Simon Anders (@s_anders_m) profile picture

Bioinformatics/Biostatistics Researcher @simon_anders@mstdn.social

Heidelberg, Germany
Joined July 2016
Great thread by Anshul, one of the pioneers of deep learning for biology, summarizing our preprint!
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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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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/…
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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/…
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🎉 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 🧵👇
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… 🧵1/9
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And read the Research Briefing here: nature.com/articles/s41592-0…
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.@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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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
Physicist Suvrat Raju shared this letter he sent to an editor of Nature Communications, declining to referee for them.
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“Is Science Self-Correcting? Evidence from 5 Recent Papers on the Effect of Replications on Citations.” replicationnetwork.com/2023/…
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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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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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Life science postdoc positions in Heidelberg: health-life-sciences.de/post…
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Replying to @LPMKremer
@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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Proud to present this work by @LPMKremer, @SCerrizuela et al. from @molneurolab and our group:
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… 🧵1/9
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cellpypes - cell type pipes for R. Annotate scRNAseq data manually with simple rules:
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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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Just started using @TrostNils's R package for plotting 3D scatter points (and more). It's very convenient, powerful and useful.
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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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)
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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