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Teaching Neuroinformatics with an Emphasis on Quantitative Locus Analysis
Although powerful bioinformatics tools are available for free on the web and are used by neuroscience professionals on a daily basis, neuroscience students are largely ignorant of them. This Neuroinformatics module weaves together several bioinformatics tools to make a comprehensive unit. This unit...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Faculty for Undergraduate Neuroscience
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3592744/ https://www.ncbi.nlm.nih.gov/pubmed/23493834 |
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author | Grisham, William Korey, Christopher A. Schottler, Natalie A. McCauley, Lisa Beck Beatty, Jackson |
author_facet | Grisham, William Korey, Christopher A. Schottler, Natalie A. McCauley, Lisa Beck Beatty, Jackson |
author_sort | Grisham, William |
collection | PubMed |
description | Although powerful bioinformatics tools are available for free on the web and are used by neuroscience professionals on a daily basis, neuroscience students are largely ignorant of them. This Neuroinformatics module weaves together several bioinformatics tools to make a comprehensive unit. This unit encompasses quantifying a phenotype through a Quantitative Trait Locus (QTL) analysis, which links phenotype to loci on chromosomes that likely had an impact on the phenotype. Students then are able to sift through a list of genes in the region(s) of the chromosome identified by the QTL analysis and find a candidate gene that has relatively high expression in the brain region of interest. Once such a candidate gene is identified, students can find out more information about the gene, including the cells/layers in which it is expressed, the sequence of the gene, and an article about the gene. All of the resources employed are available at no cost via the internet. Didactic elements of this instructional module include genetics, neuroanatomy, Quantitative Trait Locus analysis, molecular techniques in neuroscience, and statistics—including multiple regression, ANOVA, and a bootstrap technique. This module was presented at the Faculty for Undergraduate Neuroscience (FUN) 2011 Workshop at Pomona College and can be accessed at http://mdcune.psych.ucla.edu/modules/bioinformatics. |
format | Online Article Text |
id | pubmed-3592744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Faculty for Undergraduate Neuroscience |
record_format | MEDLINE/PubMed |
spelling | pubmed-35927442013-03-14 Teaching Neuroinformatics with an Emphasis on Quantitative Locus Analysis Grisham, William Korey, Christopher A. Schottler, Natalie A. McCauley, Lisa Beck Beatty, Jackson J Undergrad Neurosci Educ Article Although powerful bioinformatics tools are available for free on the web and are used by neuroscience professionals on a daily basis, neuroscience students are largely ignorant of them. This Neuroinformatics module weaves together several bioinformatics tools to make a comprehensive unit. This unit encompasses quantifying a phenotype through a Quantitative Trait Locus (QTL) analysis, which links phenotype to loci on chromosomes that likely had an impact on the phenotype. Students then are able to sift through a list of genes in the region(s) of the chromosome identified by the QTL analysis and find a candidate gene that has relatively high expression in the brain region of interest. Once such a candidate gene is identified, students can find out more information about the gene, including the cells/layers in which it is expressed, the sequence of the gene, and an article about the gene. All of the resources employed are available at no cost via the internet. Didactic elements of this instructional module include genetics, neuroanatomy, Quantitative Trait Locus analysis, molecular techniques in neuroscience, and statistics—including multiple regression, ANOVA, and a bootstrap technique. This module was presented at the Faculty for Undergraduate Neuroscience (FUN) 2011 Workshop at Pomona College and can be accessed at http://mdcune.psych.ucla.edu/modules/bioinformatics. Faculty for Undergraduate Neuroscience 2012-10-15 /pmc/articles/PMC3592744/ /pubmed/23493834 Text en Copyright © 2012 Faculty for Undergraduate Neuroscience |
spellingShingle | Article Grisham, William Korey, Christopher A. Schottler, Natalie A. McCauley, Lisa Beck Beatty, Jackson Teaching Neuroinformatics with an Emphasis on Quantitative Locus Analysis |
title | Teaching Neuroinformatics with an Emphasis on Quantitative Locus Analysis |
title_full | Teaching Neuroinformatics with an Emphasis on Quantitative Locus Analysis |
title_fullStr | Teaching Neuroinformatics with an Emphasis on Quantitative Locus Analysis |
title_full_unstemmed | Teaching Neuroinformatics with an Emphasis on Quantitative Locus Analysis |
title_short | Teaching Neuroinformatics with an Emphasis on Quantitative Locus Analysis |
title_sort | teaching neuroinformatics with an emphasis on quantitative locus analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3592744/ https://www.ncbi.nlm.nih.gov/pubmed/23493834 |
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