Search results for "label"

Mapping of a binding site for ATP within the extracellular region of the Torpedo nicotinic acetylcholine receptor beta-subunit.

1997

Using 2,8,5'-[H-3]ATP as a direct photoaffinity label for membrane-bound nicotinic acetylcholine receptor (nAChR) from Torpedo marmorata, we have identified a binding site for ATP in the extracellular region of the beta-subunit of the receptor. Photolabeling was completely inhibited in the presence of saturating concentrations of nonradioactive ATP, whereas neither the purinoreceptor antagonists suramin, theophyllin, and caffeine nor the nAChR antagonists alpha-bungarotoxin and d-tubocurarine affected the labeling reaction. Competitive and noncompetitive nicotinic agonists and Ca2+ increased the yield of the photoreaction by up to 50%, suggesting that the respective binding sites are allost…

Cover Picture: A Biocatalytic Nanomaterial for the Label-Free Detection of Virus-Like Particles (ChemBioChem 11/2017)

2017

A Nonlinear Label Compression and Transformation Method for Multi-label Classification Using Autoencoders

2016

Multi-label classification targets the prediction of multiple interdependent and non-exclusive binary target variables. Transformation-based algorithms transform the data set such that regular single-label algorithms can be applied to the problem. A special type of transformation-based classifiers are label compression methods, which compress the labels and then mostly use single label classifiers to predict the compressed labels. So far, there are no compression-based algorithms that follow a problem transformation approach and address non-linear dependencies in the labels. In this paper, we propose a new algorithm, called Maniac (Multi-lAbel classificatioN usIng AutoenCoders), which extra…

A label compression method for online multi-label classification

2018

Abstract Many modern applications deal with multi-label data, such as functional categorizations of genes, image labeling and text categorization. Classification of such data with a large number of labels and latent dependencies among them is a challenging task, and it becomes even more challenging when the data is received online and in chunks. Many of the current multi-label classification methods require a lot of time and memory, which make them infeasible for practical real-world applications. In this paper, we propose a fast linear label space dimension reduction method that transforms the labels into a reduced encoded space and trains models on the obtained pseudo labels. Additionally…

Multi-label classification using boolean matrix decomposition

2012

This paper introduces a new multi-label classifier based on Boolean matrix decomposition. Boolean matrix decomposition is used to extract, from the full label matrix, latent labels representing useful Boolean combinations of the original labels. Base level models predict latent labels, which are subsequently transformed into the actual labels by Boolean matrix multiplication with the second matrix from the decomposition. The new method is tested on six publicly available datasets with varying numbers of labels. The experimental evaluation shows that the new method works particularly well on datasets with a large number of labels and strong dependencies among them.

Instance-Based Multi-Label Classification via Multi-Target Distance Regression

2021

Interest in multi-target regression and multi-label classification techniques and their applications have been increasing lately. Here, we use the distance-based supervised method, minimal learning machine (MLM), as a base model for multi-label classification. We also propose and test a hybridization of unsupervised and supervised techniques, where prototype-based clustering is used to reduce both the training time and the overall model complexity. In computational experiments, competitive or improved quality of the obtained models compared to the state-of-the-art techniques was observed. peerReviewed

Data set of the protein expression profiles of Luminal A, Claudin-low and overexpressing HER2+ breast cancer cell lines by iTRAQ labelling and tandem…

2015

Breast cancer is the most common and the leading cause of mortality in women worldwide. There is a dire necessity of the identification of novel molecules useful in diagnosis and prognosis. In this work we determined the differentially expression profiles of four breast cancer cell lines compared to a control cell line. We identified 1020 polypeptides labelled with iTRAQ with more than 95% in confidence. We analysed the common proteins in all breast cancer cell lines through IPA software (IPA core and Biomarkers). In addition, we selected the specific overexpressed and subexpressed proteins of the different molecular classes of breast cancer cell lines, and classified them according to prot…

A mild juvenile variant of type IV glycogenosis.

1992

The mild juvenile form of type IV glycogenosis, confirmed by a profound deficiency of the brancher enzyme in tissue specimens is reported from three Turkish male siblings who, foremost, suffered from chronic progressive myopathy. Muscle fibers contained polyglucosan inclusions of typical fine structure, i.e. a mixture of granular and filamentous glycogen. They reacted strongly for myophosphorylase, but were resistant to diastase. These inclusions were ubiquitinated and reacted with antibody KM-279 which previously has been shown to bind to Lafora bodies, corpora amylacea and polyglucosan material in hepatic and cardiac cells of type IV glycogenosis as well as polyglucosan body myopathy with…

The effects of glutamate receptor antagonists on cerebellar granule cell survival and development.

2007

N-Methyl-d-aspartate (NMDA) receptor stimulation promotes neuronal survival and differentiation under both in vitro and in vivo conditions. We studied the effects of various NMDA receptor antagonists acting at different NMDA receptor binding sites and non-NMDA receptor antagonists on the development and survival of cerebellar granule cell (CGC) culture. Only three of the drugs tested induced neurotoxicity-MK-801 (non-competitive NMDA channel blocking antagonist), ifenprodil (an antagonist of the NR2B site and polyamine site of the NMDA receptor) and L-701.324 (full antagonist at glycine site), while CGP-37849 (a competitive NMDA antagonist), (+)-HA-966 (a partial agonist of the glycine site…

Sources of nitrous oxide and fate of mineral nitrogen in sub-Arctic permafrost peat soils

2021

Nitrous oxide (N2O) emissions from permafrost-affected terrestrial ecosystems have received little attention, largely because they have been thought to be negligible. Recent studies, however, have shown that there are habitats in subarctic tundra emitting N2O at high rates, such as bare peat surfaces on permafrost peatlands. The processes behind N2O production in these high-emitting habitats are, however, poorly understood. In this study, we established an in situ 15N-labelling experiment with the main objectives to partition the microbial sources of N2O emitted from bare peat surfaces (BP) on permafrost peatlands and to study the fate of ammonium and nitrate in these soils and in adjacent …