A comparative analysis of phenotypes derived from genes or biomedical literature in COVID-19

Sophie Steenson; Christopher Hawthorne; Guillermo Lopez-Campos

doi:10.3233/SHTI220283

A comparative analysis of phenotypes derived from genes or biomedical literature in COVID-19

Sophie Steenson, Christopher Hawthorne, Guillermo Lopez-Campos

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

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Abstract

Since the emergence of SARS-CoV-2 in November 2019, there has been an exponential production of literature due to worldwide efforts to understand the interactions between the virus and the human body. Using an "in-house" developed script we retrieved gene annotations and identified phenotype enrichments. Human Phenotype Ontology terms were retrieved from the literature using the Onassis R package. This produced both disease-gene and disease-phenotype data as well as data for gene-phenotype interactions. Overall, we retrieved 181 human phenotypes that were identified by both approaches. Further in-depth analysis of these relationships could provide further insights in the molecular mechanisms related with the observed phenotypes, answers and hypotheses for key concepts within COVID-19 research.

Original language	English
Title of host publication	MEDINFO 2021: One world, one health – global partnership for digital innovation
Editors	Paula Otero, Philip Scott, Susan Z. Martin, Elaine Huesing
Publisher	IOS Press
Pages	1092-1093
Number of pages	2
ISBN (Electronic)	9781643682655
ISBN (Print)	9781643682648
DOIs	https://doi.org/10.3233/SHTI220283
Publication status	Published - 06 Jun 2022

Publication series

Name	Studies in Health Technology and Informatics
Volume	290
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Keywords

COVID-19
Computational Biology
SARS-CoV-2 - genetics
Phenotype
Humans
Data Mining

UN SDGs

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

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10.3233/SHTI220283Licence: CC BY-NC

A comparative analysis of phenotypes derived from genes or biomedical literature in COVID-19
Copyright 2022 International Medical Informatics Association (IMIA) and IOS Press. This is an open access Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits use, distribution and reproduction for non-commercial purposes, provided the author and source are cited.
Final published version, 209 KBLicence: CC BY-NC

Investigation and development of novel exposome informatics methodologies and solutions for the analysis and integration of phenome, genome and exposome data
Hawthorne, C. (Author), Lopez Campos, G. (Supervisor), Simpson, D. (Supervisor) & Devereux, B. (Supervisor), Dec 2023
Student thesis: Doctoral Thesis › Doctor of Philosophy

Cite this

Steenson, S., Hawthorne, C., & Lopez-Campos, G. (2022). A comparative analysis of phenotypes derived from genes or biomedical literature in COVID-19. In P. Otero, P. Scott, S. Z. Martin, & E. Huesing (Eds.), MEDINFO 2021: One world, one health – global partnership for digital innovation (pp. 1092-1093). (Studies in Health Technology and Informatics; Vol. 290). IOS Press. https://doi.org/10.3233/SHTI220283

Steenson, Sophie ; Hawthorne, Christopher ; Lopez-Campos, Guillermo. / A comparative analysis of phenotypes derived from genes or biomedical literature in COVID-19. MEDINFO 2021: One world, one health – global partnership for digital innovation. editor / Paula Otero ; Philip Scott ; Susan Z. Martin ; Elaine Huesing. IOS Press, 2022. pp. 1092-1093 (Studies in Health Technology and Informatics).

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Steenson, S, Hawthorne, C & Lopez-Campos, G 2022, A comparative analysis of phenotypes derived from genes or biomedical literature in COVID-19. in P Otero, P Scott, SZ Martin & E Huesing (eds), MEDINFO 2021: One world, one health – global partnership for digital innovation. Studies in Health Technology and Informatics, vol. 290, IOS Press, pp. 1092-1093. https://doi.org/10.3233/SHTI220283

A comparative analysis of phenotypes derived from genes or biomedical literature in COVID-19. / Steenson, Sophie; Hawthorne, Christopher; Lopez-Campos, Guillermo.
MEDINFO 2021: One world, one health – global partnership for digital innovation. ed. / Paula Otero; Philip Scott; Susan Z. Martin; Elaine Huesing. IOS Press, 2022. p. 1092-1093 (Studies in Health Technology and Informatics; Vol. 290).

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

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AU - Hawthorne, Christopher

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N2 - Since the emergence of SARS-CoV-2 in November 2019, there has been an exponential production of literature due to worldwide efforts to understand the interactions between the virus and the human body. Using an "in-house" developed script we retrieved gene annotations and identified phenotype enrichments. Human Phenotype Ontology terms were retrieved from the literature using the Onassis R package. This produced both disease-gene and disease-phenotype data as well as data for gene-phenotype interactions. Overall, we retrieved 181 human phenotypes that were identified by both approaches. Further in-depth analysis of these relationships could provide further insights in the molecular mechanisms related with the observed phenotypes, answers and hypotheses for key concepts within COVID-19 research.

AB - Since the emergence of SARS-CoV-2 in November 2019, there has been an exponential production of literature due to worldwide efforts to understand the interactions between the virus and the human body. Using an "in-house" developed script we retrieved gene annotations and identified phenotype enrichments. Human Phenotype Ontology terms were retrieved from the literature using the Onassis R package. This produced both disease-gene and disease-phenotype data as well as data for gene-phenotype interactions. Overall, we retrieved 181 human phenotypes that were identified by both approaches. Further in-depth analysis of these relationships could provide further insights in the molecular mechanisms related with the observed phenotypes, answers and hypotheses for key concepts within COVID-19 research.

KW - COVID-19

KW - Computational Biology

KW - SARS-CoV-2 - genetics

KW - Phenotype

KW - Humans

KW - Data Mining

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M3 - Chapter (peer-reviewed)

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SN - 9781643682648

T3 - Studies in Health Technology and Informatics

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EP - 1093

BT - MEDINFO 2021: One world, one health – global partnership for digital innovation

A2 - Otero, Paula

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A2 - Martin, Susan Z.

A2 - Huesing, Elaine

PB - IOS Press

ER -

Steenson S, Hawthorne C, Lopez-Campos G. A comparative analysis of phenotypes derived from genes or biomedical literature in COVID-19. In Otero P, Scott P, Martin SZ, Huesing E, editors, MEDINFO 2021: One world, one health – global partnership for digital innovation. IOS Press. 2022. p. 1092-1093. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI220283

A comparative analysis of phenotypes derived from genes or biomedical literature in COVID-19

Abstract

Publication series

Keywords

UN SDGs

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Student theses

Investigation and development of novel exposome informatics methodologies and solutions for the analysis and integration of phenome, genome and exposome data

Cite this