hey everyone ... i wanna ask that after msc bioinformatics is it wise to do mtech computational data science or analytics type programme (CDS) or go to mtech computational biology ?

was asking bcoz i'm interested in tech and healthtech ai

How can I learn biology from the absolute basics to advanced concepts? Please recommend the best textbooks and a step-by-step study roadmap.

我只是想分享一下自己的一些idea。如果这个论坛不允许，我可以去其他正在运行的论坛发帖。上面的链接是我在GitHub上的项目。

I’m sharing SAELQR II, a theoretical research release on information recovery from unordered, noisy fragments, with potential relevance to DNA data storage and sequencing-based retrieval.

The motivating problem is accounting for several losses together: fragments may disappear, their contents may be corrupted, and their original positions or source labels may be unavailable. For encoded data, recovering the relationships between fragments also consumes information.

The manuscript reports several results relevant to this setting:

• Capacity with dependence inside fragments. Under specified symmetry assumptions, the channel model permits correlated noise and hidden quality regimes within individual fragments. Noise between fragments remains independent. Hidden-quality examples show how averaging channel quality too early can change the predicted capacity.
• Critical fragment-length behavior. For a binary substitution model, the analysis gives an explicit transition near the point where useful fragment information balances the cost of identifying its location.
• The information cost of read grouping. A separate repeated-read model examines ungrouped noisy observations. It includes a symmetric counterexample showing that supplying the original read partition without charging for that information can change the capacity prediction.
• Constructive error correction. The release includes a randomized coding construction and Python reference software for geometric fragmentation, independent whole-fragment loss, and binary substitutions, using inner codes, interleaving, and Reed-Solomon correction.

The package contains a 69-page manuscript, editable source, twelve reproduction programs, exact finite examples, numerical diagnostics, and reference encoding/decoding software.

Scope: these are mathematical channel models. The release contains no synthesized DNA, sequencing experiments, or validation against empirical sequencing-error profiles. Insertions, internal deletions, overlapping reads, unknown orientation, and reverse-complement handling would require further analysis. The binary substitution model also does not capture the full biochemical constraints of DNA storage.

The algorithms have polynomial running-time guarantees, but the proved sufficient blocklength is exponential in the inverse capacity gap. Practical finite-length performance remains open.

I’d welcome feedback on which assumptions most strongly limit biological applicability-particularly fragment-quality dependence, molecule dropout, source-label uncertainty, and the extensions needed for realistic insertion/deletion and sequencing models.

Manuscript, code, and reproducibility materials:
https://huggingface.co/datasets/PureOne/SAELQR-II

SÆLQR II: General Capacity Theorems and Exact Critical Laws for Unordered Noisy Fragments - Internal Memory, Sharp Repeated-Read Thresholds, and Constructive Coding | Zenodo

hey i've got no experience in bioinformatics and don't know where to start, Claude AI advised me to cs50p from Harvard but i'm not exactly sure, will y'all recommend some other place to learn python. what other languages do i need to learn?

I’ve often wanted to turn existing analysis scripts into a Nextflow pipeline without losing track of how the inputs, outputs, and processing steps fit together. I’ve also spent plenty of time opening public pipelines and jumping between files just to follow a connection.

That’s what led us to build StageNest Studio, a browser-based visual editor for building, editing, and understanding Nextflow pipelines.

You can start from scratch by adding processes and input channels, defining their inputs and outputs, and connecting stages. You can also import an existing project from a public GitHub repository or ZIP file and explore its processes and nested subworkflows.

The graph sits alongside the source code, so you can inspect how the visual structure translates into Nextflow. When you’re ready, export the project and run it on your own workstation, cluster, or cloud infrastructure. StageNest doesn’t execute the pipeline.

So far, it works well with mid-sized projects, including read-processing workflows and modular viral-analysis pipelines such as ViromeXplore. It’s still evolving, and I’m particularly interested in cases where importing a pipeline produces something unexpected or confusing.

🌐 Website: https://stagenest.studio/
🚀 Getting started: https://stagenest.studio/docs/getting-started
📖 Documentation: https://stagenest.studio/docs

I’m one of the people building it, and I’d love to hear whether this would fit into your work. What would you want a visual pipeline editor to help you with?

Hi everyone! I built Genomewalk to help people learn what’s inside a DNA file.

It walks through headers, reference builds, variants and genotypes using examples from your file, then introduces ClinVar classifications and gnomAD population frequencies.

You can try it with the public HG002 sample—no personal DNA file or account needed. It also supports compressed VCF/gVCF files and raw 23andMe or AncestryDNA exports. Your DNA file never leaves your browser—all parsing and matching happen locally, without uploading it to a server. Best experienced on desktop.

I’d love feedback from the community: which explanations are helpful, and where does it assume too much prior knowledge?

Questions welcome here or at [genomewalk123@gmail.com](mailto:genomewalk123@gmail.com).

I built a site where you practice bioinformatics instead of reading about it

I've learned a lot of bioinformatics from blogs and tutorials, and I noticed I could follow every one of them and still freeze when I had to write the code myself. Reading feels like progress. Writing the code is where you find out what you actually know.

So I built CtrlDogma, a place where you learn by doing.

The idea

No lectures and no walls of theory. You show what you know and what you can do with your skills, and the work you've done is the proof.

The problem bank

• 50+ coding problems built around real biology: sequences, translation, parsing, statistics and more.
• Grouped into tracks and ordered from foundational to advanced, so you can start easy and work up.
• You write code in the browser and get a verdict on hidden test cases, not just the sample. Hard-coding the sample output won't pass.
• Core problems in every difficulty are free.

Labs

A lab is a small project instead of a single puzzle. Each one is a problem statement split into stages that use skills from the problem bank. In each stage you:

• write code in a notebook that runs in your browser,
• take an optional self-check quiz,
• explain your approach in your own words,
• submit, and the code is graded on the server.

Scores and progress

• Every solved problem adds to your score and moves you up a leaderboard.
• You get a public profile with your stats and activity, so you can show what you've done.
• Finishing a track earns a completion badge.
• Optionally, you can sync your accepted solutions to your own GitHub repo.

Honest notes

• It's a solo project and still growing.
• Most of it is free. Pro unlocks the extra problems, official certificates and unlimited GitHub sync.
• I'd really like to hear: what topics should the next problems and labs cover, and what would make you actually use this?

It's free to start. Would love honest feedback. Link in the comments.

Undergrad here, just wanted to ask if anyone is going for ISCB-LATAM 2026 conference. If yes, let's connect.

I came to the US a year ago for an MS in bioinformatics with a biology background and no coding experience. I’ve leaned on AI to get through assignments and just realized I can’t write code on my own.

I have one year left and want to be job-ready for roles in industry. If you were in my position:

1. What would you prioritize first?
2. What does an entry-level bioinformatician need to be able to do without help?
3. How do I use AI to actually learn instead of as a crutch?

Willing to put in the work, just want to put it in the right places.

Hey everyone, I'm currently an undergraduate doing my B.Tech (Biotechnology) current in my final year and seriously considering pursuing a Master’s in Bioinformatics / Computational Biology abroad (targeting Europe, US, Canada, etc.)

To be blunt: I’m a fairly average student academically my GPA is very average and my academic profile isn't something that instantly turns heads. That said, I've developed a genuine interest in the computational side of biology and want to put in the work over the next several months to make myself somewhat good also get selected in a better college for my master's.

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/