Collections

Dastaset resources

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Designing a case

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Facilitaing cases tips

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Adapting cases

thoughts on adapting existing cases

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Eleven tips for working with large data sets

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Case Study guidelines from K. P. Cross Academy

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BIOINFORMATICS: TEACHING BIOLOGY AS A DATA SCIENCE! Removing obstacles for Integrating Bioinformatics Into Biology Curriculum

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Bioinformatics core competencies for undergraduate life sciences education

Abstract:

Although bioinformatics is becoming increasingly central to research in the life sciences, bioinformatics skills and knowledge are not well integrated into undergraduate biology education. This curricular gap prevents biology students from harnessing the full potential of their education, limiting their career opportunities and slowing research innovation. To advance the integration of bioinformatics into life sciences education, a framework of core bioinformatics competencies is needed. To that end, we here report the results of a survey of biology faculty in the United States about teaching bioinformatics to undergraduate life scientists. Responses were received from 1,260 faculty representing institutions in all fifty states with a combined capacity to educate hundreds of thousands of students every year. Results indicate strong, widespread agreement that bioinformatics knowledge and skills are critical for undergraduate life scientists as well as considerable agreement about which skills are necessary. Perceptions of the importance of some skills varied with the respondent’s degree of training, time since degree earned, and/or the Carnegie Classification of the respondent’s institution. To assess which skills are currently being taught, we analyzed syllabi of courses with bioinformatics content submitted by survey respondents. Finally, we used the survey results, the analysis of the syllabi, and our collective research and teaching expertise to develop a set of bioinformatics core competencies for undergraduate biology students. These core competencies are intended to serve as a guide for institutions as they work to integrate bioinformatics into their life sciences curricula.

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DNA Sequencing and Genomic Analysis

Course resources from the Genomics Education Partnership

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Carlos C. Goller onto High-throughput Sequencing

Bringing Next-Generation Sequencing into the Classroom through a Comparison of Molecular Biology Techniques

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Carlos C. Goller onto High-throughput Sequencing

Whole Genome Sequencing in the Undergraduate Classroom: Outcomes and Lessons from a Pilot Course

Drew and Tripplett 

J Microbiol Biol Educ. 2008; 9(1): 3–11. 

Published online 2008 Dec 17. 

PMCID: PMC3577148

PMID: 23653818

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Carlos C. Goller onto High-throughput Sequencing

High-throughput Sequencing course at Duke

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Carlos C. Goller onto High-throughput Sequencing

High Content Q&A videos

https://www.thermofisher.com/us/en/home/life-science/cell-analysis/cellular-imaging/high-content-screening/hca-q-and-a.html

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Carlos C. Goller onto HT Cell imaging Collection

Bioimage Informatics Activity - Julian, D. 2018

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Carlos C. Goller onto HT Cell imaging Collection

DATASET Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq

Dataset for case study

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Leigh Ann Samsa onto scRNAseq Analysis Resources

Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq

Original paper for case study dataset.

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Leigh Ann Samsa onto scRNAseq Analysis Resources

Granatum

GUI students will use to visualize data. 

"Without a single line of programming code, users can click through the pipeline, setting parameters and visualizing results via the interactive graphical interface. Granatum conveniently walks users through various steps of scRNA-Seq analysis. It has a comprehensive list of modules, including plate merging and batch-effect removal, outlier-sample removal, gene-expression normalization, imputation, gene filtering, cell clustering, differential gene expression analysis, pathway/ontology enrichment analysis, protein network interaction visualization, and pseudo-time cell series construction." Zhu et al. Genome Medicine 9:108. doi:10.1186/s13073-017-0492-3

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Leigh Ann Samsa onto scRNAseq Analysis Resources

XKCD - simple writer

Only allows you to use the most common 1000 words in the English language.  

Educational use here - Introducing Students to the Challenges of Communicating Science by Using a Tool That Employs Only the 1,000 Most Commonly Used Words

 

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Sam S Donovan onto HITS 2018 Workshop Resources

Data Management Skill Building Hub

The Data Management Skillbuilding Hub contains resources for better data management and is open to community input and update. These resources are adaptable across a range of contexts and intended for use by researchers, teachers, librarians, or anyone who wants to learn better data management practices. Each tile below contains a lesson in slide format with annotations, a one page handout that distills the main message, and a hands-on exercise. 

Also see the data life cycle at DataONE.

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