
Rainer König, Gunnar Schramm, Marcus Oswald, Hanna Seitz, Sebastian Sager, Marc Zapatka, Gerhard Reinelt and Roland Eils
Discovering functional gene expression patterns in the metabolic network of Escherichia coli with wavelets transforms
BMC Bioinformatics 2006, 7:119
[PDF][Web Site]
・マイクロアレイデータより遺伝子間のネットワークを推定する。具体的には、E.coliのaerobic/anaerobic環境下のデータより、metabolicのネットワークを推定する。
・処理「We mapped gene expression data from E. coli under aerobic and anaerobic conditions onto the enzymatic reaction nodes of its metabolic network.」
・マイクロアレイ研究のまとめ「However, the advent of DNA microarrays has allowed us to explore a major subset or all genes of an organism under a variety of conditions such as alternative treatments, mutants, developmental stages and time points. For example, the technique enables us to classify tumor samples [5], to define small sets of potential marker genes to distinguish leukemias [6], and to discover regulatory mechanisms [7,8]. E.g., without prior information, the structure and function of the network that regulates the SOS pathway in E.coli could be elucidated with transcription profiles [9]. Furthermore, physical and chemical interaction data of proteins have been integrated. Knowledge of protein-protein interaction from high-throughput techniques [10] was applied to analyse gene expression data and revealed novel regulatory circuits [11]. Moreover, interaction knowledge from the biochemical network has been used to support the clustering procedure for gene expression profiles of yeast [12,13].」
・まとめ「Hence, we elucidated some interesting and relevant subgraphs of the metabolic network that showed necessary changes during the aerobic - anaerobic shift. But note, that such findings may not represent the entire regulatory change during such a shift of the metabolic network.」
・「Such a "Haar" wavelet transform can be regarded as a low pass filter when calculating the mean, and a high pass filter when calculating the difference between neighbouring value pairs.」
・遺伝子ネットワークの図は、生物学の知識がないのでさっぱり分からない。
・ウェーブレット変換に関する記述はほとんどなし。
Discovering functional gene expression patterns in the metabolic network of Escherichia coli with wavelets transforms
BMC Bioinformatics 2006, 7:119
[PDF][Web Site]
・マイクロアレイデータより遺伝子間のネットワークを推定する。具体的には、E.coliのaerobic/anaerobic環境下のデータより、metabolicのネットワークを推定する。
・処理「We mapped gene expression data from E. coli under aerobic and anaerobic conditions onto the enzymatic reaction nodes of its metabolic network.」
・マイクロアレイ研究のまとめ「However, the advent of DNA microarrays has allowed us to explore a major subset or all genes of an organism under a variety of conditions such as alternative treatments, mutants, developmental stages and time points. For example, the technique enables us to classify tumor samples [5], to define small sets of potential marker genes to distinguish leukemias [6], and to discover regulatory mechanisms [7,8]. E.g., without prior information, the structure and function of the network that regulates the SOS pathway in E.coli could be elucidated with transcription profiles [9]. Furthermore, physical and chemical interaction data of proteins have been integrated. Knowledge of protein-protein interaction from high-throughput techniques [10] was applied to analyse gene expression data and revealed novel regulatory circuits [11]. Moreover, interaction knowledge from the biochemical network has been used to support the clustering procedure for gene expression profiles of yeast [12,13].」
・まとめ「Hence, we elucidated some interesting and relevant subgraphs of the metabolic network that showed necessary changes during the aerobic - anaerobic shift. But note, that such findings may not represent the entire regulatory change during such a shift of the metabolic network.」
・「Such a "Haar" wavelet transform can be regarded as a low pass filter when calculating the mean, and a high pass filter when calculating the difference between neighbouring value pairs.」
・遺伝子ネットワークの図は、生物学の知識がないのでさっぱり分からない。
・ウェーブレット変換に関する記述はほとんどなし。
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