Title |
An integrated approach for genome annotation of the eukaryotic thermophile Chaetomium thermophilum
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Published in |
Nucleic Acids Research, November 2014
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DOI | 10.1093/nar/gku1147 |
Pubmed ID | |
Authors |
Thomas Bock, Wei-Hua Chen, Alessandro Ori, Nayab Malik, Noella Silva-Martin, Jaime Huerta-Cepas, Sean T. Powell, Panagiotis L. Kastritis, Georgy Smyshlyaev, Ivana Vonkova, Joanna Kirkpatrick, Tobias Doerks, Leo Nesme, Jochen Baßler, Martin Kos, Ed Hurt, Teresa Carlomagno, Anne-Claude Gavin, Orsolya Barabas, Christoph W. Müller, Vera van Noort, Martin Beck, Peer Bork |
Abstract |
The thermophilic fungus Chaetomium thermophilum holds great promise for structural biology. To increase the efficiency of its biochemical and structural characterization and to explore its thermophilic properties beyond those of individual proteins, we obtained transcriptomics and proteomics data, and integrated them with computational annotation methods and a multitude of biochemical experiments conducted by the structural biology community. We considerably improved the genome annotation of Chaetomium thermophilum and characterized the transcripts and expression of thousands of genes. We furthermore show that the composition and structure of the expressed proteome of Chaetomium thermophilum is similar to its mesophilic relatives. Data were deposited in a publicly available repository and provide a rich source to the structural biology community. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Spain | 2 | 40% |
Venezuela, Bolivarian Republic of | 1 | 20% |
United States | 1 | 20% |
Unknown | 1 | 20% |
Demographic breakdown
Type | Count | As % |
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Scientists | 4 | 80% |
Members of the public | 1 | 20% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Germany | 4 | 3% |
United Kingdom | 1 | <1% |
Unknown | 113 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 29 | 25% |
Student > Ph. D. Student | 28 | 24% |
Student > Bachelor | 14 | 12% |
Student > Master | 13 | 11% |
Student > Doctoral Student | 6 | 5% |
Other | 13 | 11% |
Unknown | 15 | 13% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 44 | 37% |
Agricultural and Biological Sciences | 42 | 36% |
Computer Science | 5 | 4% |
Chemistry | 4 | 3% |
Unspecified | 2 | 2% |
Other | 5 | 4% |
Unknown | 16 | 14% |