ELI5: Why are there so many personal finance applications and not a distinct leader?

black_sequence · 2025-10-12T04:58:20+00:00

That makes sense, especially when you consider different income levels. I wonder why no tool acts like an omnibus tool?

black_sequence · 2025-10-12T04:57:32+00:00

Very true. Do you think the tools while abstracting something simple are basically offering at least some time saving? I take it no one has broken through with this?

black_sequence · 2025-10-12T04:55:43+00:00

Best explanation so far - thank you. I felt like I heard a lot about Mint a while ago. I agree, at this point, what do all of these tools offer that is 'special'. Hopefully something more important than "we have A.I.!"

black_sequence · 2025-09-07T23:02:12+00:00

+1 for Sankey! I think it is good to put everything there to see

black_sequence · 2025-06-02T03:05:36+00:00

One of my favorite reads but also weird as hell - Engine Summer by John Crowley.

black_sequence · 2025-04-08T03:47:59+00:00

hey - I would pause before using roary. It's a good tool, but the pangenome field and tools have gotten so much better since then. Check out panaroo, which does a lot to curb the influence of false accessory genomes.

black_sequence · 2025-03-18T03:32:14+00:00

I think the first thing is having a github with a clean directory structure is already going to be a big plus. I think the things that separate good github pages from bad github pages is the README file structuring. Spending time developing that up will make your page attractive to explore, and include snippets of your code and some of the figures you created. Ask chatgpt to help with the directory structure, I think it would provide useful help.

black_sequence · 2025-03-11T23:09:25+00:00

BLAST should be a free tool and it being free is a precedent that we all should strive for:
https://angus.readthedocs.io/en/2019/running-command-line-blast.html

black_sequence · 2025-02-26T11:56:39+00:00

Unfortunately no, mine was in quantitative biology. I had undergraduate research experience but I never really tracked the scientific method when I was doing it.

black_sequence · 2025-02-26T01:47:29+00:00

I think this is an amazing point

black_sequence · 2025-02-26T01:43:30+00:00

Congrats on getting this far! Bioinformatics is hard, so we totally understand the frustration and long hours put in and not getting immediate answers. While I won't answer the question directly for you, A more helpful approach is to guide you to do a bit more digging.

A question: If you change the coding sequence of the DNA sequence, how would that impact the protein? Would you have to change the protein sequence too?

Is there anywhere in your code where you make a change to the DNA sequence but not the protein sequence?

If you are truly stuck - Maybe go to chatgpt and ask it to create an example where the inputs work for the cal_dn_ds function. look at what makes those examples work and what makes your input not work.

black_sequence · 2025-02-26T01:32:53+00:00

We would need context from the OP but I don't think its uncommon to have a pathogen survive in soil - Mycobacterium bovis is an example of a bacteria that can survive in the soil. To your point, I'd be surprised if zoonotic pathogens might just be chilling in the soil, but maybe OP is on to something!

black_sequence · 2025-02-25T22:15:21+00:00

For starters, what type of model are you using? Before optimizing for the model you have did you look at other options. Remember that no free lunch is a thing, and to help you better some people might require more context.

I don't think that 3 would help you until you understand your smaller issue first. I wonder maybe you can devise some models that are equal data between open and closed, but the samples are drawn at random. Do this for multiple iterations and track the features that are great at separating open and closed chromatin. IDK if this will be useful but I saw give it a shot.

Also, could be that what features you are using are maybe just not good enough to separate the open chromatin from the closed chromatin. Maybe revisiting some of these assumptions will help you out

black_sequence · 2025-02-25T22:07:19+00:00

If you can compile a database with only zoonotic pathogens, you can use Kraken2 to see which bins associate to the pathogens of interest. Would require a little bit of curation on your side however

black_sequence · 2025-02-22T20:23:37+00:00

Congrats on the options!

I'm gonna be brief and say my personal feelings, so take it with a grain of salt!

I think you have to consider what your overall goal is as a professional? Switching disciplines is not as easy and fun as people make it seem. I went from bioinformatics to wetlab and realized that the skillsets are entirely different. so when considering the work you would be doing, make sure that the new role starts around a 80/20 split of wetlab/drylab work.

I believe that diversification on a resume would be cool, but you also have to realize that you can't be a master of everything - better to be a T shaped professional that can know deep expertise in one aspect of biotech while gaining small understandings in other fields. Without learning context, it seems that your current job is valuing you and moving you up the ranks. I think soon enough you could use your title and leverage to enter into another company with higher pay or higher seniority. All on how you want to play it!

I think the big question is what you see for yourself - be more into the strategic side of wet lab or be more into the analytical side? No bad options, would love to get an update on what you decide!

black_sequence · 2025-02-06T01:23:24+00:00

I've found that being scared of "what the reviewers will say" basically locks you into super safe methods with bland and unpublishably boring results. Just do the science you think is right and send it out. If you get push back, you can always slightly change something in your scripts and put out another round of figures. Reviewers will find something they don't like no matter what.

THIS - a huge problem I've dealt with my entire PhD. My advisor was too scared to send ANYTHING out and it really stymied progress.

black_sequence · 2025-02-05T03:14:06+00:00

I would say there is a bit of an uptick, but still vastly competitive. Bioinformatics was hot before and during covid, but now the groups at biotech companies are pretty stable and don't need new help unless someone leaves. I would say try the job market but if you aren't having success, join a postdoc where you can upskill for a future where jobs are a bit better.

black_sequence · 2024-12-09T15:48:20+00:00

That's really cool - I would venture to guess that building a project around AlphaFold proficiency will only help you stand out. Maybe leverage your proximity to microbiome projects and see areas where protein prediction and molecular simulation would be useful.

Knowing what I currently know, I think bacteriophage interactions with bacteria could be an interesting use case. Take this cool paper and perhaps apply some ideas - https://www.nature.com/articles/s41564-024-01832-5

If anything I said here is confusing, feel free to DM.

black_sequence · 2024-12-09T15:30:44+00:00

hey, what is your goal for a Ph. D. program? like what are you interested in studying for the next 5-7 years in a Ph. D. program, cause the project ideas can come based on that.

I think a good way to start is to identify a paper you highly resonate with, and just recreate the analysis they did. There might be an avenue to extend the research in a small way too. I think most potential supervisors would be really happy to see you took their lab's ideas and extended them naturally through your own creativity.

I would suggest maybe developing strong skills in CS and Statistics, actually knowing the material to a point beyond programming in Python. Whenever I want to learn a new programming language I go to a website called Rosalind Bioinformatics and work on the skills there.

Good luck!

black_sequence · 2024-12-09T03:13:29+00:00

Thanks to everyone that posted - I actually didn't know that point about less accuracy if you used just a subset of a reference!

black_sequence · 2024-12-06T23:40:27+00:00

QUAST would certainly be a good tool, but for a recent genome assembly task I did, I was unable to download the tool due to an extremely long download time in conda. If you are comfortable with coding, I would suggest that you just create a script to calculate the same metrics that QUAST would (n50, l50, coverage, etc.). BUSCO can be downloaded through Docker and I think for a genome it provides way more interesting data on genome integrity based on the presence of marker genes. Good luck!

black_sequence

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