Support

Support Options

  • Knowledge Base

    Find information on common questions and issues.

  • Support Messages

    Check on the status of your correspondences with members of the QUBES team.

Contact Us

About you
About the problem

Resources: All

Search
  1. Following the Data - PowerPoint Addition to Module

    Following the Data - PowerPoint Addition to Module

    2020-01-10 21:29:24 | Teaching Materials | Contributor(s): Darlene Panvini | doi:10.25334/731M-8788

    This PowerPoint presentation guides instructors and students through the key background information for the module.

  2. Data is the New Science - Modified and combined with Following the Data Module

    Data is the New Science - Modified and combined with Following the Data Module

    2020-01-10 20:52:41 | Teaching Materials | Contributor(s): Darlene Panvini | doi:10.25334/RN01-VX30

    In this module, students will be introduced to some emerging biodiversity data resources. They will be asked to think critically about the strengths and utility of these data resources and apply what they have learned to research a question.

  3. Databases:  A Study of Influenza

    Databases: A Study of Influenza

    2020-01-09 21:35:48 | Teaching Materials | Contributor(s): Selene Nikaido | doi:10.25334/Z8VP-G378

    This lesson introduces the student to the Influenza Research Database. Students will select Influenza genome sequences to see how they are related. Students tests hypotheses about evolutionary ideas involving reassortment in Influenza.

  4. Introduction to Genome Annotation

    Introduction to Genome Annotation

    2020-01-09 21:32:41 | Teaching Materials | Contributor(s): Selene Nikaido | doi:10.25334/2ANZ-SV60

    This exercise is an adaptation of the Annotation Lesson by Rosenwald et al. It introduces the use of bioinformatics tools to extract information from genome databases. It is a basic lesson on genome annotation databases.

  5. Data Analysis and Cancer

    Data Analysis and Cancer

    2019-12-18 21:51:34 | Teaching Materials | Contributor(s): Lynn Marie Diener | doi:10.25334/BTAS-Z679

    This is a flipped classroom approach, students will learn the basic content about cell-signaling, p53, and transcription factors before class. During class students will focus on data analysis applying what they learned to their interpretation of the data

  6. Biodiversity research using digitized, internet-based natural history collections

    Biodiversity research using digitized, internet-based natural history collections

    2019-12-17 19:26:39 | Teaching Materials | Contributor(s): Kaitlin Stack Whitney | doi:10.25334/RSKN-MQ83

    Collections based research is a critical tool for organismal biology and biodiversity research. Yet natural history collections have a complicated past. This multi-class module examines the origins, problems, and current uses of collections.

  7. Online, 10-minute adaptation of Biobyte 1 – Where are we in the data science landscape?

    Online, 10-minute adaptation of Biobyte 1 – Where are we in the data science landscape?

    2019-12-11 01:19:11 | Teaching Materials | Contributor(s): Megan A. Jones | doi:10.25334/D20F-P060

    Adaptation for 10 minute activity in an online meeting to introduce the NAS Data Science For Undergraduates report's definition of data acumen and engage participants in a self assessment of how they connect with those 10 data science concepts.

  8. An Introduction to Biodiversity Databases and Specimen Images

    An Introduction to Biodiversity Databases and Specimen Images

    2019-12-04 19:33:58 | Teaching Materials | Contributor(s): Amanda Fisher | doi:10.25334/1NCG-T718

    In this module, students will be introduced to some biodiversity data resources and how to search for and download herbarium specimen images. They will be asked to think critically about the strengths and utility of these data resources.

  9. Lesson VI - The Community Science Project

    Lesson VI - The Community Science Project

    2019-11-19 21:18:39 | Teaching Materials | Contributor(s): Anne Rosenwald, Gaurav Arora, Vinayak Mathur | doi:10.25334/MN0K-XB56

    Genome Solver's Community Science Project was developed as a way to use the skills taught in the previous lessons. We're asking members of the community to provide instances of potential phage genes embedded in bacterial genomes.

  10. Teaching Population Dynamics with Data and HHMI BioInteractive

    Teaching Population Dynamics with Data and HHMI BioInteractive

    2019-11-16 22:04:49 | Teaching Materials | Contributor(s): Abby Kula, Kristine Grayson | doi:10.25334/DRTS-CZ24

    Presented at NABT 2019, we demonstrate how the Population Dynamics Click & Learn resource can be customized for any organism - using the Lionfish invasion as an example

  11. Earth Analytics in Python Course

    Earth Analytics in Python Course

    2019-11-01 14:37:29 | Teaching Materials | Contributor(s): Leah Wasser, Jenny Palomino, Chris Holdgraf | doi:10.25334/SH4R-QH25

    Earth analytics is an intermediate, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of heterogeneous ‘big scientific data’.

  12. Intro videos and terminology for GMOs, Transcription, Translation

    Intro videos and terminology for GMOs, Transcription, Translation

    2019-10-28 16:35:24 | Teaching Materials | Contributor(s): Sandi Connelly | doi:10.25334/CJZQ-3K68

    Compiled resources around GMOs and protein production including vocabulary, animations, videos, and games

  13. Complete Set of Lessons

    Complete Set of Lessons

    2019-10-23 15:16:23 | Teaching Materials | Contributor(s): Anne Rosenwald, Gaurav Arora, Vinayak Mathur | doi:10.25334/E4GQ-2S85

    The Genome Solver Project began as a way to teach faculty some basic skills in bioinformatics - no coding or scripting. These Lessons also work well in the undergraduate classroom, culminating with an authentic community research project.

  14. Lesson V - Phylogenetics

    Lesson V - Phylogenetics

    2019-10-22 21:27:41 | Teaching Materials | Contributor(s): Anne Rosenwald, Gaurav Arora, Vinayak Mathur | doi:10.25334/HBAR-5X64

    Genome Solver began as a way to teach undergraduate faculty some basic skills in bioinformatics; no coding or scripting is required. Lesson V is an introduction to Phylogenetics.

  15. Lesson VII - Synteny

    Lesson VII - Synteny

    2019-10-22 21:21:12 | Teaching Materials | Contributor(s): Gaurav Arora, Anne Rosenwald, Vinayak Mathur | doi:10.25334/HV52-1P80

    The lesson teaches about synteny or the order of genes along a chromosome, which is useful for looking at orthologous genes between two species or strains.

  16. Get Started With GIS in Open Source Python Workshop

    Get Started With GIS in Open Source Python Workshop

    2019-10-15 20:27:32 | Teaching Materials | Contributor(s): Leah Wasser, Jenny Palomino, Joe McGlinchy

    There are a suite of powerful open source python libraries that can be used to work with spatial data. Learn how to use geopandas, rasterio and matplotlib to plot and manipulate spatial data in Python.

  17. Introduction to Version Control and Git Workshop

    Introduction to Version Control and Git Workshop

    2019-10-15 20:22:16 | Teaching Materials | Contributor(s): Leah Wasser, Max Joseph

    Learn how to use version control with Git to work collaboratively and back up your work.

  18. Writing Clean Code in R Workshop

    Writing Clean Code in R Workshop

    2019-10-15 20:18:39 | Teaching Materials | Contributor(s): Max Joseph, Leah Wasser

    When working with data, you often spend the most amount of time cleaning your data. Learn how to write more efficient code using the tidyverse in R.

  19. Introduction to Earth Data Science Textbook

    Introduction to Earth Data Science Textbook

    2019-10-15 18:05:03 | Teaching Materials | Contributor(s): Jenny Palomino, Leah Wasser

    Introduction to Earth Data Science is an online textbook for anyone new to open reproducible science and the Python programming language. There are no prerequisites for this material, and no prior programming knowledge is assumed.

  20. Earth Analytics in R Course

    Earth Analytics in R Course

    2019-10-15 18:00:50 | Teaching Materials | Contributor(s): Leah Wasser

    Earth analytics is an advanced, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of heterogeneous ‘big scientific data.’