The first US HUPO 2025 post (by guest blogger Amanda Smythers)!

Ben: (Amanda is a postdoc at Dana Farber and some Harvard place and is the Chair of the US HUPO Early Career Researchers (ECR) Committee. Many of us picked up extra stuff, but Amanda pulled triple duty at US HUPO 2025 filling in for government reasearchers who weren't allowed to present to the public...cause... you know...).  

Amanda: 

The first time I went to US HUPO we were in the beautiful city of Charleston, SC. We had everything you could want in a conference – innovative science, inspiring atmosphere, great weather, a t-shirt cannon, and a Waffle House within walking distance. However, what really caught my attention (and kept me going back year after year), was the commitment to Early Career Researchers throughout the program.

If you haven’t been to US HUPO before, you can expect an ECR event every night. The last few years we have had the same general set up. We start with a “mentorship day” before the plenary, where we focus on skills like marketing yourself, negotiating pay raises, and visually communicating your science. The Monday night of the conference we have a “Speed Dating” night, where we talk about how to give an elevator pitch and then use the time to meet all the other ECRs in attendance. And last but not least, we have a “Lab Pitch Night” on Tuesday, where we put academic and industry/biotech lab heads in the hot seat and give them exactly 3 minutes to pitch why you should go work for them.

After benefiting from the incredible ECR programs in Charleston and Chicago, I joined the leadership committee where I now serve as chair. We were absolutely delighted to bring our largest program yet to Philadelphia and can’t wait to see what we can bring to St. Louis in 2026.

(Photos captioned by Ben, sorry about spelling ) 

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For the first time, we had two sessions for our annual mentorship day. In the morning, we focused on “Navigating Tough Conversations in the Workplace,” with four fantastic speakers: Dr. Stefani Thomas (University of Minnesota), Dr. Dominique Figueroa (Thermo Fisher Scientific), Dr. Baljit Ubhi (fractional leader and consultant, multiple companies), and Dr. Ben Orsburn (the man, the myth, the legend – now at University of Pittsburgh). One of my favorite pieces of advice was from Stefani, who aptly started by reminding everyone to be careful of advice! Not all advice is applicable and useful for every person. Bal challenged us all to know what we want, and that if you don’t ask for it, you will never get it. We spent a lot of time in the morning talking about negotiation strategies, and how essential it is to strategize what you request in a negotiation. The need to be flexible was certainly underscored, as a failure to achieve what you want in one arena may open you up to more negotiation power in another.  Dominique broke this down succinctly into three steps: 1) focus on one ask and an answer; 2) make the ask clear; and 3) take yourself out of it. Ben added to this with some easy ways to support asks, including looking at market value, knowing your worth, and not being afraid to aim high. I was particularly grateful that Ben reminded us how women frequently aim for lower than their worth at positions where they meet 100% of the qualifications, while men typically aim for higher than their worth at positions where they only meet 60% of the qualification (read more about this here: https://hbr.org/2014/08/why-women-dont-apply-for-jobs-unless-theyre-100-qualified). 

(Photo and captioning by Ben - definitely got the spelling right this time)

In the afternoon, we switched paces to talk about "Innovation 101: How to approach new scientific ideas, follow up on inspiration, and convince others it is worthwhile,” with another four fantastic speakers: Dr. Daniel DeBord (MOBILion), Dr. Michael Krawitzky (Bruker), Dr. Mark Condina (Mass Dynamics), and Dr. Sarah Parker (Cedars Sinai). Mark kicked us off by telling us that we need to know what we are good at, and use this inspire your vision, purpose, and motivation, as well as your ability to communicate with authenticity and create shared value. Daniel added to this further by reminding us that opportunity comes from the confrontation of scientific problems with passion and skill, and encouraged us to follow inspiration and not be afraid of failing (sometimes making something worse shows us how to make it better!). Michael encouraged a start-up mindset which includes adapting and pivoting when needed, accepting failure, embracing persistence, capitalizing on ideas, and trusting yourself. Finally, Sarah reminded us all that innovation can mean so much to so many people- including the implementation of ideas and creating teams. I love this mentality, as it can be overwhelming to always feel that you must invent something new in order to support innovative science.

For those who missed out, Mark put together a phenomenal list of resources here: https://tinyurl.com/53by7tcp. PS: I have to give a shout out to Mass Dynamics, who have constantly been supportive of ECRs and offered to help sponsor this event long before I met Mark!

All in all, US HUPO was yet again my favorite event of the year for getting inspiring and making new friends and connections. Next year in St. Louis!

Insightful article on the proteomics expert shortage!

 

As a lot of people know I've been trying to find the funds and opportunity to launch a formal degree program in proteomics for...a while... I'm cautiously optimistic that I might have found an interested audience with the money and the authority to make it happen. We'll see, though! Honestly - it can almost feel like escapism to put your head down and prep a couple hundred samples for an instrument right now - or submit a crappy grant - but there is only so much protesting and complaining that we can do. (That's what I'm telling myself, anyway!) 

As I'm rebuilding and upgrading the pitch deck from the last time I did it - there is all sorts of cool new stuff out there. Not only overly optimistic market growth numbers, but also things like this insightful article. 

If you don't feel like reading this - you could at least check out some excerpts like this one that I'm clearly going to be using. 

Of course, this, and probably my whole blog and enthusiasm for the growth of my field and science in general is all overshadowed by the terrifying and uninformed decisions being made in Washington DC - but -the US is a small landmass. And proteomics is global! 

Predictive markers of BRAF targeted therapy effectiveness!

 

Title first because - by page 2 I was thinking - 

1)  Can I get another espresso without waking my kid or his puppy up? 

and 

2) What a weird and crappy experimental design! I do need that espresso because I'm clearly misreading Table 1. 

24 solid tumors were analyzed? Across both sexes and a wide age range? They are all tumors? Like no healthy matched controls? Wait - are those tumors from different organs? Weird, right? 

The reason I'm continuing to type isn't (solely) because I'm procrastinating on 10 things I need to be doing. I'm continuing to type because it fucking worked! 

The question was totally a spotlight into the dark to illuminate an important area. The question is something like: We give people these BRAF targeted therapeutics when we find a BRAF 600E mutation and we don't know anything else about whether that's was the best idea or how well it would work. So they had this small set of frozen tumors from people who had this BRAF targeted therapy and they did RNASeq and proteomics (TIMSTOF) on them. They also know what regimen of drugs the patients were on and how well the regimen worked as broken down in how long the therapy kept the cancer from recurring.

The RNASeq pointed out a bunch of mutations but - no surprise to anyone here - it doesn't appear to have pointed out a protein that appears to coincide, maybe even correlate (unclear), with the time that the patient was in remission.

I guess the lesson here is something like - look - sometimes samples are super precious and you just don't have the numbers to assemble a cohort that makes sense - that doesn't mean you shouldn't take a look?

ABRF 2025 is next week! Don't miss the proteomics sessions!

Hey! Are you going to ABRF2025? It starts in 4 days! I should pick a seat for my flight! (Strangely you do that on SouthWest now??? Weird. 

I was asked to amplify some of the mass spec stuff that can sometimes get lost among the FACS and microscopy and inferior technologies like genomics/transcriptomics. 

Honestly, I have 6 different scSeq things circled on my calendar, as well as some microscopy stuff. 

There is still mass spec there! 

Self-serving, the session I designed is the first one that pops up (there will clearly be lightning talks and posters) but the first proteomics session got the super ideal timeslot of 4:30pm on Tuesday! 

I hope that we'll make these available via Webinar as well. Working on it. ABRF had a blanket deal with one of the big webinar companies and the squeeky wheel seems to get the limited time slots).

There will be a talk on technology from a vendor that I haven't gotten to see yet as well! 

Wednesday is a super cool session that I literally changed my flight to be able to catch. 

Artificial intelligence in proteomics? Let's goooooooooooooooo! 

Oh yeah...and there is Metabolomics! (Insert vomiting sounds here)!  

Got 3 minutes? Vote for TalusBio (and proteomics) to win a cool award!

TaluBio is this funky spinout company that has stolen some of the best and brightest young people in our field and is out doing crazy cool proteomics drug discovery work on rare diseases.

You probably knew that, but did you know that they're up for some big award against all sorts of funky startups? It's a funny list to go down, like one company makes autonomous tractors. Hopefully.... by... developing their own algorithms and not using these... no one wants what happened to Jeremy Renner (he got better). 

You can go to GeekyWire and check it out (and vote for TalusBio) here! 

SpectroPipeR - Clean up those .SNE files with this R stuff!

 

I can't wait to try this and compare it to DIA-Analyst! 

Actually tell if it is an ADP-r or a PolyADP-r with insanely hard sample prep!

 

If you're ever feeling really good about your skills as a proteomic mass spectrometrist and need knocked down a peg, I strongly recommend going into the amazing field of ADP-Ribosylation. This amazing modification can be one ADPr or long chains of repeated ADPr. Sounds fun, right? 

Glycoproteomics is great because there are like 1-4 sugars for each mass and they can go on like 5 amino acids? I forget, and each sugar chain can break in like 2 or 3 places. 

ADPr cranks up the fun by each monomer fragmenting in 7 possible places, the mod can exist on 11 different amino acids and - again - each monomer has the exact same mass. 

Look at this awful thing (from this great JASMS paper from a couple years ago) 

Sign me up for citrullination on an Orbitrap (please don't) or phospho vs sulfation vs nitration on a TOF (for real, no, please don't) any day of the week. 

So Anthony and Isabel had this great idea of MAKING THIS HARDER. Because the way people do it is to cleave it down to a much smaller mod, so you know that there was an ADPr, but you don't know if it was one or a chain. 

It took a village - and maybe like 5 years (including pandemic times which we all know like only sorta counts) but Isabel actually pulled it off. 

To really get it to work - you need that ETD + HCD (EThcD?) thing that you can only get on Tribrids. And while the preliminary work on Chan-Hyun Lab Lumos(es) looked good, you can really see the benefits of the enhanced signal and improved fragmentation dynamics on the Eclipse in Ben Garcia's lab. This didn't make the manuscript - but - wow - does this stuff look better with the labile mod workflows in the newer MSFraggers and huge thanks to Dan and Alexey's team for extra help setting those processing things up. 

NIH BioArt has a Q Exactive!

 

If you're rapidly drafting some figures - Biorender can be super cool. But what if you don't have a license? NIH BioArt is adding stuff all the time! 

https://bioart.niaid.nih.gov/

Proof? There is no way that it had a Q Exactive when it first made my blog last year! I would have found it, but now it has it and more free/open art to use to really drive that dumb point home that you're trying to make! 

While you're there check out how much cool new stuff has been put on NIH 3D! 

https://3d.nih.gov/

Mandatory reminder that these government resources are probably at risk right now. I mean... we should be concerned about how we will do science if PubMed is no longer a thing....

EasyPubPlot - Super simple amazing customizable plots in like 90 seconds!

 

Where was this when I was stinking up the NIH submission system with my crappy grant applications? 

You want a 110 pt font axis? You get a 100 pt font axis! 

Introducing EasyPubPlot! 

And I'm not messing around guys. This isn't easy for someone who knows off the top of their head what version of R is on their computer. I'm not talking easy for someone who knows the difference between a .txt and a .tsv and a .csv that only opens right in Notepad++, not NotePad+ or NotePad-

I want to take the vomit inducing plots from SpectroNaut and make a plot that is not vomit inducing? 

I go here. 

https://pharmaco-omicslab.shinyapps.io/EasyPubPlot/

I put in a .csv that contains my protein, my fold change and my p-value and -BOOOM volcano plot! 

Is it going to impress your bioinformatics friend carries a shoebox of hard drives with them wherever they go? No. Because he/she/they can make a volcano plot some other magical way that I can not. 

Did I make the nicest proteomics volcano plot I've ever made in my life in about 90 seconds? HELL yeah I did and then I cranked the fonts up to 110 and turned off the legends and swapped the colors around. I DID THIS WITHOUT LEARNING ANYTHING. AT ALL. 100.00% of my brain was focused on a ridiculously good bibimbap. 

For real, it's like they took everything I need to make plots and simplified it down to just those things. It's like what the Red Elephant did for manual peptide sequencing. Or simplifying Prosit down to actually what I need from Prosit the way EL FRAGMENTADOR does. 

I've been paying for and using GraphPad for 5 years and I can't make something in it that isn't hideous without 4 hours of work. It's eventually okay, but - man does it start out dumb every time you put data in it. EasyPubPlot just makes nice plots! 

It does more stuff than Volcano, too! This is just what I'm most excited about. 

The heatmap feature is nice, but if you need a heatmap the Broad's Morpheus toolkit is probably a little nicer and it has embedded statistics. But if you just want to make a nice publication ready bubble plot or box plot - the tutorials are ON POINT. 

Is there a problem? 

The pub is short for "publish" but could you make a publication ready volcano plot at a pub? There is only one way to find out, probably. 

Too lazy to read? Navigate NCI resources with DrBioRight 2.0!

 

Just like everyone else, I'm absolutely fucking thrilled to see Artificial Intelligence showing up all over the place. A lot of commercial websites now have slow new AI functions that are essentially "ctrl+f" in your web browser - the kind of improvement is assume Elon Musk and his fans are most excited about. 

(Another amazing new success from Mr. Musk this week. Add that with the fact that they're  

now leasing office space for HHS bioinformaticians to log into AWS to do their work...cause that's a cost savings over them logging into AWS from spaces that cost the HHS $0! .... Though my favorite thing this week is the stated attempt to put AI into all government databases.. ..which...run...on.. .COBOL.... if you aren't familiar, when I took Fortran 77 in highschool (the 77 was the year that version of the language was finalized - which is a good summary of Appalachian high schools in the 90s) my teacher would make fun of COBOL being old and useless. Totally going to seamlessly integrate with AI. No worries there. 

While I'm ranting you can absolutely buy this at BestBuy right now. Just in case your "smart washer" from 2018 that is the single worst appliance you've ever owned in your entire life needs downgraded for 5x what a non-smart washer/drier that works costs! 

With that lead in! 

Introducing Dr BioRight 2.0! A large language model to search NCI data! 

If you're thinking something like "oh no, did peer reviewers see the words 'large language models and multi-omics' in the abstract and just accept it without ever looking at it?" you're probably a cynical jerk. Geez.... I mean, that's exactly what I thought, and that's why I spent my morning trying to see if this LLM could actually do things (other than generate "Internal Server" errors, which, to be fair, it generates an awful lot of) 

Short summary? There is some value here, I think. Particularly if you're not a big fan of reading, but you're patient enough to ask an algorithm to dig through some results for you, and you aren't patient enough to dig through said results yourself. 

For a bad example - I went to a pancreatic cancer dataset and I asked Dr. BioRight how often KRAS mutations show up in the cohort. Since it's the most mutated gene in that dataset, I figured it would skim the abstract and give me the answer. It didn't. ChatGPT400 or whatever it's called now will do that for you, that's not why you want to use this tool. 

I got frustrated, saved this blog post in my "do not push the publish button, Ben" folder and moved on. I went back because it popped up in my newsfeed and then I grabbed a random dataset and started asking it stuff about the source data in the study.

 And this is where things get really interesting. In this study with a 65 patient cohort I just asked what the most commonly mutated genes were. It appears to generate R commands and run them?  

That's actually super legit! Slow....but it really sounds impressive. Now - I'm not checking to see if this is actually right, but you can see where this might be an asset.

You don't go to an AI to make art for you because you know how to make art. You don't ask ChatGPT to write something for you if you want it written well and accurately. And you don't want to ask Dr. BioRight 2.0 about a cancer study that you reanalyzed yourself and contributed to a paper on. But if you are interested in skimming publicly available data for stuff you want to dig into depth on, it is faster than pulling the manuscript source data, figuring out which table is the one you want, and looking for it yourself. And that can probably be of use at times.