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Molecular Signal Processing
Bioorganic Chemistry
Biochemistry of Plant Interactions
Cell and Metabolic Biology
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Publications - Cell and Metabolic Biology
Books and chapters
Searching and mining nuclear magnetic resonance (NMR)-spectra of naturally occurring substances is an important task to investigate new potentially useful chemical compounds. Multi-dimensional NMR-spectra are relational objects like documents, but consists of continuous multi-dimensional points called peaks instead of words. We develop several mappings from continuous NMR-spectra to discrete text-like data. With the help of those mappings any text retrieval method can be applied. We evaluate the performance of two retrieval methods, namely the standard vector space model and probabilistic latent semantic indexing (PLSI). PLSI learns hidden topics in the data, which is in case of 2D-NMR data interesting in its owns rights. Additionally, we develop and evaluate a simple direct similarity function, which can detect duplicates of NMR-spectra. Our experiments show that the vector space model as well as PLSI, which are both designed for text data created by humans, can effectively handle the mapped NMR-data originating from natural products. Additionally, PLSI is able to find meaningful ”topics” in the NMR-data.
Books and chapters
Searching and mining nuclear magnetic resonance (NMR)-spectra of naturally occurring products is an important task to investigate new potentially useful chemical compounds. We develop a set-based similarity function, which, however, does not sufficiently capture more abstract aspects of similarity. NMR-spectra are like documents, but consists of continuous multi-dimensional points instead of words. Probabilistic semantic indexing (PLSI) is an retrieval method, which learns hidden topics. We develop several mappings from continuous NMR-spectra to discrete text-like data. The new mappings include redundancies into the discrete data, which proofs helpful for the PLSI-model used afterwards. Our experiments show that PLSI, which is designed for text data created by humans, can effectively handle the mapped NMR-data originating from natural products. Additionally, PLSI combined with the new mappings is able to find meaningful ”topics” in the NMR-data.
Publications
In addition to a previously characterized 13-lipoxygenase of 100 kDa encoded by LOX2:Hv:1 [Vörös et al., Eur. J. Biochem. 251 (1998), 36 44], two fulllength cDNAs (LOX2:Hv:2, LOX2:Hv:3) were isolated from barley leaves (Hordeum vulgare cv. Salome) and characterized. Both of them encode 13-lipoxygenases with putative target sequences for chloroplast import. Immunogold labeling revealed preferential, if not exclusive, localization of lipoxygenase proteins in the stroma. The ultrastructure of the chloroplast was dramatically altered following methyl jasmonate treatment, indicated by a loss of thylakoid membranes, decreased number of stacks and appearance of numerous osmiophilic globuli. The three 13-lipoxygenases are differentially expressed during treatment with jasmonate, salicylate, glucose or sorbitol. Metabolite profiling of free linolenic acid and free linoleic acid, the substrates of lipoxygenases, in water floated or jasmonatetreated leaves revealed preferential accumulation of linolenic acid. Remarkable amounts of free 9- as well as 13-hydroperoxy linolenic acid were found. In addition, metabolites of these hydroperoxides, such as the hydroxy derivatives and the respective aldehydes, appeared following methyl jasmonate treatment. These findings were substantiated by metabolite profiling of isolated chloroplasts, and subfractions including the envelope, the stroma and the thylakoids, indicating a preferential occurrence of lipoxygenasederived products in the stroma and in the envelope. These data revealed jasmonateinduced activation of the hydroperoxide lyase and reductase branch within the lipoxygenase pathway and suggest differential activity of the three 13-lipoxygenases under different stress conditions.
This page was last modified on 27 Jan 2025 .
