Online Tools for Teaching Cancer Bioinformatics

ABSTRACT The rise of deep molecular characterization with omics data as a standard in biological sciences has highlighted a need for expanded instruction in bioinformatics curricula. Many large biology data sets are publicly available and offer an incredible opportunity for educators to help student...

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Autores principales:	Mason D. Taylor, Bryn Mendenhall, Calvin S. Woods, Madeline E. Rasband, Milene C. Vallejo, Elizabeth G. Bailey, Samuel H. Payne
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2021
Materias:	cancer genomics proteomics classroom teaching online modules Python Special aspects of education LC8-6691 Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/8f0d074b4ff1421383e481c010daf471
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spelling	oai:doaj.org-article:8f0d074b4ff1421383e481c010daf4712021-11-15T15:04:51ZOnline Tools for Teaching Cancer Bioinformatics10.1128/jmbe.00167-211935-78851935-7877https://doaj.org/article/8f0d074b4ff1421383e481c010daf4712021-09-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/jmbe.00167-21https://doaj.org/toc/1935-7877https://doaj.org/toc/1935-7885ABSTRACT The rise of deep molecular characterization with omics data as a standard in biological sciences has highlighted a need for expanded instruction in bioinformatics curricula. Many large biology data sets are publicly available and offer an incredible opportunity for educators to help students explore biological phenomena with computational tools, including data manipulation, visualization, and statistical assessment. However, logistical barriers to data access and integration often complicate their use in undergraduate education. Here, we present a cancer bioinformatics module that is designed to overcome these barriers through six exercises containing authentic, biologically motivated computational exercises that demonstrate how modern omics data are used in precision oncology. Upper-division undergraduate students develop advanced Python programming and data analysis skills with real-world oncology data which integrates proteomics and genomics. The module is publicly available and open source at https://paynelab.github.io/biograder/bio462. These hands-on activities include explanatory text, code demonstrations, and practice problems and are ready to implement in bioinformatics courses.Mason D. TaylorBryn MendenhallCalvin S. WoodsMadeline E. RasbandMilene C. VallejoElizabeth G. BaileySamuel H. PayneAmerican Society for Microbiologyarticlecancergenomicsproteomicsclassroom teachingonline modulesPythonSpecial aspects of educationLC8-6691Biology (General)QH301-705.5ENJournal of Microbiology & Biology Education, Vol 22, Iss 2 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	cancer genomics proteomics classroom teaching online modules Python Special aspects of education LC8-6691 Biology (General) QH301-705.5
spellingShingle	cancer genomics proteomics classroom teaching online modules Python Special aspects of education LC8-6691 Biology (General) QH301-705.5 Mason D. Taylor Bryn Mendenhall Calvin S. Woods Madeline E. Rasband Milene C. Vallejo Elizabeth G. Bailey Samuel H. Payne Online Tools for Teaching Cancer Bioinformatics
description	ABSTRACT The rise of deep molecular characterization with omics data as a standard in biological sciences has highlighted a need for expanded instruction in bioinformatics curricula. Many large biology data sets are publicly available and offer an incredible opportunity for educators to help students explore biological phenomena with computational tools, including data manipulation, visualization, and statistical assessment. However, logistical barriers to data access and integration often complicate their use in undergraduate education. Here, we present a cancer bioinformatics module that is designed to overcome these barriers through six exercises containing authentic, biologically motivated computational exercises that demonstrate how modern omics data are used in precision oncology. Upper-division undergraduate students develop advanced Python programming and data analysis skills with real-world oncology data which integrates proteomics and genomics. The module is publicly available and open source at https://paynelab.github.io/biograder/bio462. These hands-on activities include explanatory text, code demonstrations, and practice problems and are ready to implement in bioinformatics courses.
format	article
author	Mason D. Taylor Bryn Mendenhall Calvin S. Woods Madeline E. Rasband Milene C. Vallejo Elizabeth G. Bailey Samuel H. Payne
author_facet	Mason D. Taylor Bryn Mendenhall Calvin S. Woods Madeline E. Rasband Milene C. Vallejo Elizabeth G. Bailey Samuel H. Payne
author_sort	Mason D. Taylor
title	Online Tools for Teaching Cancer Bioinformatics
title_short	Online Tools for Teaching Cancer Bioinformatics
title_full	Online Tools for Teaching Cancer Bioinformatics
title_fullStr	Online Tools for Teaching Cancer Bioinformatics
title_full_unstemmed	Online Tools for Teaching Cancer Bioinformatics
title_sort	online tools for teaching cancer bioinformatics
publisher	American Society for Microbiology
publishDate	2021
url	https://doaj.org/article/8f0d074b4ff1421383e481c010daf471
work_keys_str_mv	AT masondtaylor onlinetoolsforteachingcancerbioinformatics AT brynmendenhall onlinetoolsforteachingcancerbioinformatics AT calvinswoods onlinetoolsforteachingcancerbioinformatics AT madelineerasband onlinetoolsforteachingcancerbioinformatics AT milenecvallejo onlinetoolsforteachingcancerbioinformatics AT elizabethgbailey onlinetoolsforteachingcancerbioinformatics AT samuelhpayne onlinetoolsforteachingcancerbioinformatics
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Online Tools for Teaching Cancer Bioinformatics

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