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See detailRecon3D enables a three-dimensional view of gene variation in human metabolism.
Brunk, Elizabeth; Sahoo, Swagatika; Zielinski, Daniel C. et al

in Nature biotechnology (2018), 36(3), 272-281

Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein ... [more ▼]

Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life. [less ▲]

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See detailGeneration of genome-scale metabolic reconstructions for 773 members of the human gut microbiota
Magnusdottir, Stefania UL; Heinken, Almut Katrin UL; Kutt, Laura et al

in Nature Biotechnology (2016)

Genome-scale metabolic models derived from human gut metagenomic data can be used as a framework to elucidate how microbial communities modulate human metabolism and health. We present AGORA (assembly of ... [more ▼]

Genome-scale metabolic models derived from human gut metagenomic data can be used as a framework to elucidate how microbial communities modulate human metabolism and health. We present AGORA (assembly of gut organisms through reconstruction and analysis), a resource of genome-scale metabolic reconstructions semi-automatically generated for 773 human gut bacteria. Using this resource, we identified a defined growth medium for Bacteroides caccae ATCC 34185. We also showed that interactions among modeled species depend on both the metabolic potential of each species and the nutrients available. AGORA reconstructions can integrate either metagenomic or 16S rRNA sequencing data sets to infer the metabolic diversity of microbial communities. AGORA reconstructions could provide a starting point for the generation of high-quality, manually curated metabolic reconstructions. AGORA is fully compatible with Recon 2, a comprehensive metabolic reconstruction of human metabolism, which will facilitate studies of host–microbiome interactions. [less ▲]

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See detailCrowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression
Küffner, Robert; Zach, Neta; Norel, Raquel et al

in Nature Biotechnology (2015), 33(1), 51-57

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with substantial heterogeneity in its clinical presentation. This makes diagnosis and effective treatment difficult, so better ... [more ▼]

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with substantial heterogeneity in its clinical presentation. This makes diagnosis and effective treatment difficult, so better tools for estimating disease progression are needed. Here, we report results from the DREAM-Phil Bowen ALS Prediction Prize4Life challenge. In this crowdsourcing competition, competitors developed algorithms for the prediction of disease progression of 1,822 ALS patients from standardized, anonymized phase 2/3 clinical trials. The two best algorithms outperformed a method designed by the challenge organizers as well as predictions by ALS clinicians. We estimate that using both winning algorithms in future trial designs could reduce the required number of patients by at least 20%. The DREAM-Phil Bowen ALS Prediction Prize4Life challenge also identified several potential nonstandard predictors of disease progression including uric acid, creatinine and surprisingly, blood pressure, shedding light on ALS pathobiology. This analysis reveals the potential of a crowdsourcing competition that uses clinical trial data for accelerating ALS research and development. [less ▲]

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See detailA unified test of linkage analysis and rare-variant association for analysis of pedigree sequence data.
Hu, Hao; Roach, Jared C.; Coon, Hilary et al

in Nature Biotechnology (2014), 32(7), 663-669

High-throughput sequencing of related individuals has become an important tool for studying human disease. However, owing to technical complexity and lack of available tools, most pedigree-based ... [more ▼]

High-throughput sequencing of related individuals has become an important tool for studying human disease. However, owing to technical complexity and lack of available tools, most pedigree-based sequencing studies rely on an ad hoc combination of suboptimal analyses. Here we present pedigree-VAAST (pVAAST), a disease-gene identification tool designed for high-throughput sequence data in pedigrees. pVAAST uses a sequence-based model to perform variant and gene-based linkage analysis. Linkage information is then combined with functional prediction and rare variant case-control association information in a unified statistical framework. pVAAST outperformed linkage and rare-variant association tests in simulations and identified disease-causing genes from whole-genome sequence data in three human pedigrees with dominant, recessive and de novo inheritance patterns. The approach is robust to incomplete penetrance and locus heterogeneity and is applicable to a wide variety of genetic traits. pVAAST maintains high power across studies of monogenic, high-penetrance phenotypes in a single pedigree to highly polygenic, common phenotypes involving hundreds of pedigrees. [less ▲]

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See detailA community-driven global reconstruction of human metabolism.
Thiele, Ines UL; Swainston, N.; Fleming, Ronan MT UL et al

in Nature Biotechnology (2013), 31

Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus ‘metabolic reconstruction’, which ... [more ▼]

Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus ‘metabolic reconstruction’, which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ~2× more reactions and ~1.7× more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type–specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/. [less ▲]

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See detailWhat is flux balance analysis?
Orth, Jeffrey D.; Thiele, Ines UL; Palsson, Bernhard O.

in Nature Biotechnology (2010), 28(3), 245-8

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See detailReflect: augmented browsing for the life scientist
Pafilis, Evangelos; O'Donoghue, Sean I.; Jensen, Lars J. et al

in Nature Biotechnology (2009), 27(6), 508-510

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See detailA framework for designing transgenic crops - science, safety, and citizen’s concerns.
König, Ariane UL

in Nature Biotechnology (2003), 21(11), 1274-1279

Detailed reference viewed: 123 (6 UL)