Article
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Mendeley readers
| Chapter title |
Kinetic Analysis of Amyloid Formation
|
|---|---|
| Chapter number | 12 |
| Book title |
Amyloid Proteins
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7816-8_12 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7815-1, 978-1-4939-7816-8
|
| Authors |
Georg Meisl, Thomas C. T. Michaels, Sara Linse, Tuomas P. J. Knowles |
| Abstract |
The formation of amyloid fibrils is a central phenomenon in the progressive pathology of many neurodegenerative diseases, as well as in the fabrication of functional materials. Several different molecular processes acting in concert are responsible for the formation of amyloid fibrils from monomeric protein in solution. Here, we describe a method to determine which microscopic processes drive the overall formation of fibrils by using chemical kinetics in combination with systematic experimental datasets analysed in a global manner. We outline general concepts for obtaining suitable kinetic data and detail the key stages of data analysis, from quality control to the verification of a specific mechanism of aggregation. |
Mendeley readers
The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 5% |
| Spain | 1 | 1% |
| Lithuania | 1 | 1% |
| Unknown | 71 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 17% |
| Researcher | 10 | 13% |
| Student > Doctoral Student | 8 | 10% |
| Student > Master | 7 | 9% |
| Student > Bachelor | 6 | 8% |
| Other | 19 | 25% |
| Unknown | 14 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 18 | 23% |
| Agricultural and Biological Sciences | 15 | 19% |
| Chemistry | 10 | 13% |
| Medicine and Dentistry | 5 | 6% |
| Physics and Astronomy | 3 | 4% |
| Other | 10 | 13% |
| Unknown | 16 | 21% |