When you’re deciding which antibodies to buy you’ll look at these figures to get a sense of their quality. Antibodies aren’t perfect and might bind proteins unrelated to the one you want to study. Depending on your application, some off-target binding might be acceptable, but usually it’s not. Also, they might just be completely nonfunctional and bind nothing (perhaps due to missteps during manufacturing).
So what this fraud does is convince you to give these antibodies a chance when you otherwise wouldn’t have. You should validate them yourself and show they only bind your target before doing an experiment, but now you’re just wasting time and money evaluating something that’s guaranteed to fail.
Antibodies are notoriously unreliable, so you might have to give two or three vendors a try before you get one that works. Now I’m starting to wonder how much of that reputation is due to fraud and not just nature.
There’s nothing to be reminded of. English has a word to describe North and South America together (“the Americas”). Other languages have different words for the same concept.
It’s like reminding someone they shouldn’t say “bicycle” but should instead say “fahrrad”.
I’d be surprised if they’re running at less than 100% capacity after this. It’s just too useful to too many people for whom an $80/month increase is immaterial (I speculate)
I think it would be helpful to reframe this as a statistical problem, and not as an issue with units. Estimating some measure of central tendency and variance (mean and 95% CI maybe? I'm not familiar with time series statistics) would not only make it clear that there's uncertainty in the number, but it would handle the issue with picking a window size - smaller windows would increase the uncertainty.
Regardless, we're talking about a distribution of abilities, and the number of people who can't drive safely is going to increase dramatically in the near future. The point of this article wasn't to judge all boomers.
I work in a field that has a strong glass ceiling, and the only way through is with a PhD (some employers are starting to recognize that, with several years of experience, people with a bachelor's or master's degree can attain the same level of independence and mastery that you'd demand from a PhD, but it's still kinda rare).
But even having a PhD isn't enough to establish credibility during the interview process, as there are plenty of PhDs who are incompetent. It's really more of a thing that gets your foot in the door - a signal that it's plausible that this candidate could have the juice.
The solution is that after the usual interview steps (resume, phone screen, etc), the candidate gives an hour long seminar on their research to 10-20 people (really 45 minutes of material + 15 minutes of questions). It's basically impossible to talk for that long about your research and the prior literature with a critical audience of experts and not reveal whether you actually know your stuff.
So in a sense, your vision has actually been achieved, but only within the group of people who have traditional credentials. The question of how to open this up to anyone regardless of credentials is not something I'm going to be able to answer, but I certainly hope it does.
In terms of frameworks for evaluating competence, here's the questions I ask when deciding if someone is an expert (and what I get out of these questions in parentheses):
1) Has this person spent years doing something where they constantly discovered that they were wrong? (if you're never wrong, you're not learning and you're certainly not doing anything interesting, and might be a crank)
2) Did they have a mentor or group of expert peers who helped them grow and critiqued their work? (this both helps them grow on a daily basis and also plugs gaps in their knowledge and skills, and gives them new ways of thinking)
3) Have they built or discovered something non-trivial, and in the LLM era, do they actually understand what they built? (You can't really be sure your knowledge and skills are meaningful until you apply them)
4) Can they hold their own when being grilled by other people with deep experience in the same field, or adjacent fields? (This assumes the experts are arguing in good faith, but if you can either answer critical questions or convince someone that their questions are flawed, that's a great sign)
5) Do they have both depth and breadth in their knowledge of their field? (I think this one might get downplayed as it smacks of gatekeeping, but it's so easy to make huge errors or reinvent the wheel when you don't know what other people have already done, and don't know how your contribution fits into the work of others)
6) Can they explain their work on multiple levels of complexity? (Filters out people who are just trying to hide their incompetence with jargon)
7) Are they willing to say they don't know, when asked a question they don't know the answer to? (Cranks will never admit this)
You don't need to synthesize an entire bacterial genome from scratch to do this. You can just insert them one at a time into existing bacteria. Or just give them plasmids. Anyway, the ability to achieve the outcome you're describing has existed for decades.
Sure, but there apparently wasn't enough of a dialog either. With a textbook, you're confronted with facts and explanations that you didn't ask about, or even knew to ask about. Don't get me wrong - my original recommendation to take an interactive course is still the best option in my mind, as simplifications made for the benefit of the learner often lead to apparent contradictions that an instructor can clarify. But at some point you do just need the set of raw facts to be able to work with these systems.
LLMs may be enabling, but OP explicitly stated "I wanted to dig deeper into the subject, but not by reading a boring textbook", which, of course, would have eliminated the issues in this tool, or at least made it clear to them that they needed to dive deeper before publishing. I feel like there might be some analogy with blaming cars for drunk driving - by definition, not possible without cars, but you can drive responsibly if you choose to.
This is so riddled with inaccuracies that I can spot them immediately despite not being a phage biologist. For example, the PhiX image has a DNA with about 20 base pairs - wildly not to scale. M13 is also wildly scaled, and it clearly has a double stranded DNA which is labeled as single stranded.
What the hell is this amino acid view? This is not how genes work at all. This is biology 101 and it's completely wrong. Why did you buy a domain name to share disinformation that you don't even understand?
None of this is displayed in a way that would be useful to working biologists, and I don't see how this could be used as a teaching tool even if all the errors were corrected. This simply doesn't provide any insight into how phages work. Looking at a raw sequence is pointless (also that color scheme is incredibly garish) - you need annotations! The 3D structures don't have their domains labeled and you can't connect sequence features to structural elements.
Why wouldn't you just use all of the existing tools that already do all of this correctly? Look, I don't mean to gate keep, and it's great that you learned something (assuming you didn't vibe code this), but this is a lot of effort that could have been avoided if you had had a single conversation with a biologist of any background, or asked an LLM to critique your idea, or made a single reddit post asking if this would be useful.
Edit: This may come across as super harsh - but really, I love the enthusiasm and I hope you keep pursuing this. But the right place for this passion at this point in your life is a classroom or some kind of structured course.