disease‐causing proteins.
Alex J. Vecchio
wiley +1 more source
, 2021 We study the problem of learning a clustering of an online set of points. The specific formulation we use is the k-means objective: At each time step the algorithm has to maintain a set of k candidate centers and the loss incurred by the algorithm is the
Rom, G +3 more
core
Face detection based on K-medoids clustering and associated with convolutional neural networks
HeliyonOver the last several years, the COVID-19 epidemic has spread over the globe. People have become used to the novel standard, which involves working from home, chatting online, and keeping oneself clean, to stop the spread of COVID-19.
Potharla Ramadevi, Raja Das
doaj +1 more source
Discerning protein pools by selective staining with self‐labeling tags
FEBS Letters, EarlyView.Cell surface proteins have an intra‐ and extracellular pool. Combining genetic fusion to self‐labeling tags that can be addressed with small molecule fluorophores allows separating these pools. We highlight recent developments and techniques for state‐of‐the‐art interrogation of cell surface proteins in the complex tissue setting.
Kati Fischermanns, Johannes Broichhagen
wiley +1 more source
Analysis on local optimum existence form of K-means-type
, 2014 With the hypothesis of Gaussian distribution of patterns, K-means and its extensions are good for clustering. As the representative of partitional clustering algorithm, K-means follows rules for running: numbers of clusters to be set, cluster ...
Xia QH(夏庆华) +8 more
core
MODIFIKASI K-MEANS BERBASIS ORDERED WEIGHTED AVERAGING (OWA) UNTUK KASUS KLASTERING
Agrointek, 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
FEBS Letters, EarlyView.Animals must match their growth rate to available nutrients. We show that in Drosophila larvae, the nutrient‐sensing TOR kinase controls growth by regulating levels of TFAM, a key regulator of mitochondrial function, in the adipose tissue. When nutrients are abundant, high TOR activity suppresses TFAM, lowering mitochondrial bioenergetic activity and ...
Shrivani Sriskanthadevan‐Pirahas +4 more
wiley +1 more source
Klustering Dengan K-Means Berbasis LVQ Dan K-Means Berbasis OWA
Jurnal Teknologi Informasi dan Ilmu Komputer, 2015 Dian Eka Ratnawati, Indriati .
doaj +1 more source
Peripheral lysosomes recruit PLEKHG3 to focal adhesions and restrain protrusion dynamics
FEBS Letters, EarlyView.Proximity‐dependent labeling at the LAMTOR complex revealed the Rho GEF PLEKHG3 as a lysosome‐proximal protein directing the study toward the influence of lysosome positioning on actin dynamics and cell motility. We show that PLEKHG3 colocalizes with lysosomes at focal adhesion sites and observe that forced peripheral dispersion of lysosomes hinders ...
Rainer Ettelt +8 more
wiley +1 more source
Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation
FEBS Letters, EarlyView.Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang +2 more
wiley +1 more source