Genome informatics. International Conference on Genome Informatics最新文献_第8页

A state space representation of VAR models with sparse learning for dynamic gene networks. 基于稀疏学习的动态基因网络VAR模型的状态空间表示。

Genome informatics. International Conference on Genome Informatics Pub Date : 2010-01-01 DOI: 10.1142/9781848165786_0006

Kaname Kojima, R. Yamaguchi, S. Imoto, Mai Yamauchi, Masao Nagasaki, Ryo Yoshida, Teppei Shimamura, Kazuko Ueno, T. Higuchi, N. Gotoh, S. Miyano

{"title":"A state space representation of VAR models with sparse learning for dynamic gene networks.","authors":"Kaname Kojima, R. Yamaguchi, S. Imoto, Mai Yamauchi, Masao Nagasaki, Ryo Yoshida, Teppei Shimamura, Kazuko Ueno, T. Higuchi, N. Gotoh, S. Miyano","doi":"10.1142/9781848165786_0006","DOIUrl":"https://doi.org/10.1142/9781848165786_0006","url":null,"abstract":"We propose a state space representation of vector autoregressive model and its sparse learning based on L1 regularization to achieve efficient estimation of dynamic gene networks based on time course microarray data. The proposed method can overcome drawbacks of the vector autoregressive model and state space model; the assumption of equal time interval and lack of separation ability of observation and systems noises in the former method and the assumption of modularity of network structure in the latter method. However, in a simple implementation the proposed model requires the calculation of large inverse matrices in a large number of times during parameter estimation process based on EM algorithm. This limits the applicability of the proposed method to a relatively small gene set. We thus introduce a new calculation technique for EM algorithm that does not require the calculation of inverse matrices. The proposed method is applied to time course microarray data of lung cells treated by stimulating EGF receptors and dosing an anticancer drug, Gefitinib. By comparing the estimated network with the control network estimated using non-treated lung cells, perturbed genes by the anticancer drug could be found, whose up- and down-stream genes in the estimated networks may be related to side effects of the anticancer drug.","PeriodicalId":73143,"journal":{"name":"Genome informatics. International Conference on Genome Informatics","volume":"17 1","pages":"56-68"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89889175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 32

Characterization and classification of adverse drug interactions. 药物不良反应的特征和分类。

Genome informatics. International Conference on Genome Informatics Pub Date : 2010-01-01 DOI: 10.1142/9781848165786_0014

Masataka Takarabe, D. Shigemizu, Masaaki Kotera, S. Goto, M. Kanehisa

引用次数: 5

A dynamic programming algorithm to predict synthesis processes of tree-structured compounds with graph grammar. 基于图语法的树状化合物合成过程预测的动态规划算法。

Genome informatics. International Conference on Genome Informatics Pub Date : 2010-01-01 DOI: 10.1142/9781848166585_0018

Yang Zhao, Takeyuki Tamura, M. Hayashida, T. Akutsu

引用次数: 0

Comparison of gene expression profiles produced by CAGE, illumina microarray and real time RT-PCR. CAGE、illumina芯片和实时RT-PCR基因表达谱的比较。

Genome informatics. International Conference on Genome Informatics Pub Date : 2010-01-01

André Fujita, Masao Nagasaki, Seiya Imoto, Ayumu Saito, Emi Ikeda, Teppei Shimamura, Rui Yamaguchi, Yoshihide Hayashizaki, Satoru Miyano

{"title":"Comparison of gene expression profiles produced by CAGE, illumina microarray and real time RT-PCR.","authors":"André Fujita, Masao Nagasaki, Seiya Imoto, Ayumu Saito, Emi Ikeda, Teppei Shimamura, Rui Yamaguchi, Yoshihide Hayashizaki, Satoru Miyano","doi":"","DOIUrl":"","url":null,"abstract":"Several technologies are currently used for gene expression profiling, such as Real Time RT-PCR, microarray and CAGE (Cap Analysis of Gene Expression). CAGE is a recently developed method for constructing transcriptome maps and it has been successfully applied to analyzing gene expressions in diverse biological studies. The principle of CAGE has been developed to address specific issues such as determination of transcriptional starting sites, the study of promoter regions and identification of new transcripts. Here, we present both quantitative and qualitative comparisons among three major gene expression quantification techniques, namely: CAGE, illumina microarray and Real Time RT-PCR, by showing that the quantitative values of each method are not interchangeable, however, each of them has unique characteristics which render all of them essential and complementary. Understanding the advantages and disadvantages of each technology will be useful in selecting the most appropriate technique for a determined purpose.","PeriodicalId":73143,"journal":{"name":"Genome informatics. International Conference on Genome Informatics","volume":"24 ","pages":"56-68"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30252336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Annotating gene functions with integrative spectral clustering on microarray expressions and sequences. 利用微阵列表达和序列的整合谱聚类来注释基因功能。

Genome informatics. International Conference on Genome Informatics Pub Date : 2010-01-01

Limin Li, Motoki Shiga, Wai-Ki Ching, Hiroshi Mamitsuka

引用次数: 0

New kernel methods for phenotype prediction from genotype data. 从基因型数据预测表型的新核心方法。

Genome informatics. International Conference on Genome Informatics Pub Date : 2010-01-01

Ritsuko Onuki, Tetsuo Shibuya, Minoru Kanehisa

引用次数: 0

A state space representation of VAR models with sparse learning for dynamic gene networks. 基于稀疏学习的动态基因网络VAR模型的状态空间表示。

Genome informatics. International Conference on Genome Informatics Pub Date : 2010-01-01

Kaname Kojima, Rui Yamaguchi, Seiya Imoto, Mai Yamauchi, Masao Nagasaki, Ryo Yoshida, Teppei Shimamura, Kazuko Ueno, Tomoyuki Higuchi, Noriko Gotoh, Satoru Miyano

{"title":"A state space representation of VAR models with sparse learning for dynamic gene networks.","authors":"Kaname Kojima, Rui Yamaguchi, Seiya Imoto, Mai Yamauchi, Masao Nagasaki, Ryo Yoshida, Teppei Shimamura, Kazuko Ueno, Tomoyuki Higuchi, Noriko Gotoh, Satoru Miyano","doi":"","DOIUrl":"","url":null,"abstract":"We propose a state space representation of vector autoregressive model and its sparse learning based on L1 regularization to achieve efficient estimation of dynamic gene networks based on time course microarray data. The proposed method can overcome drawbacks of the vector autoregressive model and state space model; the assumption of equal time interval and lack of separation ability of observation and systems noises in the former method and the assumption of modularity of network structure in the latter method. However, in a simple implementation the proposed model requires the calculation of large inverse matrices in a large number of times during parameter estimation process based on EM algorithm. This limits the applicability of the proposed method to a relatively small gene set. We thus introduce a new calculation technique for EM algorithm that does not require the calculation of inverse matrices. The proposed method is applied to time course microarray data of lung cells treated by stimulating EGF receptors and dosing an anticancer drug, Gefitinib. By comparing the estimated network with the control network estimated using non-treated lung cells, perturbed genes by the anticancer drug could be found, whose up- and down-stream genes in the estimated networks may be related to side effects of the anticancer drug.","PeriodicalId":73143,"journal":{"name":"Genome informatics. International Conference on Genome Informatics","volume":"22 ","pages":"56-68"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"28785607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Formal representation of the high osmolarity glycerol pathway in yeast. 酵母中高渗透压甘油途径的形式表示。

Genome informatics. International Conference on Genome Informatics Pub Date : 2010-01-01 DOI: 10.1142/9781848165786_0007

C. Kühn, K. V. S. Prasad, E. Klipp, P. Gennemark

{"title":"Formal representation of the high osmolarity glycerol pathway in yeast.","authors":"C. Kühn, K. V. S. Prasad, E. Klipp, P. Gennemark","doi":"10.1142/9781848165786_0007","DOIUrl":"https://doi.org/10.1142/9781848165786_0007","url":null,"abstract":"The high osmolarity glycerol (HOG) signalling system in yeast belongs to the class of Mitogen Activated Protein Kinase (MAPK) pathways that are found in all eukaryotic organisms. It includes at least three scaffold proteins that form complexes, and involves reactions that are strictly dependent on the set of species bound to a certain complex. The scaffold proteins lead to a combinatorial increase in the number of possible states. To date, representations of the HOG pathway have used simplifying assumptions to avoid this combinatorial problem. Such assumptions are hard to make and may obscure or remove essential properties of the system. This paper presents a detailed generic formal representation of the HOG system without such assumptions, showing the molecular interactions known from the literature. The model takes complexes into account, and summarises existing knowledge in an unambiguous and detailed representation. It can thus be used to anchor discussions about the HOG system. In the commonly used Systems Biology Markup Language (SBML), such a model would need to explicitly enumerate all state variables. The Kappa modelling language which we use supports representation of complexes without such enumeration. To conclude, we compare Kappa with a few other modelling languages and software tools that could also be used to represent and model the HOG system.","PeriodicalId":73143,"journal":{"name":"Genome informatics. International Conference on Genome Informatics","volume":"103 1","pages":"69-83"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80928254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Evaluation of DNA intramolecular interactions for nucleosome positioning in yeast. 酵母核小体定位中DNA分子内相互作用的评价。

Genome informatics. International Conference on Genome Informatics Pub Date : 2009-10-01

Michael Fernandez, Satoshi Fujii, Hidetoshi Kono, Akinori Sarai

引用次数: 0

Comparative analysis of aerobic and anaerobic prokaryotes to identify correlation between oxygen requirement and gene-gene functional association patterns. 好氧和厌氧原核生物的比较分析，以确定氧需求与基因-基因功能关联模式之间的相关性。

Genome informatics. International Conference on Genome Informatics Pub Date : 2009-10-01

Yaming Lin, Hongwei Wu

{"title":"Comparative analysis of aerobic and anaerobic prokaryotes to identify correlation between oxygen requirement and gene-gene functional association patterns.","authors":"Yaming Lin, Hongwei Wu","doi":"","DOIUrl":"","url":null,"abstract":"Activities of prokaryotes are pivotal in shaping the environment, and are also greatly influenced by the environment. With the substantial progress in genome and metagenome sequencing and the about-to-be-standardized ecological context information, environment-centric comparative genomics will complement species-centric comparative genomics, illuminating how environments have shaped and maintained prokaryotic diversities. In this paper we report our preliminary studies on the association analysis of a particular duo of genomic and ecological traits of prokaryotes--gene-gene functional association patterns vs. oxygen requirement conditions. We first establish a stochastic model to describe gene arrangements on chromosomes, based on which the functional association between genes are quantified. The gene-gene functional association measures are validated using biological process ontology and KEGG pathway annotations. Student's t-tests are then performed on the aerobic and anaerobic organisms to identify those gene pairs that exhibit different functional association patterns in the two different oxygen requirement conditions. As it is difficult to design and conduct biological experiments to validate those genome-environment association relationships that have resulted from long-term accumulative genome-environment interactions, we finally conduct computational validations to determine whether the oxygen requirement condition of an organism is predictable based on gene-gene functional association patterns. The reported study demonstrates the existence and significance of the association relationships between certain gene-gene functional association patterns and oxygen requirement conditions of prokaryotes, as well as the effectiveness of the adopted methodology for such association analysis.","PeriodicalId":73143,"journal":{"name":"Genome informatics. International Conference on Genome Informatics","volume":"23 1","pages":"72-84"},"PeriodicalIF":0.0,"publicationDate":"2009-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"28734943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0