Awesome that you are interested in bioinformatics!

First some considerations, I suspect that you are somewhat limited in terms of compute resources with your personal or school's pc/laptop.

Also setting up your work environment can be a bit of a hassle if you have never done sth. similar before.

I believe a good starting point would be to use google colab in your case (all you need in fact is a google account - https://colab.research.google.com/notebooks/intro.ipynb).

This way you have a "playground" to learn & experiment.

A great example to familiarize yourself with colab is "Bioinformatics for Benched Biologists" (https://colab.research.google.com/github/pachterlab/BBB/blob/master/notebooks/lung_atlas/mouse_lung_dropseq_SRR8426358_python.ipynb) by L. Pachter's group that will also introduce you too single cell analysis.

There are also a corresponding videos - https://www.youtube.com/watch?v=vKsh_ovq8x8.

In terms of ideas I have a couple of general pointers:

If research is your focus:

- start with small data sizes - why not investigate a particular gene family in a set of species?

- if you want to do sth. larger, you don't need to be creative -> repeating an existing published analysis is actually a valuable contribution to the field!

If the learning aspect is your initial goal, my personal favorite recommendation is Rosalind:

http://rosalind.info/problems/locations/

Here you can learn a lot of general bioinformatics.

Also, you can directly apply the things you learn to real data - e.g. having fun with k-mers.

I suggest you linked up with the Philippine genome center at UP Diliman, since you are in Philippine Science High School (I assume the main campus in Quezon City). They might have projects that welcomes volunteers. I read before that they are looking for volunteers who can help them analyze covid-related datasets. I am not sure if it is still open. Just go to their website, in the Opportunities tab. I think they also periodically offer internship programs which can help your group decide what topic to work on.

Hi Lalaine Trotth

Bioinformatics offers a lot of opportunities for improvement, however, I would recommend focusing on enhancing visual representations of biological data. Some biological data types require a more sophisticated visualization. Finding the right kind of data may take some time. Another option is to merge the existing visualizations to provide a better visual representation. It is not likely that much of the resources or facilities would be needed. You can easily do it on your laptop. Feel free to let me know your thoughts on this and I can make further suggestions (even if you are interested in other areas). I wish you all the best.

Current Research Topics in Bioinformatics

Cloud computing, big data, Hadoop.

Machine learning.

Artificial intelligence.

Functional genomics.

Rna-seq analysis (equally relevant along with next-generation sequencing techniques)

Data mining (including text search, data integration, database development, and management)

https://bioinformaticsreview.com/20200922/current-research-topics-in-bioinformatics/

Check https://www.jax.org/research-and-faculty/bioinformatics

You can watch this video

https://www.youtube.com/watch?v=lhU3CzslFqw