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johannabosch/README.md

Welcome to my Github!

I'm a biologist from Canada, and my main area of research lies in the ecology and conservation of seabirds in the Atlantic ocean! Alongside my work in seabird science, I also have a passion for science-communication and web design. I currently design Javascript based web-apps for academics from all kinds of backgrounds who want to display their research and results in a shareable, interactive format. I have experience analysing DNA sequencing, geochemical, GPS/GLS, demographic and other ecological datasets using R and Python, so my research experience gives me the advantage of working together with an academic team to design unique content that fits the needs of their data. Most of my projects are available here on my Github!

Some of my past projects have involved:

(a) using paleolimnological methods (ie. tracking geochemical and biological shifts in sedimentary records) to reconstruct past seabird populations (see repo). See the publication in Science Reports here:

Bosch, JL., Álvarez-Manzaneda, I., Smol, J.P. et al. Blending census and paleolimnological data
allows for tracking the establishment and growth of a major gannet colony over several centuries.
Sci Rep 14, 20462 (2024). https://www.nature.com/articles/s41598-024-69860-z

(b) amplicon and metagenomic sequencing analyses to assess the composition and diversity of the seabird gut microbiome, and sedimentary DNA from sediment cores (see repo).

(c) building a web-app to display results from an integrated population modelling study on the Endangered Piping Plover in Atlantic Canada

More About Me

🎓 MSc. in Biology (Memorial University of Newfoundland)

💻 I work with Windows and Linux

⚡ Currently learning more about Parallel programming and HTML5


Contact

Gmail Badge Linkedin Badge Instagram


Languages I use

Python Perl R Shell Script Markdown HTML5


Technologies I work with

MySQL SQLite Git GitHub Adobe WordPress AWS Github Pages


Popular repositories Loading

  1. Microbiome-Analysis-Using-Clusters Microbiome-Analysis-Using-Clusters Public

    This is a 16S amplicon analysis for visualizing microbiome data using QIIME, QIIME2R and Phyloseq. DNA was isolated fom both sediment cores and seabird fecal samples for this analysis.

    CSS 2

  2. johannabosch johannabosch Public

  3. creative-portfolio creative-portfolio Public

  4. Paleolimnological_Analysis_in_R Paleolimnological_Analysis_in_R Public

    This is a paleolimnological analysis using tidypaleo in R. View the Github page to walk through each step of the analysis.

    R