Dr. Henry Rodriguez has provided a very broad and comprehensive overview of need for proteogenomics research. In today's lecture, he will discuss about two more latest initiatives, International Cancer Proteogenome Consortium or ICPC and Apollo Network. The cancer moonshot program is a very ambitious initiative from US government and now it is also expanding with various other international countries to build the networks where all the countries could start sharing the data which could accelerate cancer research. These initiatives by Dr. Henry Rodriguez are not only accelerating the cancer research but also helping in worldwide data sharing. Dr. Rodriguez will talk about Apollo Network which has applied proteogenomics organization learning and outcome. The emerging field of proteogenomics aims to better predict how patients will respond to a given therapy by screening their tumors for both genetic abnormalities and protein information. An approach that has been made possible only in recent years due to advances in proteogenomic analysis. Dr. Henry Rodriguez will demonstrate how cancer moonshot can accelerate the cancer research, how it can make more therapies available to more patients while it will also improve our ability to prevent cancer and detect at an early stage. Lastly, Dr. Rodriguez will talk about NCI Genomic Data Commons. The mission is to provide the cancer research community with a unified data repository that enables data sharing across cancer genomic studies in support of precision medicine. So let us welcome Dr. Rodriguez for today's lecture. So CPTAC today is not the only one that begins to blend the worlds of genomics with proteomics. Two other programs really have come into play and a lot of it is attributed to the cancer moonshot. One of them is referred to as Apollo and the other one is referred to as ICPC or the International Cancer Proteogen Consortium. And again the part that is quite nice about all these three is that now they do they blend these worlds together but everything that we produce genomically, transcriptomically, proteomically and from an imaging from the pathology suite and from the radiology suite we place it in the public domain. So that said how are these other two programs and what is their relevance Apollo and ICPC that comes out of the cancer moonshot. So the cancer moonshot is an interesting program. This is something that was launched in January of 2016 and at the time that was being led in fact the inspiration was the former vice president of the United States Joe Biden. And the part that struck me the most was the simplicity of the overarching goals that the cancer moonshot wants to achieve. And that was accelerate progress in cancer. In other words if something would take ten years can you condense it down to five years. There's many ways that you could achieve that to be quite candid. But the last two are things that the CP type room within the US has been doing now for years. And one is greater cooperation and collaboration to be very clear that's not simply collaboration within your own laboratory with your colleague next door on your lab bench or with another person in another lab within your institution that really was implied on an international scope which is what they were trying to achieve. The other one was data sharing. Make all the data that's really deemed pre-competitive and place it in the public domain as a way of accelerating progress in cancer research. Now when this actually came out then I actually then was asked by the White House Cancer Moonshot Task Force to come up with some ideas behind it. The Cancer Moonshot is much larger than these two programs but one of the things they asked was individuals hey can you come up with ideas that we could see that might be interesting to develop. So what started going through my head was basically taking this idea of what CP type has been doing with the National Cancer Institute, blending proteomics with genomics and begin to expand it. So one of the things was well can you develop additional efforts and research groups that now have an interest to blend these two avenues. At the same time if you look at different organizations they would be the best to determine what cancers would be most relevant whether it be within their organization in the United States or outside of the United States. Furthermore because CP type has spent a lot of quite frankly time and money developing a lot of these metrics people will begin to adapt them as appropriate. They're not forced to do it because I think that's wrong but if it's appropriate we want to do that. But the part that was really nice was is that everybody would sign what now affects what we refer to as a data sharing pledge. And the pledge is basically a document and it does say it if you wish to partner with our organization the information you produce from this research collaboration will be placed in the public domain. We'll host it at the NCI or you could host it anywhere you want but we want to see it in the public that was the key thing for us. So the very first one that we decided to do was keep it within the US. So right across our hospital in Washington DC happens to be the Naval Hospital and that was the first one that we decided to start the deal with. And that program is now is affection referred to as Apollo. So Apollo involves the National Cancer Institute, the Department of Defense and the Veterans Administration. And Apollo basically takes the CPTEC model and we're rolling across all the VA hospitals and all the military hospitals within the US. The ultimate goal is to be conducting research that begins to blend the existing genomic-based methodologies that's been driving a lot of the patient care with now blending it with the proteomics landscape. Now this one when this got completed I thought my job quite frankly was done. I could give myself a nice pat on the back. I could go to my wife. Hey, you won't believe what I just ended up doing. My daughter would be like, wow, that's amazing what you ended up doing. It turns out it wasn't that easy because when this got done then I get another phone call. And the phone call is, well, we love what you ended up doing here but can you bring outside countries now into this mix? I thought it was an interesting call. So we decided to take the challenge upon us. So in summer now of 2016 we decided to take the program on an international level. Partly because we also had little collaborations with some institutions across the US but we decided to now formalize it across the cancer moonshot activity. So the very first country that signs onto this idea of developing this partnership with the National Cancer Institute becomes Australia. So we had Australia on board and we brought in four institutions. Now, again I thought my job was done. I satisfied a phone call. Nope, it's never that easy it turns out. When you deliver typically people want more. So rule of thumb, you want to under promise and over deliver which is what I've learned because the minute you start delivering everybody expects even above that now. So I ended up then getting that second phone call. The second phone call becomes okay we love what you ended up doing with Australia. And in fact it was great because the former vice president Joe Biden flies to Australia and he does his big opening. Another phone call comes down the road and the question is, well can you bring other countries? And by the way you have eight weeks to do this. I had no idea why eight weeks was relevant. I found out later on that it was going to be announced at the United Nations. But nevertheless I decided to take the challenge again. So in July of 2016 we ended up going from one country four institutions in a span of eight weeks. We expanded this now to eight countries and we brought in 16 institutions. Now this happens to be September of 2016. Obviously now we're in December of what 2018. So the question is whatever came of this program. So to my surprise but to my pleasure I have to admit this has now taken a life on its own. So this now is officially known as ICPC. This is the International Cancer Proteogenome Consortium. This now involves 12 countries spanning 31 institutions collectively all working together on just over a dozen cancer types. Some of these cancer types do overlap but that's actually fine because I'm the first one that I've wanted to know for years. Why for example individuals in the United States that are predominantly going to be of European descent develop breast cancer women. Yet these individuals a lot of it's going to be smoke based you find out.  For me the goal is very simple of ICPC. Ultimately what we want to do is develop a database a resource that now is finally going to be representative of the diversity of individuals along with their cancers across the globe and give all the information back into the public domain. So what has the program done in the past 12 months? Not you know since the time this thing was created. So here's an example of what we've done. So the very first data set because at the time people said oh you'll never get other countries to make the data public. No one's ever going to do that. I have no idea what people say this because if you sign a paper and that's part of what you sign on to it's like a marriage contract to me. Yes you said I will I do and you expect something to happen. And we're not having difficulty thus far. So the very first data set that got released was in September of 2017 by our colleagues in Taiwan. A very unique study that they ended up doing for oral cancer which is very dominant there especially within the rural population because of the peanut nut that happened to chew along with all the components that they add to that. Then at the same time what we did last year we actually held local cancer moonshot workshop as a way of raising greater awareness within the local municipalities. Same thing that is going to be happening here within the cancer moonshot activities raising the awareness that helps then those individuals those universities in those countries raise their own capital funding to launch larger initiatives within their own component. At the same time we actually so one was actually being held in Australia and the other one was done in Sweden. We also welcomed last calendar year officially two or three additional institutions spanning two countries. The very first one was Korea University which joined us in what October of 2017 and of course India joined in May of 2018. And we also launched an international or we piloted a student exchange program from Australia with one of our laboratories based in the U.S. The other thing that we're starting to do is because all this is research based pretty much use only is that we're starting to convert some of these laboratories on an international level to become CLIA certified and these are the targeted based assays. Why would it be advantageous to be CLIA certified? Because that means you could take the information that comes out of your instrument and take it directly back to a TUM award to give it back to a patient. So we're starting to build the infrastructure more and more on an international scope. This is a hugely fun program I have to admit we get together now at least once per year the very last time we got together was in the United States in the state of Florida. As you can see down on the right these are the other times that we've gotten together but now as a sense of pride we all get together and at the meetings we all hold our representative country flag because it's really multiple nations recognizing that cancer is simply not something that's locked to one nation it's an international effort that we need to resolve. So in the last five minutes let me talk about big data because I talked about that we give away all these data sets now first of all I love the terminology big data I have to admit I have no idea what that means anymore and being here in the past couple of days people are talking about precision based measurements what exactly is big that's a very subjective terminology is this big or is this big or is that big but people love to use phrases so I'll use them in my talk but when people talk about genomics within the National Cancer Institute one of the things that we're now we've started to do is we want to make it more easy for people to get access to our data sets. So now what we've done within the NCI is we're developing data commons so in the genomics landscape we've launched just last calendar year what's now known as the genomic data commons this is predominantly the data sets that comes out of the cancer genome atlas the part that's quite nice is that the ultimate goal is everything is based in the cloud you don't even have to download the data packets anymore and a lot of the software tools are all dockerized within the cloud itself so that's the genomics landscape so the question becomes well NCI what else are you doing because there's more than genomics and I remember Rodriguez you just said that you love the proteomics landscape mixing it with the genomics so here's what NCI is now doing the ultimate goal now for the Institute is no longer to have this genomic data commons it's basically to have a cancer research data commons and that's going to involve multiple modalities of the different types of omics obviously the one that I want to point out which is why we're here is we're going to be building a proteomic data commons and you'll be hearing lectures tomorrow exactly how the proteomics information is slowly being rolled into this landscape but if people want to play with it today they did have a soft launch this calendar year here's the website please go to it look at it play with it critique it provide your comments because those are things that we're trying to do this is basically as you have your restaurant it's a soft launch so this is like our alpha launch equivalent but it's out there now and ultimately the goal is all the data sets it's predominantly populated with the CP tech data sets but it all directly links back with DCGA and obviously the goal for us in the future is to have all everything based in the cloud along with the computational capability that we want to put into this but ultimately the goal is simply to have a cancer research data commons now lastly is this one these programs produce a lot of data sets I have to well so what do you do with the data well our investigators we do give grants and they try to analyze the data the best they can the question becomes is have you really taken or extracted all the knowledge out of the data that you possibly could quite frankly I have to admit my answer for many years was of course we've looked at everything you can look at the data sets so about five years ago I ended up meeting an individual named Gustavo Stolovitzky who actually came up with something called dream challenges and he has a he has an academic appointment in New York but he predominantly works for IBM and his comment to me was quite frankly he said you're an idiot I actually liked him when he phrased it because my comment was so what do you say this and he explained to me that he created something called challenges where he basically takes existing data sets that are out there and he challenges then the community just like you guys were doing with these questionnaires can somebody come up with a better way or a better algorithm to go after the information that either you could not extract from it or you did extract but it wasn't as efficient as time moves on with better tools that are now being developed so ultimately the goal that I came up with is this easy cartoon there's a cool little website you can actually take a picture of Einstein and you can literally type in questions that appears that Einstein is writing so for me this is exactly what I used to do when I used to be with a university setting is typically what you do when you run a laboratory is you do your experiments you collect a lot of information you find very nice correlations you try to develop these fancy graphs like volcano plots I saw being talked about yes very attractive you know they're quite complicated I think people just say nod their head yes I understand I don't know if they do but at the end of the day what you want to do is basically publish a paper it's a very effective model because what you want is these individual laboratories which are very elaborate like artisans that's a lot of the creativity that's out there and I love that landscape space but the question becomes is well what do you take that information and you put it on the public and you begin to crowdsource a question so that's what we wanted to explore so the very first one that we ended up doing was about two years ago and it was the very first proteogenomic computational challenge that was crowdsourced we teamed up at this point with with with the dream organization we actually brought in NVIDIA which is the graphical chip manufacturer we partnered with them they gave us some server frames for what they wanted to do but ultimately they also contributed a monetary award to this and we also partnered with nature methods you're not guaranteed to get your findings published but you're pretty much guaranteed to send it out for review which is quite nice but ultimately at the end of the day is we literally thought we would get maybe 50 individuals applying to a challenge to our surprise we got over 500 individuals that applied to the challenge and actually span 20 countries now this challenge predominantly was a biological driven challenge we took our data sets we basically asked simplistic questions so challenge one you could see basically is if we give you DNA and RNA how good are your predictors now determining the abundance if you give you DNA and RNA and abundance how good are your predictors at looking at the phosphorylation and the way that a lot of us now like the phrase it is the good news is you have winners the very good news is is that it turns out the computational tools are still not as good as a physical based measurement so people that are going in proteomics you clearly will have jobs for the years to come which is what I would like to say so but here's the part that really struck me the most is that out of the universities or the institutions that we thought would have won we're not the ones that won at all in fact there were groups that we never heard of within my own program so two of these challenges was won by colleagues at the University of Michigan and another challenge actually got won by a group at korea university now this was a biologically driven challenge this actually caught the attention out of the food and drug administration back in the united states and we decided to do a new challenge with them so now the FDA has launched the very first regulatory proteogenomic based challenge and here it is it's still technically ongoing so this one now basically again it looks at crowdsourcing it no longer involves the dream challenge although it's a partnership with them still but pretty much with the US FDA and what we're doing here is something that technically can happen if you take it in an individual sample and ultimately the sample goes to multiple laboratories one for genomics one for maybe metabolomics or one for proteomics in our case genomics transcriptomic and proteomics what if one of these samples become misplaced or mislabeled and the information comes back so we ask that question and using either genomics or then taking genomics and throwing proteomics how easily are you able to identify and most likely put the information back to identify where the mix up occurred so this is the very first one with the FDA and it's still open if you quickly want to join it but hopefully the goal out of this is that it kind of shows is that when you put the information in the public domain there is other utilities behind it so lastly what I want to say is I hope I hope that I've been able to kind of demonstrate how what we've been doing now at the NCI and now with these moonshot based efforts whether it be in the US or in an international level is that at least for me I'm one of these converts to me I actually come from a genomics background people ever look at my old history but I'm actually convinced is that if people talk about precision medicine or precision oncology for me that's really what I like to define as a team sport it's not genomics in isolation it's not either metabolomics in isolation or it's not proteomics in isolation if these technologies are robust immature and the quantitative and there's the ability to combine them to me that's really what fulfills the underlying story of biology and really could push precision oncology even further so with that I want to thank everyone for your attention I'll be more and be glad to address questions at this point thank you everyone sir though it might be more ambitious what I must do for once you please talk to NCI with the cancer research data comments alone how do you include aging and the diabetes into those okay so if I understand it correctly the question is for the data comments of NCI can you include aging and diabetes so aging is part of it because that's part of the metadata that we want right so all the electronic health records comes along with it but diabetes is a very difficult one because obviously so so the way that I phrase it is if you look at NCI C is cancer so but you know it's interesting because one of things that within our assay portal two years ago people were asking me we would like to deposit our assays into your portal and actually they were coming from the diabetes Institute and I'll be honest my my first reaction was no because ours is oncology but the more that I started to kind of think about it is really almost all biology plays a role in all these diseases so I'd say as things evolve there's always these possibilities so there's a couple of there's a couple of in there yeah so so within the US there's a couple of sites that you're allowed to download certain certain types of information so so but when you apply to it obviously you have to identify what the information is going to be used for because the higher level of criteria so so typically treatment naive information that's more simplistic get your access to but the more you start moving into that space and if it's de-identifying and and if it is made available it's just a higher rigor to get access to it NCI is now also investing in these alternate medicines of like so is there any kind of future thinking of so when you say alternative medicine I'm assuming you're talking more natural products yeah yeah yeah so that one I actually don't know if that sits in the population set I do know NCI does have a big repository of natural products and they're trying to identify more application that it could be applied to quite frankly I don't see why not if that won't be part of it but at least I'm not aware of any activity at the moment oh yeah I'm not from cancer background right but my curiosity to know about this okay it's fine whatever you are doing to treat to get out of this cancer but is there anything like that what kind of people is the most prone to cancer that kind of so the question is let let me make sure that I understand it so yours is are you able to identify individuals that could be more susceptible to the development of cancer so so those are epidemiology-based studies right where you're trying to understand the environment the food all those components I mean those are separate components within the NCI those things do exist as as part of the organization that they go after that is the number one question that I guess how so how can we guys don't do metabolites my god you guys need metabolites so I yeah so I I personally like to simplify things and from what I've seen is that it is already so complex quite frankly just to mix proteomics with genomics and transcriptomics adding another layer of complexity even makes it more complex so what I tend to always want to know is a very simple question you ask the people already that are understanding that disease and then you ask them do you already use metabolites first and foremost to screen something of that individual for that disease of interest so for example GBM right so like brain cancer people develop panels now so we do have a GBM project metabolites is part of the formula but but but but at least what we try to avoid because it just adds additional time and cost is we really want to make certain that you just don't do something for the sake of doing it you have some logic on why you would like to do it but the reality is we are playing with it but not to the scale that we mix DNA, RNA and proteins it's just a side project at the moment in conclusions we understand that how much initiative has already been taken by the NIH to manage multimodal data in the form of repository and global databases the genomics transeptomics proteomics imaging data when come under the same roof and analyze properly could provide many new facets many new unrevealed facts pristine medicine success story could only be written when large number of data set from all omics field are together analyzed thoroughly and then only meaningful conclusions can be drawn though we are generating large amount of data from NGS platforms and mass spectrometry technologies but whether these big data sets are fully analyzed proper QC checks have been performed we have to look into all of this very carefully so let us thank Dr. Rodriguez for his wonderful lecture which has really set up a good stage for this course why there is need to look at new approaches of proteogenomic analysis now we will move on to the modules the very first module on the genomic technologies and the first lecture of that will be given by Dr. Kelly Ruggles next week talking about introduction to genomics thank you


Make great records that are compelling that speak to where you are as an artist that speak to your soul gives people hope Taps into your fan base do all that. I'm not trying to we're not trying to make viral songs We all try to make great songs that have moments. Yeah, that can have viral utility Which call us crazy if you want everybody's growing looking for 15 second moments on their phone everybody y'all doing it I'm doing it. You're doing it. Look at something to captivate me these 15 seconds. That's dope


Hey, what's going on? That's one in the craft box. My name is Phil and today I'm joined here with Brent And we're playing on the pixel one server again and Brent's completing gems because he needs to catch up with me No, he just no life this game when we're not recording Do I just talk to Falkner. Yeah, just throw your pokeball at Falkner I'm trying to get in I'm gonna send a poke you want to help Go Gengar help Brent Brent Gengar's up there. I'm nice nice come back to me Jesus Gengar But a lot of trust in you need follow through See another part there.  I want to come in to see He's in bravery. Nice. Well, he is in bravery. Let me end you fought What? How's he gone? He's still fighting bravery No Jota he's a flying bike. No, really fun. That's a flying Jim. I wonder why it's a flying type Hey Souls in nine.  No And tell which Pokemon you're using for jumping you can see that you're using our block Go our block I'm gonna lose this No, trust me. You've got this. I believe and you Brent You got this him nine. I Really don't think so if I was allowed in what help Oh God go help him blazer Blazers there for support rent Oh, no tell it to me. Don't worry about it. What I've got one Pokemon there and that's lepros and Lepros is your hope use ice moves. There's only one move that I can use Which is the ice move ice beam. Yes Good move.  Oh Well, rip, let's go back home And we'll do some trades and see if we can help rent out to one Okay, so since you found that I have two Pokemon that you can use I'm so sorry about that We're going to help you by using you down on And you don't mean to swap them for He anyone maybe lapras not though Yeah, there you go Ripper on your bocorone. I can't press. Can you put your thing in? It's in Okay, and this guy Wait, who's my next last level who should I trade him for fly gone snorlax zappy or lapras or Charizard? Ah He's used zappy Zappy Cool, and now you should be out of one Who should I start with?  I believe in you. Oh This train it can only be better once a day. Oh Ripper on well All right Are you at home? Yes? Okay, so we're going to go on an adventure You're going on an adventure You're not golden nuggets. Yeah, I got golden nuggets from you Yeah, I got golden nuggets from you too of them. I May have thrown golden nuggets at you also, but Do you have a flying type my friend Do you have good parking? Yeah Good, so what we're going on an adventure We're two Going to wait till it's morning time way and I'm gonna give you one thing and We're going to go fly around come back here. Where are you? I Needed to give you something So we can get good stuff Oh, it's Dali's dying in the snow. Oh Shit save it. Don't let it die.  Oh, I nearly fell down the hole, but it has a letter so I didn't I'm going down to the bottom of it Think I know Where are you Brad come home? I need to give you something and then we're gonna start our adventure. No, I'm already starting my adventure But the adventure doesn't need you to go underground.  Hey, I'm gonna give you an org so you can talk all places And why you don't actually have to tell good places I'm at home Okay here This is an all static soul When fall that you can it can summon the legendary Pokemon Zapdos But what you got to do to find Zapdos is find a shrine to Zapdos and that's in the Extreme hills by on so what you got to do is you got to get your your good old friend tropius And you're gonna fly around And find the extreme hills Bounds and you're gonna find this Also fine Finding rare Pokemon the way or so you could use Charles up. I have a All frozen souls, which lets me summon the amazing Pokemon up out of Kunon Which I can fly around places as well So fun. You want to know a spooky story Spooky scary stories and story. Yeah Really? Okay. I want to learn tell me a basic tell me the story. So once upon a time There was this dark Pokemon there was this Go do you there was this dark Pokemon also known as No, you don't you don't actually know his real name nobody does this. That's why it's a spooky story So this pokey mine You never know This Pokemon. Yeah, we're nice house here this Pokemon was was a very very very different type of Pokemon So it's a golden Jesus Listen, okay, it was very different type of Pokemon one day it went around. Oh, this is such a cool cheer That's such a cool cheer design. Oh my god. How? Wow Brains looking so attract look at oh my god screenshots What's that? What's that over there? Menti That's cool. That's cool. You know, okay. So anyway, there was this it was this Pokemon, right? And yeah, and it was very different It wasn't it wasn't like a normal Pokemon and it was very special. Okay, and then one day One day that it went down into a deep dark cave Right you're with me Yeah, and and it discovered this different type of Pokemon And this Pokemon that it discovered was an Ebra and he's like, oh, who are you oh? Atropia sello trip. Oh my god. Come look at this green I'm gonna come get it.  That's so cool. Um, anyway, so Just finish the battle fan one obviously. Yep, Ebra. Cadevera Alakazam made a Made the Pokemon turn into a Pidgeotto What? Yeah, so that's why it's a Pidgeotto. That's why Pidgeotto I'll just check this chicken man's house. That's why Pidgeotto exists So Alex so so because of Ebra, Cadevera Alakazam Ebra, Cadevera and Alakazam Ebra, Cadevera and Alakazam They combined it together their mystical psychic powers To make and to form other Pokemons into Pidgeotto and turned chicken into a Pidgeotto. Yeah Did you like that story? That is amazing story. Yeah Pokemon should like I don't look cat apes. Look Brent remember these cat apes We had them in the first episode and I've seen them. So I remember Zubats.  Oh I feel holy I'm not cursed. I am very uncurseable Okay, yeah uncursable This sugarcane farm is like really good like impressed Yeah, check your man is the like he's always on here. He's one of the most reliable people to be on here Like I'm impressed.  I'm impressed really impressed Yeah, yeah, I'm not at the moment. I'm not used to like minecraft textures I mean like my texture pack textures. I'm used to minecraft textures. I'm like, why is good? Why does glass look so good?  Okay, so fun is actually pretty up here. Slow P Well the Skype notifications, you know Who what's this? Let's eat a bit of food. I'm a bit dying I'm a bit did right now. I'm a bit did I'm getting your boat. Yes. I can't fly Um, who are you?  Cool, that's the upgraded version of Zubat.  Oh My he's still at his place. Yes. I'm look it's so like a mate like I can't describe how amazing His base is like I strive to be him He's AFK at the moment, but you could talk to him usually Like, oh my god, his base is so cool. Like why can't I do that now? I'm stuck Charizard.  I can't I can't get out because I can't use bats and other I can't fly on things. I can't ride on things and other people's bases You have to port to me. Oh, yeah, it's actually be a Sins Oh a new member Okay, so So anyway, we're gonna have to end the episode here fun Really? That was a very boring episode. Yeah, well, but someone usually is boring. Yeah, not much really happened We couldn't really do anything. So, yeah Do you want to do that? Well fun Do the yeah, I do the outro. I do you I triple do okay. Okay. I'm doing it. I'm doing it Hope you guys enjoyed this episode remember like comment and subscribe if you did enjoy it So we know you guys love it and we'll continue with pigs for one hope and That's it and bring you gonna say anything and remember craft outside the box Craft outside the box. Goodbye


Good evening everyone. Today's our topic is directional coupler myself Piyusha Shedgar. These are the learning outcomes for this session. At the end of this session, students will be able to design microwave circuits using basic microwave components. And they will be able to analyze the use of these components in the design of microwave system. These are the contents. So what is directional coupler? Directional couplers are flanged built-in waveguide assemblies which can sample a small amount of microwave power for measurement purposes. Mainly, the directional couplers are designed to measure incident or reflected power. It is used to measure standing wave ratio values and also used to provide a signal path to a receiver. So there are the two types of the directional couplers. One is the unidirectional. That is, this type of directional coupler used to measure only the incident power. Whereas bi-directional coupler used to measure both incident as well as the reflected power. Now the directional coupler is having the four ports with the waveguide junction consisting of the primary waveguide or it is main waveguide and the secondary auxiliary waveguide. So from this figure you can observe that it having the four ports, port 1, port 2, port 3 and port 4. So at the port 1, P i indicates it is the incident power.  So the main properties of the ideal directional couplers are given the points. First point, a portion of power travelling from port 1 to port 2 is coupled to port 4 but not to port 3. A portion of power travelling from port 2 to port 1 is coupled to port 3 but not to port 4. A portion of power incident on port 3 is coupled to port 2 but not to port 1. A portion of power incident on port 4 is coupled to port 1 but not to port 2. Port 1 and 3 are decoupled as port 2 and 4 are also decoupled. So the directional coupler having the three parameters coupling factor, directivity and the isolation. So how to define this coupling factor? It is the ratio of the incident power P i to the forward power P f which is measured in decibel value. So mathematically it is given by C equal to 10 log to the base train P i by P f in decibel. Similarly, directivity is also defined in decibel value. Directivity is defined as the ratio of forward power P f to the back power P b which is also measured in decibel value. And this directivity D is given by 10 log to the base train P f by P b in decibel value. Whereas the isolation is defined as the ratio of incident power P i to the back power P b which is also expressed in decibel. And mathematically it is given by 10 log to the base train P i by P b. Now before going to start the scattering matrix calculation you can pause video here and you can relate isolation with directivity and the coupling factor. How you can relate these parameters to each other? Yes, from the above definitions and the mathematical equation you can write isolation in decibel is equal to coupling factor plus directivity. Now what is two-hole directional coupler? It is one of the type of the directional coupler. So it is two-hole directional coupler that is two holes are provided here with the distance lambda g by 4. It also having the two waveguides it is the main waveguide and the secondary waveguide is also known as the auxiliary waveguide. And the two holes are provided to the main waveguide which is placed at a distance of lambda g by 4 where lambda g is the guide wavelength. So how to work the directional coupler? So here again consider the directional coupler which having the four ports port 1, 2, 3 and 4. Two holes are provided at this point hole number 1 and hole number 2. And these holes are separated by the distance lambda g by 4 where lambda g is the guide wavelength. Now the two leakages out of the holes 1 and 2 are in phase at this second hole. That is if the input is applied to port 1 that input is coming from the hole 1 and hole 2 at the hole 2 is in phase. Hence they add up here contributing to the forward power that is at port number 4. Whereas two leakages out of holes 1 and 2 are out of phase at the first hole. Hence they cancel each other making back power is equal to 0 which is true for the ideal case of the directional coupler. Now the directional couplers are also having the two holes or multi-hole. So depend on the number of holes there are the types of the directional couplers as shown in this figure. First figure shows the multi-hole directional coupler whereas the second figure shows the cross directional coupler. The magnitude of the power coming out of two holes depends on the dimension of the two holes. Now how to calculate the matrix for the directional coupler? Again that properties of directional coupler can be defined by its scattering matrix which is denoted with the letter s. Now first step is the directional coupler is a four-port network. Hence s matrix can be defined as with the order of 4 by 4 and these are called as the scattering coefficients or the scattering parameters as shown by the equation number a. In a directional coupler all four ports are perfectly matched to the junction that is there is no any reflection towards the source again and therefore the diagonal elements of the above matrix are 0. Thus you can equate the parameters s11, s22, s33 and s44 equal to 0. Use the next property as a symmetry property. sij equal to sji is used for the symmetry property that is the number of row for the first matrix equal to the number of columns for the second matrix. Thus you can write s12 equal to 21, s13 equal to 31, s14 equal to 41 and similarly for the other parameters. Now in ideal case for the directional coupler the back power is 0 that is there is no any coupling between port 1 and port 3 and therefore if the input is applied to port 3 output out of the port 1 is equal to 0. Similarly if the input is applied to port 1 output out of the port 3 is equal to 0. So in above property you can observe that s13 equal to 31 and therefore these two are equal to 0. Similar to port 1 and 3 there is no any coupling between port 2 and port 4 and therefore s24 equal to s42 also equal to 0. Now use all these above values in the given matrix equation A then the matrix becomes as shown in equation number 5. Here the all diagonal elements are 0 whereas these all elements are also 0. Thus we have the 4 unknown values s12, s23, s14 and s34. Now calculate all these values and by putting all these values in equation number 5 you are getting the scattering matrix for the directional coupler. So for that again use the unitary property. Unitary property is the scattering matrix multiplied with the complex conjugate of that scattering matrix equating it to unitary matrix. So this is the matrix take the complex conjugate of that matrix equal to unitary matrix. Now by multiplying this as you know that all the diagonal elements are equal to 0 by taking the combination r1, c1, r2, c2 and r3, c3 you are getting the equation 6, 7 and 8. Now take the additional combination of r1 and c3 and write the equation number 9. So by comparing equation 6 and 7 s12 square and this 11 is same and therefore you can equate s14 equal to s23. Similarly for equation number 7 and 8 s23 are same and the right hand is also same and therefore s12 can be written as equal to s34. Let us assume that s12 is real and the positive value with the letter p. s12 equal to s34 and it is also equal to s34 star that is complex conjugate of this s34 equal to p. Now from equation number 9 and 12 you can put this s12 as a p value and s34 as a p value. You are getting this equation equal to 0 taking p as a common p s23 star plus s23 equal to 0. As p is the real number it is not equal to 0 equate this bracket is equal to 0. So from this equation if you are considering s23 is equal to jy then the complex conjugate of that is equal to minus of jy that is s23 must be imaginary value. Now let s23 equal to s14 equal to jq therefore s12 equal to s34 equal to p and s23 equal to s14 equal to jq. Put all these values in the above matrix given by the equation number 5 then you are getting the matrix for the directional coupler shown below which having this real part as a p and the imaginary part as a jq. These are the references for this session. Thank you.


Now starting, all attendees are in listen-only mode. Good morning, traders. If you can hear me and see my screen, just type yes in the questions, please. And we'll get started here. All right, excellent. Thanks, guys. OK. Just copying a link here for you guys so you can attend the Advanced Order Flow webinar later today. In about 26 minutes or so. But this is the Bookmap Platform Details webinar. OK, so this is Bruce at Bookmap, risk disclaimer, trading futures, equities, and digital currencies involves a substantial risk of loss and is not suitable for all investors. Past performance is not necessarily indicative of future results. So let's just go through it here. There's two webinars today. Every day there's two webinars. One is this webinar here, the Platform Details webinar. And this is just to go over the basics so you guys understand what Bookmap is, how to connect it, the markets that it connects to, how to get it, and then some of the elements in the user interface, and then some of the Bookmap or the phenomena that Bookmap uncovers due to its market visualization, and then how to read it. So it's just putting those basics together. But then we have the Advanced Order Flow webinar that follows that. And this is at 11 AM Eastern. And it goes for about an hour. We go through a lot of detail here in the order flow. And starting to look at bigger picture, top-down approach into microstructure. And due to our analysis, then we start to anticipate future price movement by reading the order flow and what Bookmap is objectively telling us. So no bias. Just what Bookmap is saying, what is showing us here, reading it, then we can start to anticipate the movement of price. And that's the whole goal of this second webinar. So I'm going to put that link in here for you. So if you want to register for that today, you have it. And we'll start at 11 Eastern. So that gives you insight here as well, that when you register for Bookmap, it comes with education. So let's go back to the Platform Details webinar. And you can see here, Bookmap Educational Course, listed down below here. And this is, whoops, sorry about that, hold on. All right. So the educational course is available at any time. It's already been presented, and it's recorded. But it's a four-part educational course. And even advanced users have been trading for decades, may not be aware of some of these things. And it's nothing really advanced. It's just more into the microstructure and really what is making price move. Understanding those elements is important, very important. You see it on all time frames. So we take that data and then we, or that education, and then we cover that same process in the Advanced Waterflow live webinars. So you can learn about it, but then you can see it every day in the live webinars. And you can ask questions about it. So now that's the process here. So when you subscribe to Bookmap, it comes with the education. And going through that whole educational course there. OK. So let's dive into the website. And we'll define what Bookmap is, how to connect it, and what it costs. So just scroll down here a bit. There's an intro video in the beginning here of the website. We'll continue to scroll down. We also connect to US equities. And then I'm going to scroll down to and stop here at connectivity. So let's define what Bookmap is. We are a software trading platform with unique visualization capabilities. So we're not a broker nor are we a data provider. We connect to three different types of markets, digital currencies, futures markets, and US equities. Now the digital currencies right now is for GDAX exchange only. That's going to change soon. You'll have the capability to connect to other digital currency exchanges as well. And that data is free from us for the GDAX exchange. So even with the free version of Bookmap, you'll get access to live GDAX data. But for the US equities and for the futures, you need to provide the data. And this is how you connect. All of these different data providers here. And you can see that in the list here, we have some platforms. You can connect via the API of Ninja, TTX Trader Pro, and Interactive Brokers Traders Workstation. So you have that option if you want. However, it's better, much cleaner, better data to get it directly from the data provider like CQG Rhythmic, Gain, IQ Feed, Transact, and Dev Experts. Now, if you're not familiar with Dev Experts, it's kind of newer or maybe you've never heard it. This is for the connecting to US equities through DX Feed. And you can read about it here. And you get NASDAQ Total View, you can get EdgeX, or you can get both of them together as a combo consolidated feed. If you have questions about it, just ask me. Be happy to go through equities. Went through a couple of different webinars yesterday. Maybe you guys attended and looked at a lot of different types of setups and order flow phenomena. It's great stuff to see in the equities market store, where the larger players stick out a little bit better. Now, define what book map is, how you connect it, and then here is how you can get book map. You can get it yearly, 20% discount, or monthly. And then you have the different versions here. There's digital and there's global. And the digital version here you can see is free. Connects to a live GDAX account or exchange. You only get one digital currency at a time, though. That market's open 24 hours a day, seven days a week. So you can always see how book map is operating in a live environment. That's the whole idea here with the free version. Even if you trade equities or just futures, still you get book map up and running in a live market without any data fees or any, you can get it on the weekend and take a look. No problem at all. Now it's limited support. It's also limited education. So the digital plus version connects to GDAX exchange. You get up to 20 different digital currencies at a time. And you get a U.S. equities delayed feed here. You also get that in the free version. But you also receive the advanced education that I've been talking about and access to the live order flow webinars. You also receive full support. And you can trade right from a GDAX or right from the book map chart into a live GDAX account fully funded. You have that capability as well. You can also record and replay your data. So a lot of different features here for the digital plus version. So that's the distinction there. Now the global version includes the digital currencies. You get everything in digital plus, but you also get the capability to connect to futures market and the U.S. equities that I just covered. All right, now you will need to provide the data for those, but that's how you connect to those markets with book map global. Okay, now the global plus version, the only difference here is that you get all of our add-on indicators.   So to try to keep your stops from getting hit. Large lot tracker here. We're looking at very specific players in the market with our proprietary add-on indicators here and identifying their behavior. And balance indicators for both book and volume. Iceberg detector, great stuff. We saw a really good example yesterday. We're using in the advanced order flow webinar. In fact, I'll probably take a screenshot of that and put that on our webpage. Great stuff there. It's a new indicator. There's actually two iceberg indicators now so you have your choice. Using that new one though has been giving us some pretty good information. So it's hidden liquidity. You don't see it in the book. And we can identify that with these algos. Then we have a correlation tracker. You can add other markets onto the book map chart. All right, that's that. Let's just move on here. A couple other resources you might want to check out on Twitter, follow us here at bookmap underscore pro. You can see all sorts of data here. And this is about the new iceberg, for example. You might want to take a look. And then the YouTube page here as well. All sorts of videos here. This is the basic education. And just go through some of the playlist homepage. You have the intro video here. Intro videos, features and components. And then order flow video snippets. Watch as many of these as you can. This is the kind of content we go through in the advanced order flow webinars. All right, so let's take a look at book map and the book map interface here. Okay, we're looking at the NQ, okay. Nasdaq E-mini. And let's, you can see that there's, I have a lot of add-on indicators here. So actually I'm going to close those up. You can see like for example the sub panel here for cumulative volume delta. Let's close that up. Our iceberg detector here, I'm going to turn that off. We also have a historical VWAP. And we have a point of control indicator here, which is the blue line. We're going to close all of those. And we can look at those. We're going to turn them back on in the advanced order flow webinar. Okay, but we're just going to go through the basics here. All right. And all right, so just looking here at the book map interface, and what's going on here in book map. Well, for those of you who are new, you might be looking at something that you've never seen before. It looks rather confusing. What is this big blob here? It's liquidity, okay. This is the heat map in book map. This is the history of the limit order book. Okay, so let's go through the process here and we'll go through each element on the book map chart. Okay, there's only three of them though. So it's really simple, really straightforward and very objective data. Okay, there's no sort of indicator here or derivative of time, price, or volume. It's truly the market and very objective view of it. The three elements on this chart. Current and historical, best bid and offer. The volume that traded on that best bid and offer. And then the heat map here, which is just showing you the evolution of the order book, current and historical. All right, so let's switch those off. So we're gonna really simplify this here. And then I will, I'm gonna turn on a candlestick chart. We're gonna look at a five minute candlestick chart here. This is a view we're all accustomed to. Open, high, low, and close of a five minute period. Okay, now we probably, you know, depending on how long you've been trading, you might have been looking at this for years. All right, decades even. And there's so many problems here with the candlestick chart, okay? Number one is its aggregated data. Okay, it's a time period. And we don't know what happened within that time period. Okay, it's locked up. Okay, it's completely opaque. Open, high, low, and close of that five minute period, for example. Okay, what about the volume? Where did the volume trade? Precisely where did it trade on the candle? When, what was the speed of the move? Where was the microstructure? All of these questions, we just don't have an answer to. Okay, it's all completely locked up in a candle. And we can very simply start to look at just the price action of this candle here by turning on best bid and offer, okay? And that's a first element on the book map chart here is historical best bid and offer, okay? So now we have it. And now we can zoom into that area and we can look at some of these. Hold on a minute. Okay, and we can look at some of these microstructural areas. Okay, what I was mentioning before, okay? And this isn't, it's not a bad example. So what do I mean by microstructure, okay? Well, let's just put this whole five minute period into the chart here. So now between each dotted line is actually one minute. And the microstructural elements here, well, here's an area of consolidation. And it was broken. It was broken to the downside. This is, you know, really, this is truly microstructure here. Another little area of consolidation that was broken and the move down, okay? Now, look at this, you know, this is like an ABCD move. Well, there's actually one more leg here. But look at how the retest here came right back up to where it broke from, okay? You're gonna see that again and again even on the monthly chart, the highest time frames that are there, okay? So here's another little area of consolidation that was broken and it came down into this area here. Actually, that was now broken and it came back up and look at the little retest here almost to where it broke from here, okay? And anything that you guys notice in this little area right here, okay? Any patterns there? I'm gonna clear the drawings. As well as the reverse head and shoulders, okay? And this is obviously microstructure, but you're gonna see these patterns again and again.  They exist because of the order flow. And anyway, we continued on up. We came back up to where we kind of dropped from up here and then we continued to the downside. Anyway, the major point here is the, all of these kinds of microstructural areas, we want to understand how that evolves and who's in control and we're gonna see that with the volume and the heat map, okay? But we need to first see the microstructure, right? Now let's turn on the volume, okay? And let's see who's in control in some of these areas here. And this is not a bad example, it's pretty indicative. You can see them hitting the bid here and we see a lot of red, right? Clusters of red and that's the volume that is trading. It's aggressive cell orders. Let's zoom into this area and let me show you, okay? And these are those two elements in detail here, right? So we're looking at half a second between each vertical dotted line now. And you can see truly like how these markets trade. For that first element we defined best offers, the red line, best bid is the green line. The green dots here are transactions that take place on the best offer. These are aggressive market buy orders. And we have all of that detail here if you want to use this data tip tool down to the nanosecond level we have this data. And you can see precisely when this volume traded, how much and what type here, right? So not a lot of buying here, but look at the selling. Cluster of selling over here. Okay, about a little back and forth here, another cluster of selling as they continue to hit the bid here. And we can see precisely these details. So that's what we're displaying here, those two elements. And you can see if we continue to zoom in here, we're gonna really start to open this up and you can see down to millions of seconds here. Okay, even billions of seconds. We're recording every single market event. Now, as we zoom back out, we do aggregate it just visually, okay? Into a bigger dot and then that's it. Okay, so everything is very precisely recorded. None of it is aggregated. So you know exactly what traded here. Okay, here's our downtrend. Okay, hitting the bid here, clusters of selling, another one here and another one here. And then look over in this area here where the buyer starts to step in, right here, okay? Still in a downtrend, okay? And don't break the high here. We come back down, retest where we broke from here and we find more buyers starting to step in, okay? And then our head and shoulders pattern plays out. Anyway, those are two elements on the book map chart. Okay, now the third element is the heat map. So let's add that on, okay? And you'll note that this is what's happening outside of the transactions. Well, it includes transactions as well, like right in these areas here. But this is where they're bidding and offering, okay? And that's all it is. So it might look like a lot of noise, but it actually gives quite a bit of insight here. For example, look at them in these areas here, okay? And is this real liquidity? The answer is no, because they're pulling. Boy, I shouldn't say that, it is real liquidity, but they don't have the intent to trade because as price is coming down, they're pulling and they continue to add lower. They don't want to trade here, okay? Although they're in the book, they don't want to trade. They're pulling, okay? They pull again and they pull and then down here they stay in the book. This is where they actually decided to trade, okay? And this is fact, we know this, right? They stayed in the book. Some of it pulled and then some of it stayed in and look how the transactions take place right into where they're providing that liquidity, okay? In fact, they completely absorbed it at this price level here, okay, at 25 and a half, okay? Why is that? Well, because there was no more transactions below it, no more selling. Sellers dried up, they were absorbed, okay? And we go up and we go sideways for a bit, but these guys are out. We get another test down here and we see that the selling continues, okay? But at this point, they were absorbed, okay? And you're gonna note this kind of phenomena again and again, you're gonna see it on low time frames to high time frames, okay? And then maybe that puts a whole new kind of spin on how you look at what's going on in the market, okay? What's going on within these candles here, okay? Now, how is this whole heat map derived? Let's cover that and then we're going to go to the, we'll stop this webinar and we'll continue on in the analysis, because we really haven't gotten to a lot of analysis here. Good stuff down here, really nice, okay? Down at the figure 7,200, okay? Absorbed, completely absorbed here, buyer step in, all right? So we'll go through this in about five minutes in the advanced order flow webinar, okay? But for those that are new right now, let's continue to cover what's going on here in the heat map and how it's derived. So you have an understanding, a context of these three elements on the book map chart. And let's get rid of the candlestick chart, just really gets in the way. All right, so how is it derived? Well, okay, let's zoom in here a little bit. And then we'll start with this vertical white line here. This divides historical market and current market, okay? Current market is right here, okay? This is our current best bid and offer, okay? And this is the current market window and you see the heat map here, okay? Well, how is it derived? It is all derived from the limit order book, okay? Here's our price ladder here. And then you can see the red numbers up here. Well, these are contracts. It's liquidity. It's where traders are lined up to provide liquidity. They want to be sellers at these specific price levels and they're waiting to trade, waiting in line to trade at those levels, okay? So that's the sellers on the offer. This is your depth on the offer and now here's your depth on the bid and where they want to be buyers. And we can see them very clearly, right? Now, the numeric values that you see here, for example, let's look at the, a little closer here, 101 contracts, 100 contracts up here at 15. Now, when they start to change or pull and add liquidity, and you can see that is happening constantly. They're always adding and pulling liquidity here. It's reflected here in the heat map, okay? As it is right now, you can see it's down to 77 and it's yellow. So the scale of the heat map's up here, okay? That reddish orange is very high liquidity, yellow's less liquidity, then white, then blue, and then black is the lowest amount of liquidity. And here it is. They just pulled and they just started to add back in as price is coming up, okay? So in there, now we've traded through that area. But they pulled a lot of that liquidity, right? Well, let's get an answer here, precisely what traded here, okay? And how much, was it real liquidity? Did they stay in the book? And yeah, looks like 73 of those contracts traded, okay? And that's fact, okay? So now we know. And they were providing about 72, yeah, 75 here, and then 72 and then, you know, they stayed in the book. These guys are filled. They waited, they stayed in the book. They got what they wanted. They are short at this price level, okay? Feeling the squeeze here. Well, who knows? I mean, larger players like to layer in to these positions. So they're probably the same players that are up here as well. And starting to absorb even more. And starting to stay in the book as well, a bit here, a bit pulling as well. And you can see they completely pulled here, right? So what's starting to understand now, okay? Derived all from the limit order book in the current market. And then when they pull that liquidity, it's reflected here on the chart historically, okay? And it's these striations here that we see in the heat map. This is the adding and pulling of liquidity. So what this allows us to do is start to understand the intent of traders in the auction, okay? Here on the offer and here on the bid. Now we continue on up to the upside and they're starting to add in a little bit higher here at 22. We've seen all sorts of stuff here. Look at the bid is getting very aggressive here. 90 contracts at the best bid. They traded into it and we were finding, well, we found a few more buyers, now the sellers took them on. But we're starting to understand this auction here. This might be new information for you and it can be invaluable. It's real, we can make the distinction between those that have the intent to trade and those that don't. That don't. A lot of times you'll see or you'll hear from other traders that, well, I don't really look at the dome that much because all of these areas of high liquidity is fake and it's not true. We can see where they're getting filled or not. And now you can start to understand the context of that auction and that's what we're gonna take to the next webinar. So you guys have the link. Let me paste it in here again. Okay, there it is, it's in the chat. So sign up and then join us in the next webinar here. We do this for Friday, Friday only and then else you can subscribe. But it's to give you guys a taste of what we do in the advanced order flow webinars. All right, okay, we'll see you there, bye.