Alison Chaves

Well, you will probably appreciate the hall of shame of WB and SDS-PAGE www.ruf.rice.edu/~bioslabs/st...

It would be amazing if the report.parquet could report the adjacent sequence. Let's say 4 AA before and after the peptide Stripped.Sequence. I do it with left_join from UniProt
id_mapping. This would make the graphical output more complete (as in PSManalyst for FragPipe, github.com/41ison/PSMan...)

The Zeitgeist

I respect the energy and work you put in the Proteomes. It is not on the good people like you and others I know working for MDPI journals. The editorial group reputation is quite often exposed to this kind of problem.

Holy crap, what is happening with the undergraduate microbiology courses?

I can't find the actual publication, but it is quite impressive the level of "don't give a f*" that MDPI gives to peer-review process. Look at the Fig 4 in this one: www.mdpi.com/2079-6382/14... (a mitochondria inside a bacteria!)

Would be interesting to update that graphic of price over the feature (resolution and scan speed) of interest and the percentage of the sales per manufacturer. I remember Bruker gained traction with timstof family.

Chomsky is a terrorist now! Stupid people do stupid things as elect Trump.

A great contribution for de novo field

Have you seen this one, @ucdproteomics.bsky.social ?

PepMapViz: a versatile toolkit for peptide mapping, visualization, and comparative exploration AbstractSummary. PepMapViz is a versatile R package that provides flexible peptide mapping and visualization capabilities. PepMapViz can import peptide dat

Really need to thank Zhou and cols. Great inspiration on how to represent PSM features in protein sequences freely available to the community.
PepMapViz: a versatile toolkit for peptide mapping, visualization, and comparative exploration url: academic.oup.com/bioinformati...

2007 🤔

Only NVIDIA (remember you will need CUDA). The RTX A4500 20 GB GDDR6 4DP seems to be a good option.

Side note: NVIDIA is not a personal preference. All these algorithms use pytorch, which needs CUDA. Nowadays, there is this ROCm from AMD, but no guarantee it will work. All other specs are flexible. Any 24+ threads 64+ Gb RAM will work. Don't save in GPU if de novo will be routine.

If you are going to run de novo search, you will need a dedicated GPU. Casanova, Instanovo, Cascadia, and this DIA-BERT will take forever running in CPU. If possible, use an RTX 4000 quadro. Downgrade for cheaper RTX series if it is too expensive. NVIDIA always.

yeah, gauge of the needle, choice of the anticoagulant, material of the tube (glass or plastic) and several other factors. I guess it is more a matter of be aware of these things, it is hard to standardize this in clinical samples.

EvoSep is great but quite expensive compared to common nLC. The input is critical for several samples. This alone is enough motivation to choose the nLC system. If people find a way to make microLC useful for real samples, let me know.

Not convinced at all. Only real difference seems to be at 50 µL/min compared to nL and others flows. Furthermore, you pay the price of huge input of sample. It looks more like walking to the past.

This reminds me of the case of ubiquitination Degradation Pathway inside of chloroplasts. And I don't know why.

Feijoada? do we have a Brazilian here? 🤔

Fungal Biodiversity From the Atlantic Forest With Bioactive Metabolites Against Cutaneous Leishmaniasis Biodiversity offers a rich source of bioactive compounds for drug discovery. We isolated Aspergillus fumigatus from compost in the Atlantic Forest and found its extract active against Leishmania (Lei...

Bioprospecting from Atlantic fungal biodiversity.
onlinelibrary.wiley.com/doi/10.1002/...

#USP you can do better.
Um edital de concurso público com exigências nada razoáveis. Bastante suspeito!

Quick check: Is it common for your institutions for the competition announcement to require candidates to collaborate with very specific people (including their names)? Apparently, USP in São Paulo-Brazil has a very specific interest for faculty position as assistant professor.

The data is pretty new. Check again in a few weeks. It is on the repository side, not the authors or reviewers 🤷🏻

Yes, it is hard work, but old instruments still can be perfectly used today. We extracted >7k proteins with good quantitative features from an Orbitrap Elite.

Thanks Luke, non-tryptic search is definitely a nice case where the app can help. I will keep it updated with new features in the future.

You can recursively import all the psm and protein files at once or perform a more in detail analysis with a single psm file. If you have any suggestions on what could be nice to have implemented in the app, let me know. I will find time to improve the code. :)

PSManalyst: A Dashboard for Visual Quality Control of FragPipe Results FragPipe is recognized as one of the fastest computational platforms in proteomics, making it a practical solution for the rapid quality control of high-throughput sample analyses. Starting with version 23.0, FragPipe introduced the “Generate Summary Report” feature, offering .pdf reports with essential quality control metrics to address the challenge of intuitively assessing large-scale proteomics data. While traditional spreadsheet formats (e.g., tsv files) are accessible, the complexity of the data often limits user-friendly interpretation. To further enhance accessibility, PSManalyst, a Shiny-based R application, was developed to process FragPipe output files (psm.tsv, protein.tsv, and combined_protein.tsv) and provide interactive, code-free data visualization. Users can filter peptide-spectrum matches (PSMs) by quality scores, visualize protease cleavage fingerprints as heatmaps and SeqLogos, and access a range of quality control metrics and representations such as peptide length distributions, ion densities, mass errors, and wordclouds for overrepresented peptides. The tool facilitates seamless switching between PSM and protein data visualization, offering insights into protein abundance discrepancies, samplewise similarity metrics, protein coverage, and contaminants evaluation. PSManalyst leverages several R libraries (lsa, vegan, ggfortify, ggseqlogo, wordcloud2, tidyverse, ggpointdensity, and plotly) and runs on Windows, MacOS, and Linux, requiring only a local R setup and an IDE. The app is available at (https://github.com/41ison/PSManalyst.

It's now properly published. If you want to easily check important characteristics of your data before diving into complicated statistics, check out PSManalyst.

PSManalyst: A Dashboard for Visual Quality Control of FragPipe Results | Journal of Proteome Research pubs.acs.org/doi/10.1021/...

It sounds like a Synapt G2 thing, but it works.

holy crap! GPT5 sucks in math