00:00:00.0

Y: Okay, we are now recording.

00:00:02.1

Participant 5: Okay.

00:00:04.0

Y: So,the recordings will be deleted once we're done and it's transcribed. So these are the entities. The first file that we're looking at is NCBI homo sapiens GFF. Sure. If I just could get you to match as you think appropriate entities from the pink cards to the blue items.

00:00:21.2

Participant 5: Right. Okay, so I just have to and then do I just lay them out?

00:00:24.1

You can lay them out. But I say it doesn't really matter where they go.

00:00:32.1

Participant 5:  Ah yes, the old GFF fun thing. So just the specific items right? (Starts sorting cards and browses through whilst holding stack in hands)  They have some kind of symbol, I suppose people use that nomenclature for things, gene ID or gene name, but there's the naming convention as well. So you've got I guess, different mechanisms for naming conventions, which is fun. P53 is cancer genes. I'm not gonna pick that. Accession, not really one of those, I suppose I mean, I suppose your gene ID could be considered an accession but I would say maybe your ID would fit that more. Can't see any GO terms anywhere. Database. I know HGNC is the naming convention for humans (places H SAPIENS card on table, under Symbol and NAME(?)). So I suppose I could relate that so I know um, so if I wasn't able to see the rest, then I would still probably pick HGNC. Yeah, cuz I guess I'm familiar with that. To say to the extent I'm not a huge genetics person, nothing to do with fruit flies.
Publication not so much GFFs could be somewhere not published, I suppose. Nothing to do with authors. Nope. And IDs. Protein binding I wouldn't know unless I would look up that gene ID. Transcript, no. Gene, yes. It's one of those (places GENE on table, below H SAPIENS). Organism, I suppose that suppose that still similar gene has to come from an organism I guess definitely identifier (places IDENTIFIER above SYMBOL). No DOIs, no molecular weights, diseases. HBOX helicase, maybe but I'm not not supposed to be looking at those, homologue, pathway,
expression.

00:02:51.2

Y: Okay, so could I just get you to go through what you've matched to which term?

00:02:56.1

Participant 5: Right. Okay. So I would say. Yeah, I mean ID is especially a general term for an identifier. So I suppose a lot of these sections could be could be interchangeable, I suppose. So I mean, you got identifier, which ID is an abbreviation for that. So from my knowledge of GFFs, I know that with this particular string, you can put in quite a few of your own identifiers, I suppose. And GFF has multiple levels of identifiers. So you've got a general identifier and you've got some database cross-reference for the gene ID. So again, that's some form of unique identifier. So I would say that identifier probably matches all three of those. There's some form of identifier in the abstract concepts sense of the word. Symbol, people tend to, I've, you know, heard people use, you know, gene symbols as well as gene identifiers. So I think you know, names can be used synonymously with symbols as well, some people have used those name, I'd say the name of specifically for the third one (separates cards into three stacks). So I suppose these are for the three, nine goes for the third one homo sapiens that relates to that middle section, the middle, like, identifier, the first and last don't really tell me anything about that particular gene, unless I knew something about that particular name.
All three of those relate to a particular gene (moves another card up; there is just one card left on the table "ORGANISM"; all others are arranged as one cluster now), either its unique identifier or some other kind of naming convention and organism would go with all three (moves ORGANISM up as well)
as well because I would know through the HGNC that this was some kind of human gene naming convention. So maybe those go with all three.
Those go with that goes with the first, that goes with the second and that goes with the third. Okay?

00:05:08.1

Y: I'll just verbally annotate. Identifier, symbol and organism go for all three. Gene and H. sapiens go for the middle, identifier and name goes for the third.

00:05: 19.0

Participant 5: Yeah, so I'll move these down into the video.

00:05:20.1

Y: Okay. That's fine. Thank you. So, you can reuse the cards and any others that you wish for the second time.

00:05:35.1

Participant 5: Right, okay. So, can I move this over here?
Okay, so if I were to scan the whole thing, or again, am I just supposed to be specific?

00:05:41.1

Y: Just the blues.

00:05:42.0

Participant 5: Ok, I'll try not to look.

00:45:14.1

Y: It's okay. It's not secret. Otherwise it wouldn't be there.

00:05:46.2

Participant 5: Okay. So. So, again, I would knowing things about some of these
FB I could think was something to do with fly base because fly base is another large database and I can already see some things there but I know that some you know, identifier so again FBGN is flybase gene named gene nomenclature, so I can't remember which one off the top of my head so.
So again, we're looking at some kind of some gene or gene product. Again, organism, I might be able to guess got symbols and identifiers, everywhere. So let's see, no. (starts to place cards on tables whilst sorting through stack in hands). Accession's always a tricky one. I mean, I suppose for me accessions in my mental model always relate to some kind of sample or passport identifier because we work a lot with crops, so accessions
have a particular bias towards some kind of material, perhaps an identifier that's linked to something specific and not necessarily abstract like a gene name or gene product. It's related to a seed in a gene bank for example or plant variety so accession I know that it's used for other things and accessions can be used for unique identifiers but in my mental model accessions more and more because I've been working with crops more and more over the years. Accession tends to be related to a variety or to your right. So, GO term definitely the second is a GO term. My no go isn't really a data set or database and fly base is a database so I suppose I would suggest that fly this information might come from fly base and again FB and I can see some of the other fields but fly base is about drosophila, is not really a publication, and I was gonna leave accession there but it's an orphan I think. Transcript, homologues, pathway. Well, not from those two because I don't know off the top of my head what that GO ID relates to. I don't know what this particular gene or pathway I know genes are also obviously involved in pathways but that those specific bits of information not necessarily telling me anything about particular pathway, expression, not really again. No GO term, everything isn't really giving me any information, nothing about the length I don't think. Proteins or gene product but then I can't, I'm not allowed see that so I wouldn't put protein there. Asthma, DOI, XY, chromosome, not really, uniprot, not really.

00:09:12.2

Participant 5: Okay, so I think that's probably where I'll, I'll leave those. I'll try and get those into my zone. Accession's a bit of a strange one, I wouldn't put those in again, these ones would probably again relate to all to both of these terms. The first would relate to the data and database would relate to the first blue box and the GO term relates to the second blue box.

00:09:36.2 Y: Okay, just summarising that first column again, that relates to everything. It's name, gene, organism, symbol and identifier. Okay, and one last file. Then we move on to the second task. It is actually really interesting. I think you're the first plant person I've interviewed.

00:09:51.0

Participant 5: So I wouldn't, I wouldn't say I'm a plant person. It's just because because of some that, you know, crops are a big research basis here. But we do lots of other things to do with microbes, protists, every everything apart from biomedical really.
But I'm involved in projects, the bigger projects that I'm involved in and mostly around wheat and other crops. So I tend that always influences my mental model sometimes, but I'm a microbiologist as part of my undergrad training and then I did bioinformatics. So interesting models sometimes.

00:10:31.0

Y: It's very clear, you clearly know the model organisms very comfortably as well, but I've never had anyone reference plants even.

00:10:41.1

Participant 5:  Okay. Exciting.

00:10:38.2

Y: Okay, the third file is Homo sapiens.gene_info.

00:10:46:2

Participant 5: Right, okay. Okay, so let's start. Again, let's go through all of them are involving some kind of again, we've got this human genome naming convention (places card NAME on table). Talking about some kind of gene, I know Ensembl has gene (places card GENE on table). So although this is that the thing 1, 2, 3, 4, 5
I guess because I can never remember where it delineates between the pipes and this one, I think so. I think that is all one long way isn't it? I think from last time I saw these. So again that was starting to differentiate between names symbols. Okay, so the first column I know that 9606 is the taxon- the NCBI taxonomy number for homo sapiens. Funny things that end up in our brains. So that I would say that's an identifier. We've got other identifiers here. So okay, let's do the first one as all of them again. That's the first one is definitely organism that relates to attacks on
Do nothing to do with flies this time. Okay, so 9606 we've got multiple identifiers from different databases here, I guess 9606 is the NCBI taxonomy. Ensembl is the Ensembl genomes identifiers, no GO term. Definitely homo sapiens. So that would go under organism, maybe a couple of others, but definitely that in my mental model that would then influence all of them. But first column is definitely nothing to do with DOI still. X and Ys I can't see anything in any one of those that would tell me whether it's a sex chromosome. Definitely some kind of chromosome. What? Okay.
Those ones, no.
Being that second one if I didn't know that second column I could say that could be chromosome and definitely if I were able to see some of those, I might think that would be chromosome it's not actually clear. I can't remember which column is the chromosome identifier.

00:13:19.1 Y: If it does help. (Yo reaches to cards or stack not visible on vid)

00:13:22.1

Participant 5: Okay, I didn't wanna cheat.

00:13:23.2

Y: No, you're definitely allowed to acknowledge them. It's not like, white it out.

00:13:30.2

Participant 5: Exactly. So okay, so from the headers, I would know this is definitely gene on a chromosome. And from the headers, I would know that these blue columns are not to do with the chromosome. So in strictness, I wouldn't put this in here because those fields aren't telling me which chromosome it's involved with.
I don't think this has any, ... I can't remember, is my I can't I can't remember if any of those would be uniprot identifiers. I don't know if A1BG has anything to do with asthma, glycoproteins. If I read further down there secretory sperm binding protein, I'm guessing that's not involved.
Let's go with that. I'm pretty confident. Protein, well, I guess if this was talking about gene product again, but it's not really it's not genes encode proteins, of course, or at least in transcribed into RNA, that might end up being proteins. But I suppose if I was going to be generalised about it. Length, none of that is telling me anything by any length. I mean, we've got symbol. So, I mean now, now I'm looking at, look the headers then three would be symbol. Now I'm got specific model to help me relate those fields with a particular symbol. It's a user defined identifier. All of it's about a particular gene, but I suppose somebody might suggest that this is gene names. So they would say that's gene rather than being one, two. (Keeps on sorting cards)
So I mean, these particular terms don't really have anything about homologues in them. I know you've got synonyms, but not those. Diabetes. Not sure what the MIM one is.
So I don't think the Ensembl IDs relate specifically to transcripts themselves.
Protein binding. I mean, accession. Okay, so I guess people would suggest symbol, gene or name that would relate to a gene name rather than in this particular instance. Protein kind of, I suppose it's really about genes, but actually, so I guess I'd stop there.

00:16:28.2

Y: Okay, I'll just read out those first three columns. So the first one is identifier, data set, database, protein, and uniprot.

00:16:36.0

Participant 5: Kind of covers all of them.

00:16:36.2

Y: Okay. Organism and H. sapiens, that's referring to the first one? And symbol, gene name is referring to the third column?

00:16:45.1

Y: Yeah, I guess so. Yeah. Yeah. So I can I guess gene is also across different ones. Gene ID and these relate to the naming convention (taping on column not readable). So maybe that's that first. That would be all of them in my mental model. Be this gene ID. I don't really have a term here that really matches maybe identifier, but then taxon ID is also an identifier. That symbol, I would also count again as an identifier. Example the Ensembl ID is identifier. So yeah, that would be in the third column. For symbol.

00:17:18.2

Y: Yep. Awesome. Okay, so that's task one done. Thank you very much. So there's one other task that I will ask. And that is, so now considering all of the cards, can I get you to organise them
in a way that makes sense to you and explain why you're doing so in that way? And if you feel like you need more cards, you can make them. The yellows, just so that I can pick them out afterwards.

00:17:43.2

Participant 5: Let's find some of them out. Right. Genes, proteins, they're related in terms of the biological process. Symbols, names, uniprot, accession, databases, identifiers.
Hey, how am I gonna get some way to link them up? Maybe identifier... Okay, so let's put identifier.

00:18:10.2

Y: If you need scrap and or like to draw links or anything (1 hands out scrap paper).

00:18:14.2

Participant 5: Okay, that could be useful. I might put them on afterwards. So these are organisms, but they also have identifiers. Oh this is gonna be fun. Like this is like a puzzle, right? Name, symbols, accessions kind of closer to an identifier, but it's quieter. Okay, maybe if I put those close. So that's accession is like a name, symbol, identifier for a particular organism or particular instance of...that's an identifier, but particularly for humans, so let's put it somewhere there.
Probably an identifier in some kind of database.
P53, again, is a particular gene, so maybe that would be an identifier for a particular gene.
Publications, ok, that's also got identifier as in authors, PubMED IDs.
GO term, so that's an identifier. So people often call them accessions as well.
Maybe, but then that's definitely protein-y, gene-y identifiers.
This is fun. So many overlaps. You just push them in one big.

00:19:30.1

Y: Well, I actually started with larger cards and because there's so many
got them all everywhere.

00:19:39.2

Participant 5: Transcript. Hmm. So some people use transcript as a quote from a publication perhaps. But in this case, if I was going to say, well, this is my mental model relating to all the other cards I tried to transcript is some form of between a gene and protein-y thingy.
Again, that's another identifier that's not the gene, DOI is an identifier for a publication as is a PubMed ID. So let's put those closer over here. This is fun I like this. This is a much nicer way to spend my morning rather than writing sound emails all the time. Ahhhm, molecular weight. Okay, that's an interesting one. I gonna think about that in a minute. Disease. Diseases can be caused by things other than...well, I suppose disease is a... some kind of...
Soo we've got disease, diabetes, for example, hmm? Well, I'm not sure what Q9H4C3 does, I know P53 and BRCA1 are obviously cancer related and say cancer is kind of a disease, I guess.
I'm not a medical person, but  I suppose that gives me a general idea. Then diabetes is
both a genetic and a - it's congenital and what's the term? My brain's gone blank. You can get it through lifestyle...?

00:21:43.1

Y: Environmental.

00:21:44.1

Participant 5: Thank you. Homologues, I don't know, if Q, again, Q9H4C3 is a homologue of BRCA1. I'm pretty sure you only have one BRCA1, and if you have  any orthologues or paralogues of that. P53 is the general cancer gene. So,
gene and homologue I suppose would go together but not in those cases I realise I'm going outside and I'll bring everything down in a minute. Pathway, I suppose uniprot gives me some idea of proteins and maybe if I then the you know, I can then go on from there to look at pathways. Genes are involved in prot, well pathways, proteins. Genes, pathways, proteins. Hmm, maybe with, say, pathways somewhere. Okay, I'm gonna make those go up here, those go up there (starts to rearrange cards on table).
So, we've got some kind of publication ID. Pathways, I'm not sure where to put that yet. Organism based pathways based on genes and things. Expression would be transcripts. Length could be gene protein length.
That's a factor of, that's a property. Maybe a property would go with names, symbols, lengths or arbitrary properties. But something asthma goes to disease, diabetes. There, an ID is there. Chromosomes, genes are organised into chromosomes. I suppose, over there somewhere,
X and Y are chromosomes, so put those over there. That's a DOI, that's a GO term.
Okay, so it's interesting what I put over there.
This is all publication. This is some kind of data, identifier related to genes. Other properties because you get other properties or names and symbols for the IDs, they would get protein binding relating to and then that would be organism over here. Molecular weight. Okay, that's a property. Let's put that with a property. All right. So now I'll move them all down (moves clusters down on table). I'll try and get.....

00:24:10.1

Y: We can pick up the camera and run it.

00:24:11.0

Participant 5: Oh, yeah. Okay, so I put those all together these are kind of identifiers. My mic [or I might?]. Okay, now I'll put that there and then, okay, so then we've got identifiers for these things. I'd be getting a little OCD about this, but...

00:24:31.2

Y: No, it's great. I love it.

00:24:33.0

Participant 5: Okay, and those can only, I suppose. Okay. I think I'm good.

00:24:47.2

Y: Okay, so I'm gonna try just verbally like describing what I see. Can you correct me if I've misunderstood?

00:24:52.0

Participant 5: Sure.

00:24:53:1

Y: Okay, so I'm starting from the top left, we have a group that has gene. Branching off gene we have a chromosome and XY is an example of a chromosome.
Then we have homologue beside gene. Transcript and expression both branch off genes. Am I right?

00:25:06.1

Participant 5: I guess so yes, I would say that you get some kind of...these obviously transcribed and that would give you some measure of expression. Yeah. And in a system.

00:25:18.0

Y: Okay. And does protein also branch directly off transcript?

00:25:21.0

Participant 5: Yeah. In this sense. Yeah.

00:25:23.1

Y: Okay. Moving on beside homologue. Are these two related to homologue?

00:25: 29.2

Participant 5: I don't know. I mean, probably not. I don't know what the, the on the gene does side BRCA1's a cancer gene. So I would say that's more kind of matching identifier related to genes and things maybe homologue needs to be somewhere in here. But actually, these are genes really, so maybe if we do something like that, maybe (switches cards on table).

00:25: 54.1

Y: Right. Okay. So, Q9H4C3_Human and BRCA1_Human, they're both attached to gene in that case?

00:26:02.26

Participant 5: Yes, I would imagine so because I don't know if the underscore human is particularly related to a specific database. If I knew what that identifier specifically was in that database or file format, then I might say, well, actually, that's related to some protein sequence and I might make a better choice, but at this time.

00:26:23.0

Y: As long as we know that you think it's a gene.

00:26:25.0

Participant 5: Yes, yes. Definitely gene related, yes.

00:26:28.1

Y: Okay. So does this relate to any of these or do they just (pointing on some cards on table).

00:26:34.1

Participant 5: Identifier is kind of right in the middle. So I would say identifiers for me because I work in the information management domain, data management, semantic web, ontologies, identifiers are literally the most important thing for me to do my work. So I do a lot of work in standards and ontologies and so identifiers are very important to relate something that you're looking at to something unique that you can say this is definitely this thing.

00:27:03.0

Y: Okay, fantastic. So looking at some of the other groups here we have disease. We have a couple of genes, and we have some examples of disease. Do these link up to up here?

00:27:14.2

Participant 5: Yes, they they relate to that because P53 and BRCA1 are genes.
They're not specifically related in those diseases, but they are, I guess, disease causing genes that are related to diseases. Yes.

00:27:29.2 Y: Sounds good. Okay, how about go to the GO term and the examples GO term. That's...

00:27:35.2

Participant 5: Yeah, so GO terms, right. So the GO ID, the GO colon nomenclature relates to an identifier for a unique term in the GO ontology. And so this particular example, I'm told is protein binding. So this whole example so the identifier and the human readable version of that is what we'd call a GO term.

00:28:01.0

Y: Cool. Okay, so that's linked to identifier.

00:28:04.0

Participant 5: Yes.

00:28:04.2

Y: And then we have here a generic data informatics section, would I be alright to say something like that?

00:28:09.1

Participant 5: Yeah, I'd say it's some I would say they're kind of arbitrary human properties, things. So name, a symbol, a length and a molecular weight. For me, they would have a value. So it would have a name, a symbol, and have a number for a length, a molecular weight.
So, these are kind of context for some of these other things. So, a gene would have, a protein, sorry, would have a molecular weight. A DNA sequence, a gene and a protein also have length, a chromosome has a length, a pathway has a length.
Strings, identifiers have a length. So I would say that these are properties that, well mainly molecular weight as the example here is very much related to a molecular biology term. But name, symbol and length are completely arbitrary properties that could apply to nearly everything in this in this list.

00:29:09.2

Y: That sounds good. And I think accession probably maybe falls into that group as well?

00:29:15.0

Participant 5: It does, but I would say that in my mind accession has more context to it. In different communities, it means very specific things rather than name, symbol and length. Maybe symbol. Yeah, I'll stick with. I'll stick with that. Otherwise, we just keep going.

00:29:30.1

Y: That's fine. I think what I have left to ask about is pathway all its lonesome.

00:29:35.2

Participant 5: Yeah, I couldn't work out where it's put. So I mean, you've got proteins involved in pathways, right, and genes involved in pathways and expression involved in pathways. So maybe I now that I've had a chance to digest it, I would probably switch this around (picks up card). But then pathways it's a very systems biology term. Yeah, okay. Okay, maybe we could switch this around a little bit. Maybe we could say actually, these are organisms specific identifiers because we've got these here. These are examples of organisms and maybe pathway would fit that. Yeah. Okay. No, that's, that's better. So we've got this relationship of molecular biology entities with some kind of identifiers and relationships to something involving the effects of a gene or protein interacting with it's... everything else that happens. So that's really the elements of trying to understand the pathway. And then you'd have pathway databases like Reactome or Kegg, or something like that. And then uniprot would be related to the each entity presumably in that pathway, okay, yes, that's much better.

00:30:49.0

Y: Okay. So we have two more islands. One is organism with the two examples of organism. Does that correlate in any way to anything else? Or is it just sort of a data island?


00:31:01.0

Participant 5: I wouldn't say it's a data island. I guess everything we do in biology is related to some organism, its system whether the microcosm or macrocosm and some environmental relationship, I suppose. So, I would say that everything we do in biology is related to understanding an organism and its relationship to itself and other things. So, again, I guess it's like identifier really, I mean, it's kind of core to everything. But yeah, I would say for me, because my mental model is very much about identifiers. And sadly, that becomes a very focal point for my semantic ontology driven brain.  So I organise my notes related to all these other things, but...

00:31:46.2

Y: You're looking specifically at these examples. That make sense.

00:31:50.1

Participant 5: I guess so. It so I would, I wouldn't read too much into.

00:32:02.2

Y: So so many to many to many. Okay. And we have the publication islands. So in that we've got author, publication, DOI and an example of a DOI. PubMED ID is an example of the PubMed ID. Is that there for a specific reason?

00:32:19.2

Participant 5: I would say that publication for me, again, is very much related to a data, separate database. So I'm very much an open sciency open data, open publication person. So that immediately forms publication has very much to do with information and knowledge and data and identifiers. So that's why I put it over there. I know all again, it's like all of these things fit inside this organism box. All of these things fit inside the publication box in some form. You know, publications have a length, DOI strings have a length. So again, these things all over. These the more abstract side and these the more concrete side maybe maybe I can look at it like

00:33:08.1

Y: Okay, yeah. Do you feel like anything was missing or there's any bits, any cards that you would like to add?

00:33:14.1

Participant 5: Hmm, that is a really interesting question. I could, but it would take me all day.

00:33:22.7 Y: Okay. I'm not asking you to build an entire biological data model (laughs)

Participant 5: I don't think so. I think it's an I think it's more interesting to take these as a complete set, rather than trying to add more. I think one of the interesting things is we've got this, especially because we do a lot of sequencing. We get we get a lot of. There's a lot of contextual information based on a particular data generation technique. So if we're going to say, right, let's look at genes, transcripts, expressions, proteins, that kind of thing, been doing a lot of sequencing in those depend very much on technology. So you've got, like, you know, just DNA sequencing, which embodies the whole breadth even though you might be sequencing RNA. So, RNA seek which is particularly looking at transcription, expression through transcript abundance, looking at isoforms and all these kinds of things. So maybe some things around here and there might be interesting to look at this data set, database thing again, is interesting.
I'm very much in this kind of space. And this is my GO term-y, identifier-y comfort zone here. So no, I wouldn't say...maybe that there's this gap between this dataset - database - publication, maybe you know, you've got the difference between a paper an article and the difference between a data set can be a publication, in my opinion, and a lot of people may be more "traditional scientists", in inverted commas would disagree. But I see a database in the data set as a citable publication. And whereas a lot of people might not, but you can get DOIs for datasets now. So I would say that there's definitely I think there's scope for having a distinction between a paper and a data set and database perhaps maybe that would fit in my mental model a little bit more paper article manuscript. I'm not sure what you'd want to call that bit.

00:35:58.1

Y: You're not the first person to bring this one up actually. I like it.
I definitely agree. But I also definitely approach this from a traditional point of view. So, this would go just (???).

00:36:09.1

Participant 5: Yep, that would go into here. Yeah.


00:36:13.1

Participant 5: Actually, let's put say I don't even get PubMed IDs for, you get DOIs for both and you have authors for both. PubMed ID is definitely to do with a paper or article manuscript publication whereas DOIs can be for both data set and database publications, that make sense.

00:36:31.0

Y: It does make perfect sense.

00:36:38.0

Participant 5: Authors, you can have authors for everything. Okay, so maybe that would be a better way, but that's

00:36:45.0

Y: Okay, that's fine. So I'm just running over.
There we go.
That should be readable.
First the video to transcribe it.


00:39:11.2

Participant 5: I don't envy you that

00:37:13.1

Y: It's one of the hardest things of this whole thing is transcribing videos by far. Yeah. Okay. Last question. And then we're done with this one other form to fill out. Are there any entry points or bits that are more important to you?

00:37:23.2

Participant 5: Yes, as before, I would definitely say that for me, my entry points are very much around identifiers, data sets, databases. Accessions, arbitrary terms. So, again, big into standards. So, if I were to say name, symbol or length, and I would want to see some kind of ontology term. Give me a distinct idea about what name means what symbol means and what length means.
Molecular weight, I guess is an easier one.
But yes, definitely this identifier and this abstraction of how humans see context and relating it to different entities and in my kind of line of work that's very much to do with datasets, databases,
publications, but also, you know, trying to get that information from people in a standardised way needs kind of knowledge of most of these things, really, you need the knowledge of biology to say, well, what does actually mean if you tried to say what's a gene? I think a lot of people would have a lot of trouble describe what a gene is. But some of the other things that are much clearer molecular weight is much clearer. And organism. I guess is much clearer, I suppose. Maybe some caveats. Viruses or something, I don't know. But yeah, for me, it's very much about terms standardisation, identifiers and the ways humans see those. That's my that's my interest.

00:39:05.0

Y: Okay, and thank you. Amazing. Well, I'm going to stop recording. Cool.

***END OF RECORDING***