| 1. |
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| 2. |
- Albers, Stevan C., et al.
(författare)
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The rise and fall of innovation in biofuels
- 2016
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Ingår i: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 34:8, s. 814-821
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Tidskriftsartikel (refereegranskat)
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| 3. |
- Almagro Armenteros, José Juan, et al.
(författare)
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SignalP 5.0 improves signal peptide predictions using deep neural networks
- 2019
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Ingår i: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 37:4, s. 420-423
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Tidskriftsartikel (refereegranskat)abstract
- Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish between various types of signal peptides. We present a deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs.
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| 4. |
- Ameur, Adam
(författare)
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Goodbye reference, hello genome graphs
- 2019
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Ingår i: Nature Biotechnology. - : NATURE PUBLISHING GROUP. - 1087-0156 .- 1546-1696. ; 37:8, s. 866-868
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 5. |
- Amit, Ido, et al.
(författare)
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Voices of biotech
- 2016
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Ingår i: Nature Biotechnology. - : Nature Publishing Group. - 1087-0156 .- 1546-1696. ; 34:3, s. 270-275
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Tidskriftsartikel (refereegranskat)
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| 6. |
- Babaei, Parizad, 1990, et al.
(författare)
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Challenges in modeling the human gut microbiome
- 2018
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Ingår i: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 36:8, s. 682-686
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 7. |
- Boekel, Jorrit, et al.
(författare)
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Multi-omic data analysis using Galaxy
- 2015
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Ingår i: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 33:2, s. 137-9
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Tidskriftsartikel (refereegranskat)
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| 8. |
- Bosley, Katrine S, et al.
(författare)
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CRISPR germline engineering : the community speaks
- 2015
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Ingår i: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 33:5, s. 478-486
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Tidskriftsartikel (refereegranskat)
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| 9. |
- Bowers, Robert M., et al.
(författare)
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Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea
- 2017
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Ingår i: Nature Biotechnology. - : NATURE PUBLISHING GROUP. - 1087-0156 .- 1546-1696. ; 35:8, s. 725-731
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Tidskriftsartikel (refereegranskat)abstract
- We present two standards developed by the Genomic Standards Consortium (GSC) for reporting bacterial and archaeal genome sequences. Both are extensions of the Minimum Information about Any (x) Sequence (MIxS). The standards are the Minimum Information about a Single Amplified Genome (MISAG) and the Minimum Information about a Metagenome-Assembled Genome (MIMAG), including, but not limited to, assembly quality, and estimates of genome completeness and contamination. These standards can be used in combination with other GSC checklists, including the Minimum Information about a Genome Sequence (MIGS), Minimum Information about a Metagenomic Sequence (MIMS), and Minimum Information about a Marker Gene Sequence (MIMARKS). Community-wide adoption of MISAG and MIMAG will facilitate more robust comparative genomic analyses of bacterial and archaeal diversity.
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| 10. |
- Brunk, Elizabeth, et al.
(författare)
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Recon3D enables a three-dimensional view of gene variation in human metabolism
- 2018
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Ingår i: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 36:3, s. 272-281
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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