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Back to school: getting organised

Posted by , on 27 September 2022

With the calendar about to click over from September to October, we are bringing you one last post highlighting some of our archive content that we hope will help make your academic year a good one! In this post, we look at getting organised, both in the lab and with your data analysis.

The topic of this post was prompted by a tweet from Teresa Rayon asking for advice on lab inventory management software, so we’ve included it below so you can see the replies that Teresa received.

After the lab is organised and you are approaching your first experiments, you need to think about how you are going to record all your data and metadata. We have an article on The Pros and Cons of having an Electronic Lab Notebook (ELN) here on the Node. The article also includes a link to five popular ELNs, updated in 2020.

We have collected below, a series of ‘how to’ guides from Joachim Goedhart, Helena Jambor, Jonas Hartmann and Steph Nowotarski covering organising, visualising and analysing data.

Once you have followed all the tips below, you are ready to present your data to the community. Helena tells us how to make a graphical abstract and how to win a poster prize (or how to make an impactful poster!)

If you have a ‘how to’ guide you would like to share, please get in touch or feel free to post it directly onto the Node. Details of how to register with the Node can be found here. You can contact us at  thenode@biologists.com

| How to organise your data

| Visualising data – dos and don’ts

| How to pick your colour scheme

| How and when to use p-values and what are the alternatives

| Dealing with microscopy data

Helena, Joachim and Jonas offer guides into presenting and analysing microscopy data. You can find more information on image analysis on our sister site FocalPlane, including Andrey Andreev’s recent post on presentation and analysis of calcium imaging data.

| Organising with ontologies

Steph Nowotarski takes us through why and how you should organise your data in an ontology

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Categories: Education, Research, Resources

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