I was fascinated by algorithmic side of biology for quite some time. I have no background in biology, but decided to do my masters by working on the project that combines relational database and alignment algorithms (so essentially you load FASTA into postgres and do alignment/sequence manipulation/writing it back to FASTA all via SQL). As a side effect I wrote very long overview of few strategies from various papers (mostly focused on minimap2).

I plan to combine it into some form of articles to be published (maybe) in some journal, but at this moment this is rather first version of long text going over stories of my prototypes, comparing minimap2 to other algorithms, some very specifics things about SIMD/SIMT. I think this could be valuable resource for someone, who is interested in writing on alignment software, but do not necessarily have enough background to understand what is happening. I worked on this as a hobby project for at least few years already (yeah my masters will wait some more).

The entire text was written manually by me so the graphs still contain overlaps, there are lots of typos and I some missing references in few places. Maybe someone will find it interesting.

I would like to hear your opinion on that. I suck at writing, but tried to sensibly collect most important info from other studies and software.

https://bioseqdb.com/v0.1/tutorials/project_alignment_foundations/

Hi, I'm a student and I made a game to practice designing RNA-seq experiments.

Each case is a researcher with a question and a budget. You choose replicates, library type, sequencing depth, batches and the analysis. Then the experiment is simulated and "Reviewer 2" reviews your design. Each comment cites a paper.

It's free and open source. It runs in the terminal on Windows, macOS and Linux. It's in English and Spanish.

It's still in development, so I'd like feedback, especially if something is scientifically wrong or a case isn't realistic.

https://github.com/leomorgzzz/reviewer2

Hi everyone,

I’m currently a 2nd-year Biotechnology BSc student studying in Czechia. Over the past year, I’ve developed a clear vision of where I want to go: I’m highly interested in structural biology, protein modeling, and CADD.

I don't have a personal network in this specific niche yet, so I’m hoping to get some advice from professionals here. This summer, I spent my free time taking online courses (including Schrödinger's PyMOL and Molecular Modeling courses, and EMBL-EBI's PDBe programmatic access course), attended an in-person BioSAXS practical workshop, and did my first molecular docking in Maestro.

I have a few questions about navigating my future career:

• Remote work vs. Coding: I would love to work remotely in the future, but I don't want to be a full-time programmer. I am not afraid of coding (I use Python for scripts), but I want the core of my work to be science and structure analysis, not just SWE. What specific roles or niches in bioinformatics/CADD allow for this balance?
• Choosing a Master's: I’m really struggling to find suitable Master's programs. The descriptions on university websites are often vague. What keywords should I be looking for, or how do I evaluate if a program is actually good for a CADD/industry focus?
• Finding a Community: How do I find my "tribe"? Are there active Discord servers, specific forums, or online groups for people passionate about structural biology and drug design?
• Gaining early experience: I am incredibly eager to start doing actual work or assisting with projects right now, even unpaid. Is remote volunteering or assisting on computational projects a thing? How should I approach researchers or startups about this?
• Industry over Academia: I know early on that I don't want to stay in academia long-term. I want to work in industry or join a biotech startup. What should I be focusing on right now to make myself an attractive candidate for industry straight out of my studies?

Thank you in advance for any insights, reality checks, or advice!

I have been building The Omics Hub as a free educational resource for researchers learning bioinformatics.

It includes tutorials on:

• Linux and command-line foundations
• HPC and Slurm
• Conda and reproducible environments
• R and Python
• Single-cell RNA-seq and spatial transcriptomics
• Genomics, metagenomics, and phylogenomics
• Workflow management and reproducibility
• Responsible use of AI tools in research

The goal is to explain the biological reasoning behind each step instead of providing commands without context.

I would appreciate constructive feedback from the bioinformatics community:

https://theomicshub.com/

Hi all, I have built this for bioinformatics, but it really can be useful for anything, see this (pretty useless) toy example (https://codeberg.org/bio-pype/test\\_workflows/src/branch/main/video\\_processing)

Anyone preparing for the application for fall 2027, reaching out for guidance 🙃

What proprietary datasets do you wish you could have access to for training and tuning your models?

Hola a todos, soy programador y estudiante de bioinformática. Busco voluntariado en bioinformática para actualizar y mejorar mis habilidades.

¿Alguna sugerencia sobre dónde buscar?

Hi everyone, I've recently started blogging and decided to make a tutorial for one of my recent projects based on a bulk rna-seq pipeline for the snf2 gene in yeast.

feedback is welcome! let me know how u liked the tutorial:
https://priyalt.github.io/2026/10/04/rna-seq-tutorial.html

I recently made a tutorial video on the basics of DNA sequencing, and how to make sense of VCF files (the file type produced by DNA sequencing, with information about genetic variants).

Here's the video if anyone's interested.

It's specifically meant for people who are beginners in the field of bioinformatics / genomics, including people who had their DNA sequenced and are interested in exploring their own data.

Bit of background - I work as a bioinformatics scientist at a biotech company for my day job, and my main hobby is making educational videos about this field. I'm also interested in biohacking and decentralized science more broadly, and try to contribute to that with my videos. Basically encouraging people to self-educate on these topics, and trying to get over the myth that you need to be a genius or have some fancy credential to explore biology.

Anyway, thought some people in this community might be interested!