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Computational Analysis Methods for B...

Gill, Kirandeep,

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Computational Analysis Methods for B Cell Receptor Repertoires and Comprehensive Benchmarking of Antibody Sequence Analysis Tools /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Computational Analysis Methods for B Cell Receptor Repertoires and Comprehensive Benchmarking of Antibody Sequence Analysis Tools // Kirandeep Gill.
Author:	Gill, Kirandeep,
Description:	1 electronic resource (120 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-11, Section: B.
Contained By:	Dissertations Abstracts International86-11B.
Subject:	Bioinformatics. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=32063731
ISBN:	9798314843062

Computational Analysis Methods for B Cell Receptor Repertoires and Comprehensive Benchmarking of Antibody Sequence Analysis Tools /
Gill, Kirandeep,

Computational Analysis Methods for B Cell Receptor Repertoires and Comprehensive Benchmarking of Antibody Sequence Analysis Tools /Kirandeep Gill. - 1 electronic resource (120 pages)

Source: Dissertations Abstracts International, Volume: 86-11, Section: B.

B cell receptor (BCR) repertoire constitutes the diverse range of BCRs expressed by an individual's total B cell population. B cells are responsible for a humoral immune response by producing antibodies against foreign antigens. Computational analysis methods to understand the diverse immune repertoire and its response to diseases are rapidly evolving. These analysis methods reveal the underlying mechanisms for healthy individuals and various diseases. These methods depend on the choice of the analysis tools used for annotation of antibody gene sequences. In this dissertation, I describe a comprehensive benchmarking of three commonly used antibody gene sequence annotation tools and the construction of an ensemble annotation method. Without any ground truth dataset that can be used for comparison, we developed a set of consensus sequences as our silver standard which are simulated for somatic hypermutations and their performance fall-off calculated. In the second part of my dissertation, I develop analysis methods that measure quantitative features of the B cell receptor repertoire. I then apply these analysis methods to study allergic food sensitization in children with atopic dermatitis. I propose a novel score, which we name the Immune Repertoire in Atopic Disease (IRAD) score, that could be used to measure the severity of AD and aid in disease diagnosis and risk stratification.

English

ISBN: 9798314843062Subjects--Topical Terms:

553671
Bioinformatics.
Subjects--Index Terms:

B cell receptor repertoire

Computational Analysis Methods for B Cell Receptor Repertoires and Comprehensive Benchmarking of Antibody Sequence Analysis Tools /
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520 $a B cell receptor (BCR) repertoire constitutes the diverse range of BCRs expressed by an individual's total B cell population. B cells are responsible for a humoral immune response by producing antibodies against foreign antigens. Computational analysis methods to understand the diverse immune repertoire and its response to diseases are rapidly evolving. These analysis methods reveal the underlying mechanisms for healthy individuals and various diseases. These methods depend on the choice of the analysis tools used for annotation of antibody gene sequences. In this dissertation, I describe a comprehensive benchmarking of three commonly used antibody gene sequence annotation tools and the construction of an ensemble annotation method. Without any ground truth dataset that can be used for comparison, we developed a set of consensus sequences as our silver standard which are simulated for somatic hypermutations and their performance fall-off calculated. In the second part of my dissertation, I develop analysis methods that measure quantitative features of the B cell receptor repertoire. I then apply these analysis methods to study allergic food sensitization in children with atopic dermatitis. I propose a novel score, which we name the Immune Repertoire in Atopic Disease (IRAD) score, that could be used to measure the severity of AD and aid in disease diagnosis and risk stratification.
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650 4 $a Cellular biology. $3 3172791
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