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Detecting Meaningful Compounds in Complex Class Labels
[chapter]
2016
Lecture Notes in Computer Science
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In this paper, we investigate the problem of automatically detecting meaningful compounds in such complex class labels to support methods that require an automatic understanding of their meaning such as ...
Real-world ontologies such as, for instance, those for the medical domain often represent highly specific, fine-grained concepts using complex labels that consist of a sequence of sublabels. ...
Conclusions and Future Work In this paper we presented an approach to detect meaningful compounds within complex ontology class labels. ...
doi:10.1007/978-3-319-49004-5_40
fatcat:vebrbtdeanbohcuq2qr3kma3fq
Page 225 of American Society of Civil Engineers. Collected Journals Vol. 7, Issue 4
[page]
2003
American Society of Civil Engineers. Collected Journals
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The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
Therefore, it is critical that the toxicological relevance of EDCs and PPCPs be deter- mined in order to develop an appropriate target compound list and to establish meaningful method detection limits ...
Thus individual compounds or complex mixtures can be tested at various concen- trations until the concentration required to displace 50% of the labeled ligand (ECs,) is determined. ...
Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology
2016
International Journal of Molecular Sciences
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Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. ...
No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. ...
Many critical parameters, such as the discrepancy between the low number of detected metabolites versus the real number of possible metabolites, the bias against compound classes and the overlap of compartmentalized ...
doi:10.3390/ijms17050632
pmid:27128910
pmcid:PMC4881458
fatcat:vbjyrjbizfhebcdguisgnt2cdq
Emotion detection in task-oriented spoken dialogues
2003
2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698)
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About 11% of the utterances are annotated with non-neutral emotion labels. Preliminary experiments using lexical cues detect about 70% of these labels. ...
We make use of a corpus of real agent-client spoken dialogs in which the manifestation of emotion is quite complex, and it is common to have shaded emotions since the interlocutors attempt to control the ...
Despite the complexity involved, in our opinion it is crucial to work on real-life data. Emotion detection requires first identifying and validating emotion labels. ...
doi:10.1109/icme.2003.1221370
dblp:conf/icmcs/DevillersLV03
fatcat:6mhl6eb4azfplfn53fnr7i3pma
Chemical Similarity Enrichment Analysis (ChemRICH) as alternative to biochemical pathway mapping for metabolomic datasets
2017
Scientific Reports
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Today, metabolomics datasets often contain 500-800 structurally identified compounds, for example in biomedical research 17-23 , including tumor tissues 24 . ...
Third, for many identified compounds, especially lipids, substrate-enzyme relationships have not been unambiguously defined 40 . Fourth, many metabolites appear ...
However, pure chemical similarity clusters are difficult to name by intelligible, biologically or chemically meaningful class labels. ...
doi:10.1038/s41598-017-15231-w
pmid:29109515
pmcid:PMC5673929
fatcat:crukcycbrrgpbfoqpzdp4y4jwu
Heuristics for Chemical Compound Matching
2003
Genome Informatics Series
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of biochemically meaningful features. ...
Based on the concept of functional groups in chemistry, 68 atom types (vertex types) are defined for carbon, nitrogen, oxygen, and other atomic species with different environments, which has enabled detection ...
Acknowledgments We thank Koichiro Tonomura, Rumiko Yamamoto, Tomoko Komeno, and Masaaki Kotera for checking the compound and reaction data in the course of preparing our dataset. ...
doi:10.11234/gi1990.14.144
fatcat:wcuxvummqrauph6u6nvdnain5q
Change Point Geometry for Change Detection in Surveillance Video
[chapter]
2015
Lecture Notes in Computer Science
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State of the art results are shown in change detection, a fundamental computer vision problem for identifying regions of video that exhibit meaningful variations as defined by the application context. ...
A change detection algorithm is proposed based on geometric descriptors of space-time appearance discontinuities in fixed camera video. ...
in a meaningful way. ...
doi:10.1007/978-3-319-19665-7_31
fatcat:hmsf7d4jlfafjg4w5kuh7ppnvq
Learning Semantic Composition to Detect Non-compositionality of Multiword Expressions
2015
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing
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We present methods of non-compositionality detection for English noun compounds using the unsupervised learning of a semantic composition function. ...
We show that enforcing sparsity is a useful regularizer in learning complex composition functions. ...
As mentioned earlier, overly powerful learners overfit and do not produce meaningful errors for the detection task. ...
doi:10.18653/v1/d15-1201
dblp:conf/emnlp/YazdaniFH15
fatcat:3yo5mml7rvfytee33mx5tdtwt4
Isotopologue ratio normalization for non-targeted metabolomics
2015
Journal of Chromatography A
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The internal standards are detected in an automated manner using the non-targeted tracer fate detection algorithm. ...
Unlike many previous approaches, we include both identified and unidentified compounds in the data analysis. ...
Acknowledgements The authors thank Lars Steinmetz for providing the yeast strains used in this project. ...
doi:10.1016/j.chroma.2015.02.025
pmid:25748542
fatcat:vbnaifsuhfgh7jqkiyypc5v2em
Toward non-default partitioning for compound feature identification in engineering design
2021
Procedia CIRP
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A pre-labeled dataset of mechanical parts is established in the paper for training the network. ...
A pre-labeled dataset of mechanical parts is established in the paper for training the network. ...
The labelled point clouds are further used as instances in the dataset for deep learning based methods. Fig. 9 . The case study for compound feature detection. ...
doi:10.1016/j.procir.2021.05.032
fatcat:loyqfx5yy5dpxla76alcrkszdu
Accelerating the Development of Novel Molecular Imaging Probes: A Role for High-Throughput Screening
2008
Journal of Nuclear Medicine
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Molecular imaging is a rapidly emerging research tool and clinical discipline aimed at noninvasive, quantitative visualization of in vivo molecular processes occurring at cellular and subcellular levels ...
At present, advancement of the molecular imaging field is driven by the development of improved imaging hardware for use in preclinical and clinical settings, the identification and validation of new, ...
Label-free methodologies, such as mass spectrometry, also have potential for the detection of hits in HTS. ...
doi:10.2967/jnumed.108.053009
pmid:18703594
pmcid:PMC2576283
fatcat:e7ge4lpncvgarmf2k36f7jummi
Deciphering metabolic networks
2003
European Journal of Biochemistry
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Such spatial resolution is accompanied with temporal changes of metabolite synthesis in response to environmental stimuli or developmental needs. ...
secondary gene products, i.e. transcripts, proteins, and metabolites, regularly do not cope with this spatial and temporal resolution, these gene products are often observed to be highly coregulated forming complex ...
derive any biochemical meaningful conclusion. ...
doi:10.1046/j.1432-1033.2003.03427.x
pmid:12581198
fatcat:7iue42icznh75pjltfqmi7gnoa
Semi-supervised model-based clustering with controlled clusters leakage
[article]
2017
arXiv
pre-print
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Experimental results show that C3L finds high quality clustering model, which can be applied in discovering meaningful groups in partially classified data. ...
Our method can be implemented as a module in practical expert systems to detect clusters, which combine expert knowledge with true distribution of data. ...
Since every one dimensional view induces linear decision boundary in the original space, this technique may not be sufficient to detect complex data patters. ...
arXiv:1705.01877v1
fatcat:fxmplm5mf5ditj2uwxu7qynqiu
Research in Complex Event of Intelligent Logistics System's Warehousing and Storage Activities
2016
Internet of Things and Cloud Computing
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Complex event refers to many fields, such as finance, telecommunications, banking, automotive, and so on. Especially, it has an advantage of dealing with real-time data stream. ...
The research we study is how to tackle these urgent and complicated problems with Complex Event application that oriented Intelligent logistics system and Networking Middleware. ...
Middle Ware Model of Complex Event The complex event is meaningful event with an start time and an end time which is not constant until in a certain period. ...
doi:10.11648/j.iotcc.20160402.11
fatcat:weiklaelmfhp3lteme7jmxj3rq
Improving the interoperability of biomedical ontologies with compound alignments
2018
Journal of Biomedical Semantics
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The evaluation of the algorithms has shown that they are able to produce meaningful results, with precision in the range of 60-92% for new mappings. ...
Results: We have developed ontology matching algorithms that are able to find compound mappings between multiple biomedical ontologies, in the form of ternary mappings, finding for instance that "aortic ...
Availability of data and materials The datasets and algorithms generated during this study are available at: https://github.com/AgreementMakerLight/AML-Compound. ...
doi:10.1186/s13326-017-0171-8
pmid:29316968
pmcid:PMC5761129
fatcat:krulwajynvbk7ohb3swxnji3hq
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