Advance online publication
The latest research papers, published online ahead of print. These online versions are definitive and may be cited using the digital object identifier (DOI).
About advance online publicationResearch
Letters
Predicting PDZ domain–peptide interactions from primary sequences
Jiunn R Chen, Bryan H Chang, John E Allen, Michael A Stiffler & Gavin MacBeath
Published online: 17 August 2008; | doi:10.1038/nbt.1489
PDZ domains represent one of the largest families of interaction domains. Chen et al. develop a scoring matrix that enables prediction of peptide–PDZ domain interactions. Unlike previous methods, the model works to some extent for PDZ domains that were not part of the training set.
First Paragraph - | Full Text - Predicting PDZ domain–peptide interactions from primary sequences | PDF (628 KB) - Predicting PDZ domain–peptide interactions from primary sequences | Supplementary information
High-resolution metagenomics targets specific functional types in complex microbial communities
Marina G Kalyuzhnaya, Alla Lapidus, Natalia Ivanova, Alex C Copeland, Alice C McHardy, Ernest Szeto, Asaf Salamov, Igor V Grigoriev, Dominic Suciu, Samuel R Levine, Victor M Markowitz, Isidore Rigoutsos, Susannah G Tringe, David C Bruce, Paul M Richardson, Mary E Lidstrom & Ludmila Chistoserdova
Published online: 17 August 2008; | doi:10.1038/nbt.1488
Metagenomics, or shotgun sequencing of environmental DNA, is used to study complex microbial communities. Kalyuzhnaya et al. describe a method for targeting specific microbial subpopulations in environmental samples and use it to analyze microbes that metabolize C1 compounds.
First Paragraph - | Full Text - High-resolution metagenomics targets specific functional types in complex microbial communities | PDF (353 KB) - High-resolution metagenomics targets specific functional types in complex microbial communities | Supplementary information
Computational Biology
Analysis
Network-based prediction of human tissue-specific metabolism
Tomer Shlomi, Moran N Cabili, Markus J Herrgård, Bernhard Ø Palsson & Eytan Ruppin
Published online: 17 August 2008; | doi:10.1038/nbt.1487
Metabolic network modeling in multicellular organisms is confounded by the existence of multiple tissues with distinct metabolic functions. By integrating a genome-scale metabolic network with tissue-specific gene- and protein-expression data, Shlomi et al. adapt constraint-based approaches used for microorganisms to predicting metabolism in ten human tissues. Their computational approach should facilitate interpretation of expression data in the context of metabolic disorders.
Abstract - | Full Text - Network-based prediction of human tissue-specific metabolism | PDF (618 KB) - Network-based prediction of human tissue-specific metabolism | Supplementary information
Until print versions of AOP papers are published, they should be cited in the style "Author(s) Nature Biotechnology advance online publication, day month year (doi:10.1038/nbtXXXXX)". Once the print version (identical to the AOP) is published, it should be cited as follows: "Author(s) Nature Biotechnology volume, page (year); advance online publication, (doi:10.1038/nbtXXXXX)".
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