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Indolyl Alkaloid Derivatives, Nb-Acetyltryptamine and Oxaline from a Marine-Derived Fungus
YongLi,XiFengLi,DongSooKim,HongDaeChoi,ByengWhaSon 대한약학회 2003 Archives of Pharmacal Research Vol.26 No.1
Indolyl alkaloids, Nb-acetyltryptamine (1) and the known oxaline (2) have been isolated from the organic extract of the broth of an unidentified fungus collected from the surface of the marine red alga Gracilaria verrucosa. The structure of Nb-acetyltryptamine (1) was assigned on the basis of comprehensive spectroscopic analyses.
Yongli Qiao,Wenzhu Jiang,Md Lutfor Rahman,추상호,Rihua Piao,Longzhi Han,고희종 한국분자세포생물학회 2008 Molecules and cells Vol.25 No.3
Comparison of maps and QTLs between populations may provide us with a better understanding of molecular maps and the inheritance of traits. We developed and used two reciprocal BC1F1 populations, IP/DS//IP and IP/DS//DS, for QTL analysis. DS (Dasanbyeo) is a Korean tongil-type cultivar (derived from an indica x japonica cross and similar to indica in its genetic makeup) and IP (Ilpumbyeo) is a Korean japonica cultivar. We constructed two molecular linkage maps corresponding to each backcross population using 196 markers for each map. The length of each chromosome was longer in the IP/DS//IP population than in the IP/DS//DS population, indicating that more recombinants were produced in the IP/DS//IP population. Distorted segregation was observed for 44 and 19 marker loci for the IP/DS//IP and IP/DS//DS populations, respectively; these were mostly skewed in favor of the indica alleles. A total of 36 main effect QTLs (M-QTLs) and 15 digenic epistatic interactions (E-QTLs) were detected for the seven traits investigated. The phenotypic variation explained (PVE) by M-QTLs ranged from 3.4% to 88.2%. Total PVE of the M-QTLs for each trait was significantly higher than that of the E-QTLs. The total number of M-QTLs identified in the IP/DS//IP population was higher than in the IP/DS//DS population. However, the total PVE by the M-QTLs and E-QTLs together for each trait was similar in the two populations, suggesting that the two BC1F1 populations are equally useful for QTL analysis. Maps and QTLs in the two populations were compared. Eleven new QTLs were identified for SN, SF, GL, and GW in this study, and they will be valuable in marker-assisted selection, particularly for improving grain traits in tongil-type varieties.
A Density Peak Clustering Algorithm Based on Information Bottleneck
Yongli Liu,Congcong Zhao,Hao Chao 한국정보처리학회 2023 Journal of information processing systems Vol.19 No.6
Although density peak clustering can often easily yield excellent results, there is still room for improvementwhen dealing with complex, high-dimensional datasets. One of the main limitations of this algorithm is itsreliance on geometric distance as the sole similarity measurement. To address this limitation, we drawinspiration from the information bottleneck theory, and propose a novel density peak clustering algorithm thatincorporates this theory as a similarity measure. Specifically, our algorithm utilizes the joint probabilitydistribution between data objects and feature information, and employs the loss of mutual information as themeasurement standard. This approach not only eliminates the potential for subjective error in selectingsimilarity method, but also enhances performance on datasets with multiple centers and high dimensionality. To evaluate the effectiveness of our algorithm, we conducted experiments using ten carefully selected datasetsand compared the results with three other algorithms. The experimental results demonstrate that our informationbottleneck-based density peaks clustering (IBDPC) algorithm consistently achieves high levels of accuracy,highlighting its potential as a valuable tool for data clustering tasks.
A Mixed Co-clustering Algorithm Based on Information Bottleneck
Yongli Liu,Tianyi Duan,Xing Wan,Hao Chao 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.6
Fuzzy co-clustering is sensitive to noise data. To overcome this noise sensitivity defect, possibilistic clusteringrelaxes the constraints in FCM-type fuzzy (co-)clustering. In this paper, we introduce a new possibilistic fuzzyco-clustering algorithm based on information bottleneck (ibPFCC). This algorithm combines fuzzy coclusteringand possibilistic clustering, and formulates an objective function which includes a distance functionthat employs information bottleneck theory to measure the distance between feature data point and featurecluster centroid. Many experiments were conducted on three datasets and one artificial dataset. Experimentalresults show that ibPFCC is better than such prominent fuzzy (co-)clustering algorithms as FCM, FCCM,RFCC and FCCI, in terms of accuracy and robustness.
Incremental fuzzy clustering based on a fuzzy scatter matrix
Yongli Liu,Hengda Wang,Tianyi Duan,Jingli Chen,Hao Chao 한국정보처리학회 2019 Journal of information processing systems Vol.15 No.2
For clustering large-scale data, which cannot be loaded into memory entirely, incremental clustering algorithmsare very popular. Usually, these algorithms only concern the within-cluster compactness and ignore thebetween-cluster separation. In this paper, we propose two incremental fuzzy compactness and separation (FCS)clustering algorithms, Single-Pass FCS (SPFCS) and Online FCS (OFCS), based on a fuzzy scatter matrix. Firstly, we introduce two incremental clustering methods called single-pass and online fuzzy C-meansalgorithms. Then, we combine these two methods separately with the weighted fuzzy C-means algorithm, sothat they can be applied to the FCS algorithm. Afterwards, we optimize the within-cluster matrix and betweenclustermatrix simultaneously to obtain the minimum within-cluster distance and maximum between-clusterdistance. Finally, large-scale datasets can be well clustered within limited memory. We implemented experimentson some artificial datasets and real datasets separately. And experimental results show that, compared withSPFCM and OFCM, our SPFCS and OFCS are more robust to the value of fuzzy index m and noise.