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Mar 3, 2023 -
Machine Learning Texture Optimization
Plain Text - 1.0 KB - MD5: 389bfc2f1a11e6e5d5229657a35eafb9
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Mar 3, 2023 -
Machine Learning Texture Optimization
Tab-Delimited - 14.1 MB - MD5: ba4bc1b2c58220469b88aa09f1397912
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Mar 3, 2023 -
Machine Learning Texture Optimization
Comma Separated Values - 403.7 KB - MD5: 4d27879770d10ce970acac13c54f02ff
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Mar 3, 2023 -
Machine Learning Texture Optimization
Jupyter Notebook - 10.0 KB - MD5: 780a3e6bdf582afd7db34856f5d00922
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Mar 3, 2023 -
Machine Learning Texture Optimization
Tab-Delimited - 15.9 MB - MD5: 554f247895d7f564102182f9d752d2f0
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Mar 3, 2023 -
Machine Learning Texture Optimization
Tab-Delimited - 514.3 KB - MD5: ed2ab79ec146027393b0a7894fb383c7
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Plain Text - 3.3 KB - MD5: 9bcd61f1318ea91f1dae36a2463b5c4c
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RAR Archive - 299.1 MB - MD5: ae7edef5e9e9fd788d95cbcd7cb30374
For the genomes downloaded from SRA database (raw data; without assembled version available), assembly was performed using SPAdes Genome Assembler software v.3.15.4 (Bankevich et al. 2012), using default parameters. |
RAR Archive - 1.2 GB - MD5: 7cd4ab27f7ed6e9c56b22b118fa8cb37
The 661 assembled genomes were annotated using AUGUSTUS software v.3.4.0 (Stanke and Morgenstern 2005), considering 16 different pre-trained models, chosen as belonging to the Ascomycota phyla (11) or the Basidiomycota phyla (5): Ascomycota – S. cerevisiae S288c, C. albicans, Mey... |
RAR Archive - 889.4 MB - MD5: 90a5a5170220edf89555cc8702e0ee97
A consensus proteome database was prepared by considering the 530 complete genomes (from 134 species) that passed the quality control. |