Maria Ulmer (née Wörheide)

PhD candidate at the @KastenmullerLab
@ICBMunich 🧠🧬💻

[Maria Ulmer (née Wörheide) @mwoerhe]

Very excited to finally share our preprint on the AD Atlas (https://t.co/WUMMtFgIqG) - an integrative multi-omics resource for AD research 🧠🔍 Thank you to @_MatthiasArnold @KastenmullerLab @AMPADPortal @Alzheimers_NIH and all our amazing collaborators!
https://t.co/rGTGIlc1eu

[Maria Ulmer (née Wörheide) @mwoerhe]

@pietznerm Thank you Maik! 😊

[Maria Ulmer (née Wörheide) @mwoerhe]

@gwoerhe Thanks Dad!! ♥️

[Maria Ulmer (née Wörheide) @mwoerhe]

@_MatthiasArnold Thank you so much, Matthias! I couldn't have asked for a better supervisor. 😊

[omicscience @omicscience]

By popular demand, full genome-wide summary statistics are now downloadable for our cross-platform metabolite study at
https://t.co/qAjXWPooRB

Please spread the word.

[Kastenmüller Lab @KastenmullerLab]

Amazing work lead by Claudia Langenberg and team, exploring the genetic architecture of protein-disease links! Also check out 👉🏼https://t.co/GCOZ5mYgSq for an interactive version of the proteo-genomic map and more! @pietznerm @eleanorwheeler #openscience #genomics #proteomics

[omicscience @omicscience]

🚨paper alert🚨
We are thrilled to announce that our work on the #Genetics of ~5k #Proteins is out @ScienceMagazine
>10k pQTLs creating a #proteogenomic map of the human phenome
@MRC_Epid @berlinnovation @KastenmullerLab @GSK @IMS_MRL @UCL_IHI

https://t.co/E8gri3y1ja
🧵👇

[Maria Ulmer (née Wörheide) @mwoerhe]

@gwoerhe Thanks dad!! ☺️✨

[Matthias Arnold @_MatthiasArnold]

Excited to finally share our preprint on the multi-omics AD Atlas (https://t.co/F54w7ZvxqL). Thanks and congratulations to @mwoerhe for driving this huge effort! Enabled by @AMPADPortal, @Alzheimers_NIH and all contributing partners. #AMPAD #ENDALZ
https://t.co/OvhvWYhsVP

[omicscience @omicscience]

To be or not to be?

Thrilled to share our pQTL stories

head-to-head comparison of @SomaLogic and @OlinkProteomics for 871 proteins among 10k individuals @MRC_Epid

Bidirectional platform comparison for >2k pQTLs to guide genetic discovery

https://t.co/z4bAfuOE7m

🧵👇 (1/7)

[Karsten Suhre @ksuhre]

#AI meets #metabolomics: Variational autoencoders learn universal latent representations of #metabolomics data https://t.co/Szhnj4qf58 .. new pre-print from @JanKrumsiek Lab @EngIPM @WCMQatar

[[email protected] @cpsievert]

📢 I'm thrilled to share that shiny 1.6.0 is now on CRAN!
🎉

This release makes so much easier to create beautiful, performant, and accessible #rshiny #rstats apps.

https://t.co/OwRSkCbzKK

[Xiaole Shirley Liu @XShirleyLiu]

We created a GitHub for the Harvard STAT115/215 BIO/BST282 course: Introduction to Bioinformatics and Computational Biology. https://t.co/gFqsvywtxl. Most of it is based on the 2020 course material, which we will gradually update in spring 2021.

[Matthias Arnold @_MatthiasArnold]

On the occasion of SNiPA's 6th birthday, we released a new version at https://t.co/0nOfo9doyy. V3.4 features tons of additional eQTLs/pQTLs/mQLTs/traitQTLs, incl. the whole 2nd round of GWASs (pooled & sex-specific) from the UK Biobank (thanks to @bmneale's lab)! V4 coming soon..

[Maria Ulmer (née Wörheide) @mwoerhe]

Really happy to see our review (and the first paper of my PhD 🥳) 'Multi-omics integration in biomedical research – A #metabolomics-centric review' out!

Thank you to my amazing co-authors @JanKrumsiek, @KastenmullerLab,@_MatthiasArnold.

https://t.co/vPjBHAikTa

[Maximilian Ulmer @maxwulmer]

Pretty excited about this collaboration. Obstacle avoidance for robotic manipulators is a hard problem, especially on the basis of vision. Our approach allows a seamless integration of a learned policy while maintaining the responsiveness required for many critical tasks.

[Maria Ulmer (née Wörheide) @mwoerhe]

Exciting! Can't wait to check it out #Neo4j #NODES2020

[William Lyon @lyonwj]

The GDS 1.4 release includes new machine learning algorithms, graph embeddings, and introduces a new Pregel API so you can implement your own algorithms using #Neo4j infrastructure #NODES2020

Learn more about GDS here: https://t.co/xOZlKI7aCW

[Jan Krumsiek @JanKrumsiek]

Networks inferred via p-value cutoffs are often flawed, since they do not necessarily reflect biological reality. We analyze the problem and propose a new prior knowledge-driven approach in our latest Nature Communications paper https://t.co/C9N0V1QHMN

[Matthias Arnold @_MatthiasArnold]

Nice! Thanks to Anna and her team @Sagebio, the AD atlas is now directly accessible through the Agora platform of the @AMPADPortal!

Check it out at https://t.co/wb4YKZTEoP and https://t.co/4ODdFFYgsw.

[Maria Ulmer (née Wörheide) @mwoerhe]

@TweetwithQuinn @KastenmullerLab @_MatthiasArnold Thank you! That’s great to hear, looking forward to your feedback ☺️