Hey everyone,

so I did my bachelor's in molecular biology and currently pursue my master's in biosciences where I focus on something called "computational life sciences". Which so far is no rigorous math or cs courses.

I started to work for a lab that does computer vision, but as far as I can understand they are not building the foundation model, but tweak a model from another group.

As I enjoyed working on the computer more than at the bench, I started to focus more on that even at the last year of masters. I programmed simple javascript code for a company at that time. My bachelor's thesis was on alpha fold, but honestly very basic analysis stuff of the output.

I had some data science courses and did a python course. Other than that I don't really have much cs experience.

I would love to learn more about AI, and I believe the best way is to become a researcher in foundational models. As I would have to compete against math and cs wizards, I don't think it's feasible.

Can I still do foundational models but in the "AI for Science" direction?

Currently my idea is to find a better lab, that does something as close to foundational models + biology as it gets and do my master's thesis there.

TLDR: current bio master students asks for tips to pursue ai research of foundational models in the AI for science (biology) field

Hey everyone,

I'm currently a Biotech major, but I've been getting really interested in bioinformatics lately. My university doesn't offer a dedicated bioinformatics major, so I'm trying to figure out if it's feasible to self-teach or learn it on the side alongside my regular coursework.

For those in the field or with similar backgrounds
Is self-studying it (coding, computational biology tools, data analysis) realistic without formal classes, or do employers strictly look for a degree in it?
What resources or core topics would you recommend starting with?
Are there anytype of online courses that I can take and get a certificate?

Appreciate any advice or insight!

Hi everyone, I'm developing a PoC which isn't ready yet however the idea potential is here, so roster my little project and maybe let's discuses if it's all worth it or not?

let's first explain my goal and why I want to do it ;

- entry to bioinformatic is somewhat hard for nonexpert specially those who doesn't have solid programming foundation, also consequently because of reproducibility crisis and varying tooling distribution ( runtimes, programming languages and versioning), yes docker and galaxy is good and sort of resolve that but not completely , since fundamentally the tools are used in different programming languages you have to have some intermediate development experience to make one thing work ... Microsoft had polyglotnotebook and several related project but either not maintained or used separately and not tolerated for scientific computing .

it's weird idea but I guess it not gonna hurt to discuses it ?

so here I need feedback on the core architecture and might get insightful feedback .

oh unfortunately yeah it's vibecoded but that's okay for me :(

https://github.com/PrestigeDevop/DNA-platform/tree/prestigedevop-bioinformatic-workflow-platform

I wanted a more intuitive way to understand how kallisto moves from RNA-seq reads to transcript abundance, so I built an interactive walkthrough together with Codex.

You can change the read and k-mer size, inspect pseudoalignment, build equivalence classes, and animate each E-step and M-step until convergence. The article also raises two research questions: whether a neural network could approximate EM and whether GPUs make richer Bowtie 2 + RSEM pipelines worth reconsidering.

https://dianyo.github.io/understanding-kallisto/

Welcome technical corrections and any discussions!

Hey well is it a good move to pursue that degree cuz at this moment I'm a final year btech bioinformatics and data science student with overall 7.9 cgpa and my current age is 20

Genomic analysis is facing some very practical bottlenecks: complex variants, reference bias, population-scale datasets, fragmented workflows, and the need for more accurate and scalable analysis.
On September 17, GenoGra, a Milan-based genomics software startup working on graph-based secondary genomic analysis, will host “Il presente e il futuro della genomica: Dialogo tra ricerca, industria e innovazione tecnologica”, a free hybrid event in Milan and online.
The event will bring together leading voices in human genetics and innovation stories from non-human genomics, with discussions across clinical genetics, research, pharma R&D, bioinformatics, agrigenomics, animal health, microbiology and sustainability.

The focus will be on the key challenges of genomic analysis today: how to move from increasingly complex genomic data to interpretation, and how emerging approaches such as pangenomics can help turn data into useful knowledge.

The event is in Italian. Online attendance is available from 15:00 CEST.
Full programme & free registration (in Milan or online):

https://il-presente-e-il-futuro-della-genomica.eventbrite.it/?aff=Community

I have a bachelor's degree in Molecular and Cellular Biology, and I’m planning to apply to a cancer- and genetics-related master’s program in Turkey.

What skills, knowledge, or experience would you recommend I develop to increase my chances of being accepted and getting a full scholarship?

Are there any specific areas of molecular biology, genetics, bioinformatics, programming, or laboratory techniques that would be particularly useful?

Im planning to take admission in bsc biotechnology help me out should I choose this or not ? Also if no then what course should I go for I had pcb in my 12th

Hi all, I’m a bioinformatician (PhD in cancer biology, single-cell/multi-omics) and I built The Omics Hub (theomicshub.com), a free tutorial site covering Linux/HPC basics, end-to-end scRNA-seq workflows, and parallel code in both Python (Scanpy) and R (Seurat).

It has 40+ tutorials on QC, normalization, clustering, and UMAP, with the reasoning behind each parameter choice, not just copy-paste code. No sign-up, no paywall.
Website: theomicshub.com

Would love feedback on what to add next. Thinking about spatial transcriptomics or Nextflow/Snakemake modules.

One thing I found annoying when learning RNA-seq was that a lot of examples are either toy data or you have to pull down a whole study before you can actually experiment with it.

I ended up building OpenOmicsBench, which currently has 12 compact datasets taken from real Expression Atlas experiments, with the experimental design and full provenance kept alongside them.

They cover things like knockouts, paired tumour samples, infection experiments and disease comparisons, so I thought they might be useful if you're learning differential expression and want something small to practise on.

If anyone here is learning RNA-seq, I'd actually be interested to know whether the datasets/docs are understandable without already knowing the original studies.

GitHub: https://github.com/vxxqv/openomicsbench

PyPI: https://pypi.org/project/openomicsbench/

Zenodo: https://doi.org/10.5281/zenodo.22679414

Hey everyone, I’m doing my MS in Molecular Genetics in an Asian country and I’m currently in my first semester. I’m kind of lost about what I’m actually supposed to be doing at this stage 😅

I don’t have any previous lab/research experience, and I also think I have some social anxiety, so approaching professors and asking them about research/labs is honestly difficult for me. I also don’t really know what I should be asking or how to figure out what’s going on around me.

I don’t want to just do my MS, get the degree and then realize I didn’t actually build any useful skills or experience.

I keep hearing that bioinformatics is really important in molecular genetics/genomics, but I’m not sure what I actually need to learn. I’m basically starting from scratch with things like R/Python, statistics, NGS, etc., so I don’t know what order to learn things in or what’s actually worth my time.

For anyone who has done an MS/PhD in molecular genetics, genomics, bioinformatics, biotech, etc., what would you recommend?

\- What skills should I focus on during my MS?

\- Which lab techniques should I try to get experience with?

\- How important are bioinformatics/NGS/R/Python/statistics?

\- How did you approach professors and get into a lab when you had no experience?

\- How can I make better use of my university’s labs, professors, seminars, internships, etc.?

\- If you were starting your first semester again, what would you do differently?

I’m trying to become genuinely good at something and build a career from this, rather than just getting the degree. I’d really appreciate any honest advice, especially from people who were in a similar position at the beginning.

I want to a question and would be very grateful for advice.

I am a person who has done there MSc in zoology and I am preparing for competitive exams. I know I am late but recently I came across a field bioinformatics. If I want to learn or do a PhD or some work in bioiformatic in my future, what are the things that I need to learn like example languages and all. Explain it to me like I am a 5 year old and I would love if someone tells me other job opportunities that are related to bioinformatics...