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Markus List

@itisalist.bsky.social

Assistant Professor for Data Science in Systems Biology at the Technical University of Munich (http://daisybio.de). Mostly posting about bioinformatics and systems / network biology research. Views are my own. he / him.

33 Posts327 Follower543 Folgt
Markus List@itisalist.bsky.social · 2d ago

The last MOPITAS autumn school in Garching was a lot of fun, great participants and great instructors. I'm really looking forward to join this second installment in Copenhagen. Don't miss the deadline and sign up if your interested in taking your spatial data analysis to the next level. Vi ses i DK!

Stegle Lab@steglelab.bsky.social · 2d ago

📅 Register by August 16th: event.sdu.dk/mopitas2026/... Looking forward to welcoming you to Copenhagen, together with Richard Röttger, Jakub Sedzinski, @itisalist.bsky.social, @oliverstegle.bsky.social and all the rest of the MOPITAS team.

DaiSyBio@daisybio.de · last mo.

🚀 Great news from DaiSyBio: our new manuscript, “Inferring and Evaluating Network Medicine-Based Disease Modules with Nextflow”, has been published in Bioinformatics (Oxford) as part of the ISMB 2026 proceedings.

DaiSyBio@daisybio.de · 2mo ago

📅 Join the upcoming Munich Data Science Institute (MDSI) research talk of Francesca Finotello on Wednesday, 24 June 2026 at 01:00 pm at the MDSI in Garching. 🔗 Further information on the talk and the registration can be found on the MDSI website. www.mdsi.tum.de/mdsi/bildung...

Research Talk: Decoding tissue complexity via deconvolution of transcriptomic data

The investigation of the cellular composition and architecture of tissues is key to understanding mechanisms that underlie tissue function and its disruption during disease. Deconvolution is a computa...

mdsi.tum.de

DaiSyBio@daisybio.de · 2mo ago

Yesterday, we took part in the Weihenstephaner Berglauf 2025 and enjoyed much better weather than at the last Campus Lauf. 🏃‍♂️‍➡️🏃‍♀️‍➡️

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DaiSyBio@daisybio.de · 3mo ago

🚀 Excited to share that our latest publication, "Drugst.One DREAM, Drug Repurposing through Expert Annotation and Modification" is now published in the British Journal of Pharmacology.

DaiSyBio@daisybio.de · 4mo ago

Amazing news from DaiSyBio! As the first official DaiSyBio PhD student, Alexander Dietrich successfully defended his thesis, “Advanced Methods for Cellular Composition Inference from Bulk Molecular Profiles,” on February 24th and, as of yesterday, can officially be called Dr. Dietrich.

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DaiSyBio@daisybio.de · 4mo ago

Today @fabiantheis.bsky.social has been visiting the campus of the TUM School of Life Sciences for giving an inspiring TUM Life Science Talk. We fully share his view that the decades-old vision of systems biology is finally within our reach. Exciting times ahead!

Lecture hall showing the talk of Prof. Fabian Theis and the audience.
DaiSyBio@daisybio.de · 4mo ago

🚀 New publication from the MOPITAS project Very happy to share our latest publication in Briefings in Bioinformatics, presenting a benchmarking and analysis platform for spatial transcriptomics simulations.

Markus List@itisalist.bsky.social · 5mo ago

I really enjoyed our DyHealthNet.ai workshop in Erlangen this week. It was especially amazing to meet our IHEC collaborator @guillaumebourque.bsky.social in person again after many years!

DyHealthNet

DyHealthNet is a DFG-funded research project run by FAU (Biomedical Network Science Lab), TUM (Big Data in Biomedicine Group), Eurac (Institute for Biomedicine), and UNIBZ (Database Systems Group).

dyhealthnet.ai

DaiSyBio@daisybio.de · 5mo ago

Productive discussions at the DyHealthNet workshop in Erlangen ✨ 📅 🧠 🧬

DaiSyBio@daisybio.de · 5mo ago

✨ Call for abstracts for the "AI and Bioinformatics" satellite workshop at the 55th Annual Meeting of the German Society for Immunology ✨

Markus List@itisalist.bsky.social · 7mo ago

On Wednesday, @rnakato.bsky.social gave an excellent talk in our new @tum.de Life Science Talks series: www.ls.tum.de/en/ls/public.... It was nice to see so many people join to hear about the role of multi-omics data in elucidating gene-regulatory mechanisms. Well done @rnakato.bsky.social

New lecture series: TUM Life Science Talks foster interdisciplinary discourse

New lecture series: TUM Life Science Talks in Freising-Weihenstephan promote exchange with renowned scientists.

ls.tum.de

Christina Steidele@steidele.bsky.social · 8mo ago

My barley transcriptional network preprint is officially out! Started as my Bachelor’s thesis — now it’s online: doi.org/10.64898/202... Huge thanks to @itisalist.bsky.social, @daisybio.de, @huckelhovenr.bsky.social , Felix Hoheneder & Johannes Kersting for all their help and support!

Network Inference Reveals Distinct Transcriptional Regulation in Barley against Drought and Fusarium Head Blight

We analyzed transcriptional networks in barley under single and combined Fusarium head blight (FHB) and drought stress. We applied complementary Weighted Gene Correlation Network Analysis (WGCNA) to i...

doi.org

DaiSyBio@daisybio.de · 8mo ago

One of our students, EliasAlbrecht, went the extra mile in his project and created an educational 3D-printed model of a nucleosome. We're stunned by the level of detail and excited to use this in our lectures and public events. The model is open to the community makerworld.com/en/models/20...

Histone Display by user_506892605 MakerWorld: Download Free 3D Models

This is a histone display that illustrates a nucleosome. The DNA is wrapped around a histone octamer consisting of H3, H4, H2A, and H2B. The model includes methylated cytosines, as well as histone tai...

makerworld.com

Markus List@itisalist.bsky.social · last yr.

🧬🖥️Drug response prediction is a machine learning challenge with immense potential for precision medicine. Our latest preprint introduces DrEval, a comprehensive benchmarking framework to evaluate state-of-the-art methods, uncover widespread issues, and guide the development of more robust models.

Judith Bernett@judith-bernett.bsky.social · last yr.

🧬🖥️So excited to show you the outcome of @pascivers.bsky.social and my latest project: "From Hype to Health Check: Critical Evaluation of Drug Response Prediction Models with DrEval" doi.org/10.1101/2025.05.26.655288, published with M. Picciani, M. Wilhelm, K. Baum & @itisalist.bsky.social. 🧵1/10

Overview of the DrEval framework. Via input options, implemented state-of-the-art models can be compared against baselines of varying complexity. We address obstacles to progress in the field at each point in our pipeline: Our framework is available on PyPI and nf-core and we follow FAIReR standards for optimal reproducibility. DrEval is easily extendable as demonstrated here with a pseudocode implementation of a proteomics-based random forest. Custom viability data can be preprocessed with CurveCurator, leading to more consistent data and metrics. DrEval supports five widely used datasets with application-aware train/test splits that enable detecting weak generalization. Models are free to use provided or custom cell line– and drug features. The pipeline supports randomization-based ablation studies and performs robust hyperparameter tuning for all models. Evaluation is conducted using meaningful, bias-resistant metrics to avoid inflated results from artifacts such as Simpson’s paradox. All results are compiled into an interactive HTML report. Created in https://BioRender.com.