المؤلفون: Yuan Shinsheng, Chen Cheng-Tao, Lin Bai-Ling, Wang Chin-Di, Wu Huan-Bin, Hwang Pei-Ing, Wu Guani, Li Ker-Chau

المصدر: BMC Genomics, Vol 12, Iss 1, p 439 (2011)

مصطلحات موضوعية: Biotechnology, TP248.13-248.65, Genetics, QH426-470

الوصف: Abstract Background To elucidate the molecular complications in many complex diseases, we argue for the priority to construct a model representing the normal physiological state of a cell/tissue. Results By analyzing three independent microarray datasets on normal human tissues, we established a quantitative molecular model GET, which consists of 24 tissue-specific Gene Expression Templates constructed from a set of 56 genes, for predicting 24 distinct tissue types under disease-free condition. 99.2% correctness was reached when a large-scale validation was performed on 61 new datasets to test the tissue-prediction power of GET. Network analysis based on molecular interactions suggests a potential role of these 56 genes in tissue differentiation and carcinogenesis. Applying GET to transcriptomic datasets produced from tissue development studies the results correlated well with developmental stages. Cancerous tissues and cell lines yielded significantly lower correlation with GET than the normal tissues. GET distinguished melanoma from normal skin tissue or benign skin tumor with 96% sensitivity and 89% specificity. Conclusions These results strongly suggest that a normal tissue or cell may uphold its normal functioning and morphology by maintaining specific chemical stoichiometry among genes. The state of stoichiometry can be depicted by a compact set of representative genes such as the 56 genes obtained here. A significant deviation from normal stoichiometry may result in malfunction or abnormal growth of the cells.

وصف الملف: electronic resource

العلاقة: http://www.biomedcentral.com/1471-2164/12/439Test; https://doaj.org/toc/1471-2164Test

الوصول الحر: https://doaj.org/article/f832929e7af543a593c97fff7b637378Test

المؤلفون: Wu Huan-Bin, Wang Chin-Di, Lin Chang-Chun, Chen Yi-An, Hwang Pei-Ing

المصدر: BMC Genomics, Vol 8, Iss 1, p 416 (2007)

مصطلحات موضوعية: Biotechnology, TP248.13-248.65, Genetics, QH426-470

الوصف: Abstract Background The enormous amount of sequence data available in the public domain database has been a gold mine for researchers exploring various themes in life sciences, and hence the quality of such data is of serious concern to researchers. Removal of vector contamination is one of the most significant operations to obtain accurate sequence data containing only a cDNA insert from the basecalls output by an automatic DNA sequencer. Popular bioinformatics programs to accomplish vector trimming include LUCY, cross_match and SeqClean. Results In a recent study, where the program SeqClean was used to remove vector contamination from our test set of EST data compiled through various library construction systems, however, a significant number of errors remained after preliminary trimming. These errors were later almost completely corrected by simply using a re-linearized form of the cloning vector to compare against the target ESTs. The modified trimming procedure for SeqClean was also compared with the trimming efficiency of the other two popular programs, LUCY2, and cross_match. Using SeqClean with a re-linearized form of the cloning vector significantly surpassed the other two programs in all tested conditions, while the performance of the other two programs was not influenced by the modified procedure. Vector contamination in dbEST was also investigated in this study: 2203 out of the 48212 ESTs sampled from dbEST (2007-04-18 freeze) were found to match sequences in UNIVEC. Conclusion Vector contamination remains a serious concern to the data quality in the public sequence database nowadays. Based on the results presented here, we feel that our modified procedure with SeqClean should be recommended to all researchers for the task of vector removal from EST or genomic sequences.

وصف الملف: electronic resource

العلاقة: http://www.biomedcentral.com/1471-2164/8/416Test; https://doaj.org/toc/1471-2164Test

الوصول الحر: https://doaj.org/article/55dbdc7977e742ba8236c0eaa779e78bTest

المؤلفون: Hwang, Pei-Ing, Wu, Huan-Bin, Wang, Chin-Di, Lin, Bai-Ling, Chen, Cheng-Tao, Yuan, Shinsheng, Wu, Guani, Li, Ker-Chau

المصدر: BMC Genomics ; volume 12, issue 1 ; ISSN 1471-2164

مصطلحات موضوعية: Genetics, Biotechnology

الوصف: Background To elucidate the molecular complications in many complex diseases, we argue for the priority to construct a model representing the normal physiological state of a cell/tissue. Results By analyzing three independent microarray datasets on normal human tissues, we established a quantitative molecular model GET, which consists of 24 tissue-specific G ene E xpression T emplates constructed from a set of 56 genes, for predicting 24 distinct tissue types under disease-free condition. 99.2% correctness was reached when a large-scale validation was performed on 61 new datasets to test the tissue-prediction power of GET. Network analysis based on molecular interactions suggests a potential role of these 56 genes in tissue differentiation and carcinogenesis. Applying GET to transcriptomic datasets produced from tissue development studies the results correlated well with developmental stages. Cancerous tissues and cell lines yielded significantly lower correlation with GET than the normal tissues. GET distinguished melanoma from normal skin tissue or benign skin tumor with 96% sensitivity and 89% specificity. Conclusions These results strongly suggest that a normal tissue or cell may uphold its normal functioning and morphology by maintaining specific chemical stoichiometry among genes. The state of stoichiometry can be depicted by a compact set of representative genes such as the 56 genes obtained here. A significant deviation from normal stoichiometry may result in malfunction or abnormal growth of the cells.

الإتاحة: https://doi.org/10.1186/1471-2164-12-439Test

المؤلفون: Chen, Yi-An, Lin, Chang-Chun, Wang, Chin-Di, Wu, Huan-Bin, Hwang, Pei-Ing

الوصف: Background The enormous amount of sequence data available in the public domain database has been a gold mine for researchers exploring various themes in life sciences, and hence the quality of such data is of serious concern to researchers. Removal of vector contamination is one of the most significant operations to obtain accurate sequence data containing only a cDNA insert from the basecalls output by an automatic DNA sequencer. Popular bioinformatics programs to accomplish vector trimming include LUCY, cross_match and SeqClean. Results In a recent study, where the program SeqClean was used to remove vector contamination from our test set of EST data compiled through various library construction systems, however, a significant number of errors remained after preliminary trimming. These errors were later almost completely corrected by simply using a re-linearized form of the cloning vector to compare against the target ESTs. The modified trimming procedure for SeqClean was also compared with the trimming efficiency of the other two popular programs, LUCY2, and cross_match. Using SeqClean with a re-linearized form of the cloning vector significantly surpassed the other two programs in all tested conditions, while the performance of the other two programs was not influenced by the modified procedure. Vector contamination in dbEST was also investigated in this study: 2203 out of the 48212 ESTs sampled from dbEST (2007-04-18 freeze) were found to match sequences in UNIVEC. Conclusion Vector contamination remains a serious concern to the data quality in the public sequence database nowadays. Based on the results presented here, we feel that our modified procedure with SeqClean should be recommended to all researchers for the task of vector removal from EST or genomic sequences.

العلاقة: http://www.biomedcentral.com/1471-2164/8/416Test

الإتاحة: http://www.biomedcentral.com/1471-2164/8/416Test

المؤلفون: Dong, Guo-Chung, Chuang, Ping-Hsien, Chang, Kai-chun, Jan, Pey-shynan, Hwang, Pei-Ing, Wu, Huan-Bin, Yi, Myunggi, Zhou, Huan-Xiang, Chen, Hueih Min

المصدر: Pharmaceutical Research ; volume 26, issue 2, page 375-381 ; ISSN 0724-8741 1573-904X

مصطلحات موضوعية: Pharmacology (medical), Organic Chemistry, Pharmaceutical Science, Pharmacology, Molecular Medicine, Biotechnology

الإتاحة: https://doi.org/10.1007/s11095-008-9754-5Test