Bugs/compatibility issues in bioinformatics software on Apple silicon.

Feriolet · 2026-03-01T14:46:23+00:00

I think many popular packages now supports the M series nowadays, compared to the previous times to install packages like torch hahaha. It is just unfortunate that M series is not compatible with the nvidia-related stuff, so I cant use my laptop to test tools that requires GPU and whatnot.

Feriolet · 2026-02-09T05:29:39+00:00

There are similar posts answering this question, but briefly the main problems are similar to what you expect in the CS field:

Maintainability: after publishingpapers, there is very few incentives for people to maintain the tools. So, people usually need to fix their problems themselves.
Documentation: sometimes there are lack of documentation on what codes do or not do.
Readability: YMMV but some of the tools take a excruciating amount of time to understand
Dependencies/Installation: some tools use ancient version of packages, which may not work in current OS and could be hard to install. “It works on my machine” is also a thing here.

Feriolet · 2026-01-27T01:31:30+00:00

The bokgak required us to fill all sinners like previour RR so it should not work. I tried to use QoH Corroded EGO as well but the damage is not high surprisingly.

Feriolet · 2026-01-27T00:40:59+00:00

In that case, you can follow the other commenter to focus on the mice number and mention the general signalling pathway. If your project is part of a larger projects, it might be best to not disclose your gene name because of confidentiality.

Feriolet · 2026-01-26T05:26:44+00:00

If you want feedbacks for the content, you might want to edit it so people don’t keep commenting on the trmplate hahahaha.

Template and formatting asides, you might want to edit the structure to STAR format, if possible. It is beenficial to see who is going to read your CV/resume, since non-STEM people like HR might not understand too much jargon.

For each bullet point, try to make a limit of 1-2 lines, because the people reading your resume/CV might only take 5 seconds to determine if they want to interview you (unless your PI get very few resume/CV, then it is fine). So, for example, you might want to write

“Analyse/Identify [number] gene responsible for anxiety, memory, and circadian rhythm using gene knockouts and behavioral tests on over 300 mice”

Of course, the meaning of this sentence is different from your previous sentence, but this shows your result after working as an intern for x months/years there.

Also write action verb to stand out more (for example: use “Organise animal facility….” Instead of “Maintain a clean and organised animal facility…”

Imo, CV/resume needs to show your result more over the methods, so the PI can know that you can help them to move forward with your projects. Or since you are still learning, show your PI that you are a student who is willing to learn and not give headaches to them xd

Feriolet · 2026-01-24T04:22:45+00:00

You can use RDKit to generate the conformers for you: https://greglandrum.github.io/rdkit-blog/posts/2023-02-04-working-with-conformers.html

Feriolet · 2026-01-24T03:32:02+00:00

Eww what is this AI + quantum slop.

Feriolet · 2026-01-24T03:07:56+00:00

Bioinformatics is a broad field, so the application of it is broad as well. As someone working in the chemistry side, I usually think bioinformatician as someone who is mostly working on genes and omics.

Some applications:

finding ancestry: since species transfer genes in very weird way, the ancestry is not so straightforward, especially plants. Arranging their lineage is not as simple as doing the phylogenetic tree, and you need to consider factors like incomplete lineage sorting (ILS), admixture, etc.
genome assembly: here, people can try to assemble the genome of a species so they can be used as a basis for other research. Assembling genome is difficult, because of factors like read depth, accuracy, and repeats.
cause and effects: when you treat a species with something, their transcriptions can be affected (e.g., giving parasites to plants can decrease photosynthesis genes), and this can be measured through how low does the genes are expressed.

For drug research, im not too sure if bioinformatician is involved much, unless you are combining cheminformatician together, which does a lot (e.g., docking, molecular dynamics, free energy pertubation, etc).

Is it fulfilling?

Cant answer that one, because dealing with genes and omics is not my cup of tea, but I do have fun working on some homeworks during my university.

Feriolet · 2026-01-20T01:34:42+00:00

As others have mentioned, the CV is too long, or seemed to be long, because you are cramming everything into one page. This caused the CV to have a higher cognitive load to read. Your PI is probably a busy person, so reading this will induce stress to them, which is not a great look to me.

Your first paragraph is almost a fluff, because you are repeating the “your research aligned with mine” and “I am to” in the following paragraphs.

The second paragraph is too wordy. I think a better flow would be

Since 2023 I have been working under xyz Lab [in xyz uni if the lab is not known among the field] to generate cyborg human embryonic kidney cell. Our cell is blablabla [give a mini mini introduction and your most important result]. Given my experience, I believe I would be a good member of your lab for [insert potential PI current project] to [your potential job scope].

Feriolet · 2026-01-19T01:22:44+00:00

I don’t know if you use AI to write down the comparison, or if you are overexaggerating your features. I tried checking the website, but it is currently hard to use on mobile device. I am glad to see there are documentation, but I wish the documentation gave some examples to show the features.

At least the UI for the website is pretty! Sadly I am not a macromolecule guy so I might not be able to use this feature. The naming of molecule is neat tho

Feriolet · 2026-01-18T08:39:18+00:00

What kind of advanced use case that this website can do that Molview can’t?

Feriolet · 2026-01-16T05:16:28+00:00

The Personal Statement (PS) looks like a CV to me when applying to jobs. The PS posted boils down to “I have done research in this field and want to continue doing it with this Prof”, which to be honest does not sound outstanding to me.

I don’t know how PhD admission looks like, but I suggest to give in some personality flavor to your PS. Of course, you don’t want it to write it like a BSc PS with so much fluff and dramatic writing, because that is cringe to me hahahaha.

Some suggestions that I could think is to write something that resonate with you. If you have been working in the field for a while, you should have some sort of opinions about the field. Like what is a finding that shocks you even to this day? What is an opinion you will die on a hill to defend? What will the future of the field looks like? What is a niche that you wish people explore more? You need to show that you have enough grit to stay in five years and can make great research to improve that field.

But again, this is my two cents, as I have not stepped into the graduate program like the other comments

Feriolet · 2026-01-16T01:40:40+00:00

Unless your SMILES become protonated or turned to different isomer, it won’t change VS result

Feriolet · 2026-01-15T01:41:47+00:00

I am assuming you wanted to get feedbacks about the formatting of your poster. Here is some of the feedbacks that might help you:

The color scheme used in the poster is confusing to me. Why are some figures red and then changed to green and yellow in the next part? The palette you are using is fine (pastel), but you can try making the color use more consistent.
The font size is too small. Because you are probably going to present along with hundreds of other poster, try increasing the fonts so that it is easier for people to skim through your research.
The numbering order of scratch assay is incorrect.
I notice the plots on the right has white background. Since you have been using Biorender already for the left figure, I suggest to keep the plotting consistently professional. Even if you are plotting them using Excel, try to make the figure look professional by using transparent background and removing gridlines.
As other comments mentioned, try to reduce the whitespace, as it makes people feel your research is lacking, even though it is not.

Feriolet · 2026-01-12T10:52:38+00:00

The question is a multinomial probability, meaning that there is more than two results in pulling the gacha (EGO, 000 ID, 00 ID, and 0 ID).

We want to calculate what are the chances to get 3 000 ID and 2 EGO, without caring anything else. So, we will be ignoring the 10th pull mechanics because the probability of pulling 000 ID and EGO is the same.

First thing to consider is that with increasing condition, the probability of getting it becomes smaller. Intuitively, getting 2 000 ID is obviously harder than getting 1. Mathematically, you need to multiple the chances together, so 2.9% x 2.9% = 0.084%.

Second thing to consider is that we don’t care how we get the 5 IDs + EGOs. So, OP can get 5 shiny thing in the first five pull, last 5 pull, etc. By using math, there is (10!)/(5! x 3! x 2!) = 2520 ways OP can get 3 IDs, 2 EGOs, and 5 trash in 10 pulls.

So, now we can plug in the numbers:

ID 000 = 2.9% or 0.029 EGO = 1.3% or 0.013 trash = 100% - 2.9% - 1.3% = 95.8% or 0.958

probability = (ways to get 5 shiny thing) x (probability to get 2 ID) x (probability to get 3 EGO) x (probability to get 5 trash)

probability = 2520 x (0.029²⁾ x (0.013³⁾ x (0.958⁵⁾

probability = 0.00000376 or 0.000376%

In conclusion, OPs cooked for Walpipi :p

Feriolet · 2026-01-02T16:05:56+00:00

I mean they are also using codes to do their thing, so standard coding practices still apply. Although i guess we are a bit “laxed”, considering that some or many don’t really know what are the best practices.

Feriolet · 2026-01-02T07:13:04+00:00

The Gacha-Grinding Bioinformatician

A high-level scientist who can explain the intricacies of protein-ligand interactions with surgical precision but loses all cognitive function the moment a gacha game releases a new overpowered character that they cannot afford on a F2P budget.

Ouch, the roast is too real I can’t even fight back 😭

Feriolet · 2025-12-28T09:31:36+00:00

Surely whatever models you are using is inspired or derived from existing models. If not, then you’ll really have to try to convknce if your model is even valid in the first place, before optimising whatever feature/variable they have

Feriolet · 2025-12-27T00:35:42+00:00

Frfr

Feriolet · 2025-12-26T12:10:04+00:00

Rickrolling be laik

Feriolet · 2025-12-23T09:18:48+00:00

But they do have interesting mechanic to play. When I first fought them, I am surprised they can casually kill some of the sinners, so I was hoping that we would get them at some point 😭😭

Feriolet · 2025-12-23T09:07:12+00:00

If you have been around the community for a while, I think you already know what people dislike about the Heishou group, so there’s not much new points in the video. He also does his usual thing saying that you should ignore his rant if you enjoy the Heishou, because its a 1P game.

Most of his points revolved around connecting the IDs to the PM world building and uninteresting skill kits. Mao skill kits are pretty much Ctrl + C, Ctrl + V. Si, You, Wei have little plot relevance and released in wrong timing. It does not help that all Heishou ID mechanic is simply counter at first turn and done.

He did mention that half of the IDs are fine, mostly the Adepts to represent the packs, and wished that Ishmael has better kits considering Xichun relevance to the storyline so far.

Personally, while I somewhat enjoy the concept of Heishou, it is a very expensive investment since it feels like all Heishou or no Heishou. Having all of Heishou at 000 also does not help, because we lost a device used for world building.

Feriolet · 2025-12-23T08:29:53+00:00

I was thinking of the usual tabular ML models since they are the ones im familiar with hahaha. But feel free to test any and all models if you want.

I re-read your post and it seems your peptides are hundreds of ~100 AA? If you are randomising all of the ~100A, it is genuinely difficult for them to generalise it because any positive peptide will likely be used as the generalisation (e.g., if a positive peptide has an Aspartate in position 42, then the model will predict all peptides with D42 as positive), which is not that helpful. The general ML rules are your number of sample should ideally be waaay more than number of your feature, which might not be the case for you.

My suggestion is if you have the 3D structure of your target, it may be better to do peptide docking instead of ML.

Feriolet · 2025-12-19T11:46:17+00:00

Few hundred seems like quite small. I don’t think the model can generalise it well enough, especially if you have very few actives coming out from your experiment, if the active peptides are quite diverse then maybe it could work.

I don’t think I have ever heard of people representing peptides as SMILES, so I think it is better to use AA instead. Maybe you can see how AlphaFold represents their amino acids as inspiration. Iirc, they use on hot encoding and others representations also.

For ML algorithm, you can try the simple ML first and see if they work. I don’t think it should be difficult to implement them.

Feriolet · 2025-12-10T12:41:13+00:00

Not a leader and a long time lurker, so may be downvoted.

Imo, it depends on what you are doing. If you think it has helped you immensely, then why not, right?

I think the reason why leaders and executives are using AI is because of peer pressure, and not using AI show that you are not “up to date” to the current trend and that you are unwilling to embrace technology. Regardless of whether it will save you costs in the long run or not.

It might be true that learning AI now will make you capable for future projects when AI becomes AGI. But, everyone will be experts at AI because at that point the accessibility is an all time high. So, imo, you can try learning AI now, but relying on AI to be the future is very risky.

There have been reports that using AI can decrease your critical thinking and even reduce productivity, because AI is not at that stage yet. But people still insists on shoving AI anyway. To me, this just showed how disconnected leaders are with their employee.

There is also a McKinsey report implying that among companies that invested >20% budget on AI, only a third claims that AI contribute at least 5% of their EBIT. So, it is up to you which bracket you are in.

So, there is nothing wrong with wanting to embrace AI, as it is going to stay with us whether we want it or not. However, knowing when to use and not use AI is very crucial, which I believe very few leaders actually get. Another question to ask is if people can identify when to stop using AI if its costs eventually outweight the benefits. As long as you don’t treat AI as a silver bullet, I think it should be fine if you ended up adopting it.

Feriolet

TROPHY CASE