search query: @instructor Saramäki, Jari / total: 12
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| Author: | Aggarwal, Kunal |
| Title: | T-Cell Receptor Diversity in the Human Immune System |
| Publication type: | Master's thesis |
| Publication year: | 2015 |
| Pages: | v + 39 s. + liitt. 9 Language: eng |
| Department/School: | Perustieteiden korkeakoulu |
| Main subject: | Computational and Systems Biology (T-61) |
| Supervisor: | Lähdesmäki, Harri ; Aurell, Erik |
| Instructor: | Saramäki, Jari |
| Electronic version URL: | http://urn.fi/URN:NBN:fi:aalto-201509184438 |
| Location: | P1 Ark Aalto 3009 | Archive |
| Keywords: | T-cell receptors immune diversity recombination parametric and non-parametric models kigh-throughput sequencing |
| Abstract (eng): | T-Cell Receptors are heterodimeric molecules composed of two hyper-variable protein chains. TCR Diversity is widely recognized as a direct measure of immune competence as it quantifies the variety of foreign antigens our immune system can recognize, and hence act upon. TCR diversity is generated by V(D)J recombination, a random process which rearranges variable (V), joining (J) and sometimes also diversity (D) segments of the gene encoding the antigen-binding region of the TCR. With the advent of high-throughput sequencing technology it is now possible to sequence a very large number of cells for these genes. However the immune cell count in any healthy individual is still beyond the currently feasible limits for sequencing and thus it requires that the total population diversity be estimated from a sample. Here, state-of-the-art approaches are used to model the sample diversity from millions of cells from thymus tissues. The population density is then estimated based on these models. Both parametric and non-parametric approaches are considered. |
| ED: | 2015-09-27 |
INSSI record number: 52155
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