Joined July 2016
- Tweets 94
- Following 137
- Followers 826
- Likes 288
Photos and videos
Simon Anders retweeted
Great thread by Anshul, one of the pioneers of deep learning for biology, summarizing our preprint!
21 Sep 2024
biorxiv.org/content/10.1101/…
Nice benchmark of single cell "foundation models" (scGPT, scFoundation) and GEARS (a GNN model) further hyped as "virtual cell models" against linear baselines on perturbation prediction.
Long-story short: they can't beat the linear baselines. 1/
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Simon Anders retweeted
This is the result of my brief postdoc with @s_anders_m in the last 6 months and grew out of an intriguing reviewer comment for the LEMUR paper with @wolfgangkhuber.
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Simon Anders retweeted
There's a lot of excitement about foundation models and their ability to learn biology 🧬💻
But current tools for perturbation prediction perform worse than simple linear models! We need more careful benchmarking to make progress.
biorxiv.org/content/10.1101/…
ALT Beeswarm plot of the double perturbation predictions. The Additive model outperforms GEARS, scGPT, and scFoundation by a large margin
ALT Line plot of the accuracy of the predictions that are most different from the additive model. The No Change model outperforms GEARS, scGPT, and scFoundation.
ALT Beeswarm plot of the single perturbation predictions. The linear model perform as good as GEARS, scGPT, and scFoundation.
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23 Sep 2024
New preprint from our group:
There's a lot of excitement about foundation models and their ability to learn biology 🧬💻
But current tools for perturbation prediction perform worse than simple linear models! We need more careful benchmarking to make progress.
biorxiv.org/content/10.1101/…
ALT Beeswarm plot of the double perturbation predictions. The Additive model outperforms GEARS, scGPT, and scFoundation by a large margin
ALT Line plot of the accuracy of the predictions that are most different from the additive model. The No Change model outperforms GEARS, scGPT, and scFoundation.
ALT Beeswarm plot of the single perturbation predictions. The linear model perform as good as GEARS, scGPT, and scFoundation.
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Simon Anders retweeted
5 Sep 2024
🎉 Excited to share our latest study in @nature, showing that DNA🧬 #methylation is key to stemness in the adult #brain: nature.com/articles/s41586-0…
A collaboration with @s_anders_m, driven by @LPMKremer and @SCerrizuela. #epigenetics #neuroscience #singlecell. Pre-print summary 🧵👇
ALT Top: Schematic depiction of genes involved in astrocyte function and neurogenesis, and their methylation and gene expression status in different cell states. Bottom: We propose that DNA methylation locks common parenchymal astrocytes in their astrocyte fate by repressing genes required for neurogenesis. By contrast, these genes are demethylated in NSCs, which permits their progression along the neurogenic lineage.
15 Jul 2022
We're excited to share our latest preprint where we use #singlecell #multiomics to show that stemness is encoded in the methylome of neural #stemcells (NSC) in the adult #brain 🐁🧠
#epigenetics #neuroscience #biorxiv_neursci
👉doi.org/10.1101/2022.07.13.4…
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Simon Anders retweeted
31 Jul 2024
And read the Research Briefing here:
nature.com/articles/s41592-0…
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Simon Anders retweeted
31 Jul 2024
.@LPMKremer, @molneurolab, @s_anders_m and colleagues introduce a data processing approach along with an easy-to-use software tool MethSCAn for scBS-seq data analysis.
nature.com/articles/s41592-0…
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Simon Anders retweeted
19 Sep 2023
We're so excited to share our latest work “Identification of astrocyte-driven pseudolineages reveals clinical stratification and therapeutic targets in #Glioblastoma” spearheaded by @OghuzhanKaya on the wet & @LCForst on the dry lab as a preprint @Biorxiv biorxiv.org/content/10.1101/…
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Simon Anders retweeted
3 Jun 2023
Physicist Suvrat Raju shared this letter he sent to an editor of Nature Communications, declining to referee for them.
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Simon Anders retweeted
13 Apr 2023
“Is Science Self-Correcting? Evidence from 5 Recent Papers on the Effect of Replications on Citations.”
replicationnetwork.com/2023/…
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Simon Anders retweeted
16 Mar 2023
Thanks chromatin community! We’ve been digging around in your repetitive DNA (>40,000 ChIP-seq samples) and have discovered a totally unexpected role for BRD4 and JQ1 at centromeres. Very happy to share our preprint. biorxiv.org/content/10.1101/…
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27 Feb 2023
PhD and postdoc postions for computational biologists, in the labs of @s_anders_m (me) and @molneurolab (A. Martin-Villalba): Single-cell omics methods in neurobiology. dkfz.de/en/neurobiologie-von…
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Simon Anders retweeted
13 Sep 2022
@LPMKremer presenting our latest study on epigenetic features of adult neural stem cells at #TCESRC22 on Sicily 🌅, organized by @BrunetLab and @giacomo_cavalli.
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15 Jul 2022
We're excited to share our latest preprint where we use #singlecell #multiomics to show that stemness is encoded in the methylome of neural #stemcells (NSC) in the adult #brain 🐁🧠
#epigenetics #neuroscience #biorxiv_neursci
👉doi.org/10.1101/2022.07.13.4…
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Simon Anders retweeted
13 Jun 2022
cellpypes - cell type pipes for R. Annotate scRNAseq data manually with simple rules:
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Simon Anders retweeted
26 May 2022
The current system of journals and peer review is not serving science. I have therefore resigned from all editorial roles and will no longer do pre-publication peer review. I explain why in this article and in the thread below. Please consider joining me.
neural-reckoning.org/reviewi…
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14 Apr 2022
Just started using @TrostNils's R package for plotting 3D scatter points (and more). It's very convenient, powerful and useful.
7 Nov 2020
babyplots - my tool for interactive 3D plots - is now available at bp.bleb.li! Available as a #JavaScript library, an #RStats package, a #PowerPoint add-in and as in interactive creator. Check out some examples: bp.bleb.li/viewer?p=E-WVj
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11 Apr 2022
A thread by @mikelove on best practices for QC before DGE analyses -- prompted by a recent paper claiming that edgeR, DESeq2 etc have spurious false positives (but only if you omit QC as he shows)
11 Apr 2022
Got an RNA-seq dataset with 50, 100, 200 samples? Plug it into a differential expression tool and hope for the best? No! You need to consider QC, EDA, and modeling technical variation, or else risk generating spurious results. A thread on papers, methods, and best practices:
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