Classification of the states of human adaptive immune systems by analyzing immunoglobulin and t cell receptors using immunexplorer

Susanne Schaller; Johannes Weinberger; Raúl Jiménez-Heredia; Martin Danzer; Stephan M. Winkler

doi:10.1007/978-3-319-27340-2_38

Classification of the states of human adaptive immune systems by analyzing immunoglobulin and t cell receptors using immunexplorer

Susanne Schaller, Johannes Weinberger, Raúl Jiménez-Heredia, Martin Danzer, Stephan M. Winkler

Research Center Hagenberg

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

The behavior and actions of the human adaptive immune system and its key players, namely B and T cells, are often hard to understand in their entirety. We here present a workflow for modelling the states of adaptive immune systems by analyzing B and T cell receptor repertoires using next-generation sequencing data. For our workflow, we have blood and kidney tissues from diseased patients, who suffered from different kidney diseases (e.g., renal carcinoma), and healthy proband. A set of features based on clonal expansion and diversity of immunoglobulins and T cell receptor next-generation sequencing data, isolated from patients, are calculated. Using different machine learning methods such as support vector machines, random forests, artificial neural networks and genetic programming in HeuristicLab, we are able to classify and distinguish between healthy and diseased individuals up to 80% accuracy using ImmunExplorer.

Original language	English
Title of host publication	Computer Aided Systems Theory – EUROCAST 2015 - 15th International Conference, Revised Selected Papers
Editors	Franz Pichler, Roberto Moreno-Díaz, Alexis Quesada-Arencibia
Publisher	Springer
Pages	302-309
Number of pages	8
ISBN (Print)	9783319273396
DOIs	https://doi.org/10.1007/978-3-319-27340-2_38
Publication status	Published - 2015
Event	15th International Conference on Computer Aided Systems Theory, Eurocast 2015 - Las Palmas, Gran Canaria, Spain Duration: 8 Feb 2015 → 13 Feb 2015 http://eurocast2015.fulp.ulpgc.es/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9520
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th International Conference on Computer Aided Systems Theory, Eurocast 2015
Country/Territory	Spain
City	Las Palmas, Gran Canaria
Period	08.02.2015 → 13.02.2015
Internet address	http://eurocast2015.fulp.ulpgc.es/

Keywords

Clonality and diversity feature extraction
Heuristiclab
IG and TR immune repertoire
Immunexplorer
Machine learning

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-319-27340-2_38

Cite this

Schaller, S., Weinberger, J., Jiménez-Heredia, R., Danzer, M., & Winkler, S. M. (2015). Classification of the states of human adaptive immune systems by analyzing immunoglobulin and t cell receptors using immunexplorer. In F. Pichler, R. Moreno-Díaz, & A. Quesada-Arencibia (Eds.), Computer Aided Systems Theory – EUROCAST 2015 - 15th International Conference, Revised Selected Papers (pp. 302-309). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9520). Springer. https://doi.org/10.1007/978-3-319-27340-2_38

Schaller, Susanne ; Weinberger, Johannes ; Jiménez-Heredia, Raúl et al. / Classification of the states of human adaptive immune systems by analyzing immunoglobulin and t cell receptors using immunexplorer. Computer Aided Systems Theory – EUROCAST 2015 - 15th International Conference, Revised Selected Papers. editor / Franz Pichler ; Roberto Moreno-Díaz ; Alexis Quesada-Arencibia. Springer, 2015. pp. 302-309 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{0454c39f7fb8464d93752a88eee468d4,

title = "Classification of the states of human adaptive immune systems by analyzing immunoglobulin and t cell receptors using immunexplorer",

abstract = "The behavior and actions of the human adaptive immune system and its key players, namely B and T cells, are often hard to understand in their entirety. We here present a workflow for modelling the states of adaptive immune systems by analyzing B and T cell receptor repertoires using next-generation sequencing data. For our workflow, we have blood and kidney tissues from diseased patients, who suffered from different kidney diseases (e.g., renal carcinoma), and healthy proband. A set of features based on clonal expansion and diversity of immunoglobulins and T cell receptor next-generation sequencing data, isolated from patients, are calculated. Using different machine learning methods such as support vector machines, random forests, artificial neural networks and genetic programming in HeuristicLab, we are able to classify and distinguish between healthy and diseased individuals up to 80% accuracy using ImmunExplorer.",

keywords = "Clonality and diversity feature extraction, Heuristiclab, IG and TR immune repertoire, Immunexplorer, Machine learning",

author = "Susanne Schaller and Johannes Weinberger and Ra{\'u}l Jim{\'e}nez-Heredia and Martin Danzer and Winkler, {Stephan M.}",

note = "Funding Information: The work performed in this paper was done within ImmuneProfiler, a research project funded by the basic research funding program of the University of Applied Sciences Upper Austria. Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 15th International Conference on Computer Aided Systems Theory, Eurocast 2015 ; Conference date: 08-02-2015 Through 13-02-2015",

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doi = "10.1007/978-3-319-27340-2_38",

language = "English",

isbn = "9783319273396",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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editor = "Franz Pichler and Roberto Moreno-D{\'i}az and Alexis Quesada-Arencibia",

booktitle = "Computer Aided Systems Theory – EUROCAST 2015 - 15th International Conference, Revised Selected Papers",

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Schaller, S, Weinberger, J, Jiménez-Heredia, R, Danzer, M & Winkler, SM 2015, Classification of the states of human adaptive immune systems by analyzing immunoglobulin and t cell receptors using immunexplorer. in F Pichler, R Moreno-Díaz & A Quesada-Arencibia (eds), Computer Aided Systems Theory – EUROCAST 2015 - 15th International Conference, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9520, Springer, pp. 302-309, 15th International Conference on Computer Aided Systems Theory, Eurocast 2015, Las Palmas, Gran Canaria, Spain, 08.02.2015. https://doi.org/10.1007/978-3-319-27340-2_38

Classification of the states of human adaptive immune systems by analyzing immunoglobulin and t cell receptors using immunexplorer. / Schaller, Susanne; Weinberger, Johannes; Jiménez-Heredia, Raúl et al.
Computer Aided Systems Theory – EUROCAST 2015 - 15th International Conference, Revised Selected Papers. ed. / Franz Pichler; Roberto Moreno-Díaz; Alexis Quesada-Arencibia. Springer, 2015. p. 302-309 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9520).

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

TY - GEN

T1 - Classification of the states of human adaptive immune systems by analyzing immunoglobulin and t cell receptors using immunexplorer

AU - Schaller, Susanne

AU - Weinberger, Johannes

AU - Jiménez-Heredia, Raúl

AU - Danzer, Martin

AU - Winkler, Stephan M.

N1 - Funding Information: The work performed in this paper was done within ImmuneProfiler, a research project funded by the basic research funding program of the University of Applied Sciences Upper Austria. Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - The behavior and actions of the human adaptive immune system and its key players, namely B and T cells, are often hard to understand in their entirety. We here present a workflow for modelling the states of adaptive immune systems by analyzing B and T cell receptor repertoires using next-generation sequencing data. For our workflow, we have blood and kidney tissues from diseased patients, who suffered from different kidney diseases (e.g., renal carcinoma), and healthy proband. A set of features based on clonal expansion and diversity of immunoglobulins and T cell receptor next-generation sequencing data, isolated from patients, are calculated. Using different machine learning methods such as support vector machines, random forests, artificial neural networks and genetic programming in HeuristicLab, we are able to classify and distinguish between healthy and diseased individuals up to 80% accuracy using ImmunExplorer.

AB - The behavior and actions of the human adaptive immune system and its key players, namely B and T cells, are often hard to understand in their entirety. We here present a workflow for modelling the states of adaptive immune systems by analyzing B and T cell receptor repertoires using next-generation sequencing data. For our workflow, we have blood and kidney tissues from diseased patients, who suffered from different kidney diseases (e.g., renal carcinoma), and healthy proband. A set of features based on clonal expansion and diversity of immunoglobulins and T cell receptor next-generation sequencing data, isolated from patients, are calculated. Using different machine learning methods such as support vector machines, random forests, artificial neural networks and genetic programming in HeuristicLab, we are able to classify and distinguish between healthy and diseased individuals up to 80% accuracy using ImmunExplorer.

KW - Clonality and diversity feature extraction

KW - Heuristiclab

KW - IG and TR immune repertoire

KW - Immunexplorer

KW - Machine learning

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U2 - 10.1007/978-3-319-27340-2_38

DO - 10.1007/978-3-319-27340-2_38

M3 - Conference contribution

AN - SCOPUS:84952319514

SN - 9783319273396

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 302

EP - 309

BT - Computer Aided Systems Theory – EUROCAST 2015 - 15th International Conference, Revised Selected Papers

A2 - Pichler, Franz

A2 - Moreno-Díaz, Roberto

A2 - Quesada-Arencibia, Alexis

PB - Springer

T2 - 15th International Conference on Computer Aided Systems Theory, Eurocast 2015

Y2 - 8 February 2015 through 13 February 2015

ER -

Schaller S, Weinberger J, Jiménez-Heredia R, Danzer M, Winkler SM. Classification of the states of human adaptive immune systems by analyzing immunoglobulin and t cell receptors using immunexplorer. In Pichler F, Moreno-Díaz R, Quesada-Arencibia A, editors, Computer Aided Systems Theory – EUROCAST 2015 - 15th International Conference, Revised Selected Papers. Springer. 2015. p. 302-309. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-27340-2_38

Classification of the states of human adaptive immune systems by analyzing immunoglobulin and t cell receptors using immunexplorer

Abstract

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Keywords

UN SDGs

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