Skip to content

Latest commit

 

History

History
62 lines (44 loc) · 2.19 KB

philosophy.rst

File metadata and controls

62 lines (44 loc) · 2.19 KB

Lab philosophy

The lab motto is "Better science through superior software" - we believe that, as biology becomes increasingly reliant on computation and data analysis, better software is needed to progress biological investigation. This includes better software development practices and workflows, placing an emphasis on core scientific values of open source and reproducibility, and an interest in developing flexible libraries and reusable/remixable software.

The guiding principle of the lab is to advance the biological sciences through enhanced use, extension, and development of computational tools and approaches. Our primary focus for now is on "-omics" data - primarily genomic, transcriptomic, and metagenomic sequencing data.

Open science

To the best of our ability, we practice open science; the default is set to "open".

  • all software should be available under a BSD open source license.
  • most papers are written openly and submitted to preprint servers.
  • all data is made available as soon as practical.
  • collaboration is good.

We also encourage blogging and open discussion of research on social media.

Lab details

Within the lab, we try to practice lazy consensus. For most formal requests (travel / spending), please give Titus 3 working days to consider them before moving ahead, unless it's urgent (in which case you should bother Titus with an "urgent!" request, receive positive permission, and then move ahead).

We have a code of conduct; please see :doc:`coc`.

All software within the lab should be written in C++ and/or Python, in order to maximize reuse and remixability within the lab.

Miscellany

Other miscellaneous thoughts --

  • postdocs are generally welcome to take projects with them and collaborate on lab projects after they leave the lab, although Titus may have suggestions to help with career considerations.
  • given finite resources, not all problems are worth solving. Choose problems worthy of your time and energy.
  • teaching and training are core values within the lab. However, please be mindful of the need to balance teaching/training with research efforts.