Results 251 to 260 of about 28,639 (312)

Development of human monoclonal antibodies against TARM1 by yeast display

FEBS Open Bio, EarlyView.
Human monoclonal antibodies against TARM1 are generated by yeast display‐guided selection. These antibodies bind to soluble and cell‐surface forms of TARM1. Also, these antibodies exhibit agonistic activity in the NFAT‐GFP reporter assay, indicating that TARM1 signaling can be functionally modulated by antibodies and suggesting TARM1 as a potential ...
Rikio Yabe, Mayumi Saeki, Masaaki Hashiguchi, Sayaka Ono, Kazuhisa Aoki, Hidetaka Tanno   +5 more
wiley   +1 more source

Deep learning-based prediction of gene expression from histopathology identifies NR5A1 as a candidate biomarker and druggable target in high-grade serous ovarian carcinoma. [PDF]

J Ovarian Res
Lingasamy P, Ostrowska-Leśko M, Tsakalis P, Patel N, Chamatidis I, Sudhakaran SL, Kubik J, Bobiński M, Lagaros ND, Salumets A, Modhukur V.   +10 more
europepmc   +1 more source

Establishing an assay to evaluate d‐amino acid oxidase enzyme kinetics and inhibition using WST‐8 redox dye

FEBS Open Bio, EarlyView.
This study investigated a novel WST‐8‐based assay for evaluating d‐Amino acid oxidase (DAO) inhibitors. We confirmed its effectiveness using known inhibitors and found that uremic toxins possess relatively weak inhibitory activity compared to existing drugs.
Kahoko Miyake, Yuki Enoki, Yuka Nakazawa, Kazuaki Taguchi, Kazuaki Matsumoto   +4 more
wiley   +1 more source

Spectroscopic Pulse Embeddings by Contrastive Learning from Unlabeled Data for Pile-Up Analysis. [PDF]

Sensors (Basel)
Lin C, Zheng X, Trigano T, Bykhovsky D, Zhu Y, Tian L.   +5 more
europepmc   +1 more source

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

GR2ST: spatial transcriptomics prediction based on graph-enhanced multimodal contrastive learning. [PDF]

Bioinformatics
Zhou J, Li S, Han R, Wang X, Wang Y, Li J.   +5 more
europepmc   +1 more source

CLCNet: a contrastive learning and chromosome-aware network for genomic prediction in plants. [PDF]

Brief Bioinform
Huang J, Yang Z, Yin M, Li C, Li J, Wang Y, Huang L, Li M, Liang C, He F, Han R, Jiang Y.   +11 more
europepmc   +1 more source

Physics-guided contrastive temporal graph learning for anomaly detection and root-cause localization in industrial control systems. [PDF]

Sci Rep
Rajalakshmi M, Velmurugan T.
europepmc   +1 more source

A contrastive learning framework with adaptive feature fusion for brain tumor classification. [PDF]

Sci Rep
Peng Y, He S, Chang L.
europepmc   +1 more source

Prototype-oriented contrastive mean-teacher for unsupervised domain adaptive object detection. [PDF]

Sci Rep
Cao Q, Tao J, Dan Y, Zhou D.
europepmc   +1 more source