Browsing by Author "Xiang, Yang"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Building Integrated Ontological Knowledge Structures with Efficient Approximation Algorithms
    (2015) Xiang, Yang; Janga, Sarath Chandra
    The integration of ontologies builds knowledge structures which brings new understanding on existing terminologies and their associations. With the steady increase in the number of ontologies, automatic integration of ontologies is preferable over manual solutions in many applications. However, available works on ontology integration are largely heuristic without guarantees on the quality of the integration results. In this work, we focus on the integration of ontologies with hierarchical structures. We identified optimal structures in this problem and proposed optimal and efficient approximation algorithms for integrating a pair of ontologies. Furthermore, we extend the basic problem to address the integration of a large number of ontologies, and correspondingly we proposed an efficient approximation algorithm for integrating multiple ontologies. The empirical study on both real ontologies and synthetic data demonstrates the effectiveness of our proposed approaches. In addition, the results of integration between gene ontology and National Drug File Reference Terminology suggest that our method provides a novel way to perform association studies between biomedical terms.
  • Thumbnail Image
    Item
    A framework for identifying genotypic information from clinical records: exploiting integrated ontology structures to transfer annotations between ICD codes and Gene Ontologies
    (IEEE, 2015-09) Hashemikhabir, Seyedsasan; Xia, Ran; Xiang, Yang; Janga, Sarath Chandra; Department of Biohealth Informatics, School of Informatics and Computing
    Although some methods are proposed for automatic ontology generation, none of them address the issue of integrating large-scale heterogeneous biomedical ontologies. We propose a novel approach for integrating various types of ontologies efficiently and apply it to integrate International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9CM) and Gene Ontologies (GO). This approach is one of the early attempts to quantify the associations among clinical terms (e.g. ICD9 codes) based on their corresponding genomic relationships. We reconstructed a merged tree for a partial set of GO and ICD9 codes and measured the performance of this tree in terms of associations’ relevance by comparing them with two well-known disease-gene datasets (i.e. MalaCards and Disease Ontology). Furthermore, we compared the genomic-based ICD9 associations to temporal relationships between them from electronic health records. Our analysis shows promising associations supported by both comparisons suggesting a high reliability. We also manually analyzed several significant associations and found promising support from literature.
  • Thumbnail Image
    Item
    An integrated investigation of lake storage and water level changes in the Paiku Co basin, central Himalayas
    (Elsevier, 2018) Lei, Yanbin; Yao, Tandong; Yang, Kun; Bird, Broxton W.; Tian, Lide; Zhang, Xiaowen; Wang, Weicai; Xiang, Yang; Dai, Yufeng; Lazhu; Zhou, Jing; Wang, Lei; Earth Sciences, School of Science
    Since the late 1990s, lakes in the southern Tibetan Plateau (TP) have shrunk considerably, which contrasts with the rapid expansion of lakes in the interior TP. Although these spatial trends have been well documented, the underlying hydroclimatic mechanisms are not well understood. Since 2013, we have carried out comprehensive water budget observations at Paiku Co, an alpine lake in the central Himalayas. In this study, we investigate water storage and lake level changes on seasonal to decadal time scales based on extensive in-situ measurements and satellite observations. Bathymetric surveys show that Paiku Co has a mean and maximum water depth of 41.1 m and 72.8 m, respectively, and its water storage was estimated to be 109.3 × 108 m3 in June 2016. On seasonal scale between 2013 and 2017, Paiku Co’s lake level decreased slowly between January and May, increased considerably between June and September, and then decreased rapidly between October and January. On decadal time scale, Paiku Co’s lake level decreased by 3.7 ± 0.3 m and water storage reduced by (10.2 ± 0.8) × 108 m3 between 1972 and 2015, accounting for 8.5% of the total water storage in 1972. This change is consistent with a trend towards drier conditions in the Himalaya region during the recent decades. In contrast, glacial lakes within Paiku Co’s basin expanded rapidly, indicating that, unlike Paiku Co, glacial meltwater was sufficient to compensate the effect of the reduced precipitation.