 Normally, I would like to show an example of how to view and share these relations on the back. And, of course, like... Sorry. So, of course, I don't have to motivate and explain to you why sharing is important. We cannot achieve everything by ourselves. We have to put together and work to discuss our results, our outcome, and therefore we need to share the data. So, how does the sharing culture of knowledge and results looks in the community? So, when I started my PhD three years ago, the standard of sharing looked like this. It depended on why the data was presented, trajectory output was converted into text figures under the best videos. I, at the time, was eager to understand biological processes, and this, in my case, she put in a couple of sectors and wanted to run simulations on myself. So, I went to accept it. This literature was looking at them and tried to understand what's actually happening there. And when I look at something like a figure, which is totally static, and a video, which only shows a certain perspective, I cannot really get the complex dynamics behind of this. So, I was asking my boss if there's something out which is a little bit more interactive, where I can just easily rotate this and change the orientation, where I'm more interested in to look at. Luckily, that was not the case. So, he said, I should put my head together with my colleague at that time, Alexander Rosse, who was working on visualization. And, yeah, we started to try to figure this out. And, at the beginning, we had some problems, of course, which we had to overcome. So, MD simulations are different in terms of science. So, sharing is similar by large file sizes, different file formats, and also, you often get untrocessed, broad trajectory files. Additionally, the visualization of MD simulation demands some kind of specialized standalone software and also process data. So, in the end, some expert knowledge, how to install it, how to set it up, and this heavily limits the audience to which MD is available. And, besides the technical aspects of this, it also limits the degree of how MD is shareable, especially visually. Luckily, for most of these problems, they were already solutions out. So, for example, the best and the easiest way to share visually is via the web. So, quite some time ago, web browsers could not display 3D content. It just had, just by itself, needed additional plugins like Java App, Plets and Flash. Only recent tool developments and the increasing rise of web as a platform for application led to developments like HTML5 and JavaScript language and WebGL. With WebGL, we are now able to directly interact with the GPU to calculate on there and improve rendering performance and the quality, notably. And these are now standard in every modern web browser, so you don't need to implement there anything anymore. And Alex used this to implement the NGL VR in our lab. And with this, you are now able to visualize huge structures like surface and represent in surface or all-item representations with more than 1,000 up to millions of atoms. That's no problem anymore. So, you're here actually in a web browser, so you're actually looking at this and I'm manipulating the view for you. That's not the view. Three years later now, the NGL VR is like everywhere. And this example shows that by using the NGL VR, it's possible to visualize millions of atoms. So, large, file-sized, huge amount of data. And that's exactly what's generated by emulation, huge amounts of data. So, that's in general a difficult anymore, especially if you only transfer those data which are interested for the viewer to satisfy its view. At that moment, NGL could not visualize and desimilize itself. So, large, file-sized is more or less overcome by the NGL VR, how it was processed with input especially. For the different kind of file formats, we were really happy to include the tools like MD Analysis and MD Trudge because they can handle many, many different kind of file formats like Amber Brown's, you all know this. So, we didn't have to take care about this. They processed quite in a nice way that you can easily send over files even smaller in there. At that point, NGL was also, so we added to the implementation of NGL the possibility to also visualize large trajectories. So, to remove the periodic boundary conditions and center within an instant, what most of the standalone software scan was just like a click, for example. And that's by its selection language and geometric features. And, yes, the NGL VR is a web browser VR which has a very, so it can be embellished like you saw before just in there, but it has also a very powerful graphical user interface where you can very easily change your settings, your inputs. And that also is, there's no need to install it somewhere. So, really everybody, even my parents, could use it. That's no problem. So, at last point, they almost done like to combine all these things together and make them shareable. And that's what we did in the end with what we called the MD server. So, the MD server is a program for interactive and remote exploration of trajectories by employer and client server architecture. And, so, in short, the tools to stream trajectories over the back. You have, like, a type sample, which it took. So, this was a simulation done by a former colleague of me, Roman Grigsok, who was also involved in the MD server setup. And, this simulation happened at Yana's lab, by the way. And I want to go with, you know, through an example. So, if you want, you can just open this link and splurge by yourself. But I will also show it to you. So, just like when you open the link, you come up to this graphical user interface. That's how we, at our lab, like, share simulation for our correlation partners, experimentalists, that they see what we see in the simulations. So, they can easily just, like, run the simulation. What you see here is, like, an already prepared session. So, we already choose, like, the representation and what they want to see. And the settings, how the simulation can be run. But even they can just change, like, for example, the stepsize interpolation types within just a click. And also, like, what they want to see, if they want to highlight more residues or things like this. These sessions can be, like, open available for everybody, but you can also protect them by hiding them so nobody can, like, search for them by password protection. So, depending on your needs, how you want them. So, this is, like, an example of how it is, what is how the, yeah, correlation partners get to use it. Like, for example, how you, as experts, can benefit from it. It's very easy. Like, when you install it via PiP or via Condor, so it's a Python package, you can then just, like, go into your projects folder where you have the simulations in there and then execute the empty server. Then it automatically opens a new browser file in there. You can import the structure. So, this is an example from running a simulation I just took from our cluster and, yeah, so then you add the simulation. You can also do this by the terminal. I just wanted to show you some things. And while I click on this app button, I add all of these parts of the simulations. So, what you can see, that's just the folder it contains. There is not, like, a summarized combined file of this. So, the server automatically adds all these different parts together. And then you can just, oh, yeah, you see, it's directly from the cluster, so periodic boundary condition is still on. But, like I said, I was going to click when I found the mouse. I can center it, remove the periodic boundary, superimpose it also with the first frame, yeah, then I can do the simulation in here. Actually, I would like to see, not, like, those together, but I would like to see one of them being static at the point. So, you can easily change the position you're looking at. For example, this is like, I can find this by the chain. So, ProA is the name of the chain. And then I can change this, maybe, center it also. And on the simulation, yeah. So, you know, this is static at some point. And so, you can see, you can very easily manipulate this. Why I fuse this, how I work, for example, yeah. For example, fuse it out. You can also directly connect to your server and visualize your simulation with all that you know. So, first, yeah, get them to your laptop or whatever you're working at. Another example, which I should be willing to show you. For example, for non-experts, would be, or for teaching purposes, would be something like a wiki style article. You can think about, instead of, like, having a different kind of membrane patches, which you then can simulate, try and see, interact with. You can think about something like activation mechanisms, like, that they really can see, like, how something is binding or how the proteins are moving within the cell. Instead of just having video, they can interact with it, look at specific parts they want to see. You can add also the functions about this, so not just playing with this around. We were not satisfied with just the text figures videos. They are not enough. Thanks to the VATAMOL man's NGL was possible. And also for ND analysis and NAMIC rich to handle all these file formats, we can apply this for so many tools. And thereby now we are able to share the simulations of the VATAMOL. And so we are not done with this yet. We are right now preparing some online tutorials in Bosch to make this more easier to use for others who still don't know that this is out. Also we are reaching out to journals and funding agencies that this is available, that they could, maybe at some point, also demand to get some trajectories or to represent the simulation of this. This helps also in the review process because then reviewer understands better what you actually did or what you've seen there. We are also continuously helping it, so making the transmission of the files faster, so further compression of it or how that it is submitted bitwise. And our close collaboration with Alexander was also continually improving the viewer itself. And we are also very happy to be part of the project like the 2GCR and where Janna will be talking more about this. And so I just want to thank my supervisor, Director Grant Alex from Huala who did really much during all the time. And also Ramon who was a great help in the project. So final question. Is this tool, is the goal of transparency, reducibility, reliability for a piece really like solved? I mean like, it's obvious, it's just the visualization. They're still like, you cannot get the structure from it. Oh yeah, I forgot to say, you cannot download the complete simulation out of the viewer. You could download something like, so you can make a figure of it or you can download a single PDF file of it. But you can't download the complete simulation. So I'm really looking forward to the next talk from Janna who's telling more about like, setting all these things together, combining this. Okay. Does this play with the MNTF at all? The molecular representation format from the beginning. Yes, yes, of course, of course. So all the structural parts are handled by the NGL here and I just developed the MNTF file. So it is working. How much money does it need to actually stream the trajectory? I mean like, the simulation, I'll show you, I'll send you, that was like, that is, it's shadowed in Berlin right now. So I actually don't know the numbers, but there's also another tool out, so the server is not there only to adjust this. There's HTML, I don't know how to pronounce it correctly. And they also did a study on like, who's doing it, which kind of... So normally we did not have problems and also like, to visualize the simulation, I just showed you also like, has all the atoms and everything in there. You of course can speed things up if you can move. That's the question.