Scientific Publications
SoutheastAsian Pharmacogenomics Research Network (SEAPharm): Current Status and Perspectives
2019 Oct 4 PUBLIC HEALTH GENOMICS, 2019
Supatat Chumnumwat, Zen Huat Lu, Chonlaphat Sukasem, Michael Winther, Francis Capule, Asma A'tiyah Abdul Hamid, Bibek Bhandari, Usa Chaikledkaew, Noppadol Chanhom, Soranun Chantarangsu, Angkana Charoenyingwattana, Tong Thi Hang, Tin Maung Hlaing, Kyaw Soe Htun, Jiraphun Jittikoon, Ly Le, Surakameth Mahasirimongkol, Dzul, Azri Mohamed Noor, Jesus Shrestha, Lakkana Suwannoi, Pramote Tragulpiankit, Saowalak Turongkaravee, Sukanya Wattanapokayakit, Phonepadith Xangsayarath, Rika Yuliwulandari, Shamsul Mohd Zain, Wasun Chantratita
Pharmacogenomics (PGx) is increasingly being recognized as a potential tool for improving the efficacy and safety of drug therapy. Therefore, several efforts have been undertaken globally to facilitate the implementation process of PGx into routine clinical practice. Part of these efforts include the formation of PGx working groups working on PGx research, synthesis, and dissemination of PGx data and creation of PGx implementation strategies. In Asia, the Southeast Asian Pharmacogenomics Research Network (SEAPharm) is established to enable and strengthen PGx research among the various PGx communities within but not limited to countries in SEA; with the ultimate goal to support...
Read full articleReview on Databases and Bioinformatics Approaches on Pharmacogenomics of Adverse Drug Reactions
2021 Jan 13 PHARMACOGENOMICS AND PERSONALIZED MEDICINE
Hang Tong, Nga Phan, Thanh Nguyen, Dinh Nguyen, Nam S Vo, Ly Le
Pharmacogenomics has been used effectively in studying adverse drug reactions by determining the person-specific genetic factors associated with individual response to a drug. Current approaches have revealed the significant importance of sequencing technologies and sequence analysis strategies for interpreting the contribution of genetic variation in developing adverse reactions. Advance in next generation sequencing and platform brings new opportunities in validating the genetic candidates in certain reactions, and could be used to develop the preemptive tests to predict the outcome of the variation in a personal response to a drug. With the highly accumulated available data recently, the in silico approach...
Read full articlePrevalence of pharmacogenomic variants in 100 pharmacogenes among Southeast Asian populations under the collaboration of the Southeast Asian Pharmacogenomics Research Network (SEAPharm)
2021 Feb 4 HUMAN GENOME VARIATION
Wasun Chantratita, Chakkaphan Runcharoen, Koya Fukunaga, Insee Sensorn, Nareenart Iemwimangsa, Sommon Klumsathian, Hang Tong, Nam Vo, Ly Le, Tin Hlaing, Myo Thant, Shamsul Mohd Zain, Zahurin Mohamed, Yuh-Fen Pung, Francis Capule, Jose Jr. Nevado, Catherine Lynn Silao, Zeina al-mahayri, Bassam Ali, Rika Yuliwulandari, Kinasih Prayuni, Hilyatuz Zahroh, Dzul Azri Mohamed Noor, Phonepadith Xangsayarath, Dalouny Xayavong, Sengchanh Kounnavong, Somphou Sayasone, Zoe Kordou, Ioannis Liopetas, Athina Tsikrika, Evangelia Eirini Tsermpini, Maria Koromina, Christina Mitropoulou, George Patrinos, Aumpika Kesornsit, Angkana Charoenyingwattana, Sukanya Wattanapokayakit, Surakameth Mahasirimongkol, Taisei Mushiroda
Pharmacogenomics can enhance the outcome of treatment by adopting pharmacogenomic testing to maximize drug efficacy and lower the risk of serious adverse events. Next-generation sequencing (NGS) is a cost-effective technology for genotyping several pharmacogenomic loci at once, thereby increasing publicly available data. A panel of 100 pharmacogenes among Southeast Asian (SEA) populations was resequenced using the NGS platform under the collaboration of the Southeast Asian Pharmacogenomics Research Network (SEAPharm). Here, we present the frequencies of pharmacogenomic variants and the comparison of these pharmacogenomic variants among different SEA populations and other populations used as controls. We investigated the different types of...
Read full articleAnalysis of Short-read Aligners using Genome Sequence Complexity
2020 Dec 16 KSE 2020
Quang Tran, Nam Sy Vo, Eric Hicks, Tin Nguyen, Vinhthuy Phan
Next generation sequencing technologies have the capability to provide large numbers of short reads inexpensively and accurately. Researchers have proposed many different methods to align short reads to reference genomes. Nevertheless, long repeats, which are known to be abundant in eukaiyotic genomes, have caused considerable difficulty for genome assembly methods that rely on short-read alignment. Although a few researchers have studied sequence complexity of genomes in terms of repeats, none have quantitatively related such complexity to the difficulty of short read alignment and assembly. In this paper, we investigate several measures of genome sequence complexity with the goal of quantifying...
Read full articleA comprehensive and bias-free evaluation of genomic variant clinical interpretation tools
2021 Dec 28 KSE 2021
Nguyen Minh Trang, Mai Nguyen Anh Vu, Tran Hoang Anh, Do Minh Nguyet, Nguyen Thanh Nguyen
The advancement of Next Generation Sequencing (NGS) generates a huge pool of raw sequencing data and genomic variants, while the diverse selection of variant annotation tools adds even more confusion to the mix. Choosing the right tools for clinical interpretation of genomic variants is still challenging due to the lack of comprehensive evaluation studies in this field. Here, we introduced a bias-free analysis approach to assess ten well-known variant annotation tools in terms of clinical interpretation. Our results revealed notable correlations of contemporary methods when applied to the Clin Var dataset. Moreover, allele frequency is still a strong predictor, emphasizing...
Read full articleA comprehensive imputation-based evaluation of tag SNP selection strategies
2021 Dec 28 KSE 2021
Dat Thanh Nguyen, Hieu Quang Dinh, Giang Minh Vu, Duong Thuy Nguyen, Nam Sy Vo
Regardless of the rapid development of sequencing technology, single nucleotide polymorphism (SNP) array has been widely used for many large-scale genomic studies due to its cost-effectiveness. Recently, in parallel with the advancement in imputation strategies, several genotyping platforms for various species have been developed. Despite the importance of imputation accuracy in SNP array design, to the best of our knowledge, there are no systematic studies for evaluating tag SNP selection methods based on this metric. In this paper, using the leave-one-out cross-validation approach on the 1000 genome high-coverage dataset, we comprehensively evaluated four well-known tag SNP selection algorithms based on...
Read full articleRWRMTN: a tool for predicting disease-associated microRNAs based on a microRNA-target gene network
2020 Jun 15 BMC BIOINFORMATICS, 2020
Duc-Hau Le, Trang T.H Tran
Background The misregulation of microRNA (miRNA) has been shown to cause diseases. Recently, we have proposed a computational method based on a random walk framework on a miRNA-target gene network to predict disease-associated miRNAs. The prediction performance of our method is better than that of some existing state-of-the-art network- and machine learning-based methods since it exploits the mutual regulation between miRNAs and their target genes in the miRNA-target gene interaction networks. Results To facilitate the use of this method, we have developed a Cytoscape app, named RWRMTN, to predict disease-associated miRNAs. RWRMTN can work on any miRNA-target gene network. Highly...
Read full articleMachine learning-based approaches for disease gene prediction
2020 Jun 22 BRIEFINGS IN FUNTIONAL GENOMICS, 2020
Duc-Hau Le
Disease gene prediction is an essential issue in biomedical research. In the early days, annotation-based approaches were proposed for this problem. With the development of high-throughput technologies, interaction data between genes/proteins have grown quickly and covered almost genome and proteome; thus, network-based methods for the problem become prominent. In parallel, machine learning techniques, which formulate the problem as a classification, have also been proposed. Here, we firstly show a roadmap of the machine learning-based methods for the disease gene prediction. In the beginning, the problem was usually approached using a binary classification, where positive and negative training sample sets are...
Read full articleDisease subtyping using community detection from consensus networks
2020 Dec 16 KSE 2020
Hung Nguyen, Bang Tran, Duc Tran, Quang-Huy Nguyen, Duc-Hau Le, Tin Nguyen
Disease gene prediction is an essential issue in biomedical research. In the early days, annotation-based approaches were proposed for this problem. With the development of high-throughput technologies, interaction data between genes/proteins have grown quickly and covered almost genome and proteome; thus, network-based methods for the problem become prominent. In parallel, machine learning techniques, which formulate the problem as a classification, have also been proposed. Here, we firstly show a roadmap of the machine learning-based methods for the disease gene prediction. In the beginning, the problem was usually approached using a binary classification, where positive and negative training sample sets are...
Read full articleA Novel Method for Multispectral Image Classification by Using Social Spider Optimization Algorithm Integrated to Fuzzy C-Mean Clustering
2019 May 16 CANADIAN JOURNAL OF REMOTE SENSING, 2019
Quang-Thanh Bui, Quoc-Huy Nguyen, Van Manh Pham, Vu Dong Pham, Mai Hoang Tran, Trang T.H. Tran, Huu Duy Nguyen, Xuan Linh Nguyen, Hai Minh Pham
In remote sensing, Fuzzy C-Means clustering (FCM) is a robust method in determining membership grades of a pixel belonging to 1 or more classes. This paper proposes a novel approach by using the social spider optimization (SSO) algorithm in solving the search for optimal cluster centers in FCM. Hanoi, the capital of Vietnam, was chosen as a case study because of its spatial complexity. Multispectral satellite datasets of Landsat 8, Sentinel 2A and SPOT 7 were used. The experiment started with the segmentation process, followed by an examination of the model, then the results were compared with several conventional clustering methods....
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