David Fischer

Adapting systems biology to address the complexity of human disease in the single-cell era - Nature Reviews Genetics Differences between humans and experimental models create a translational gap that makes it difficult to extrapolate research findings. The authors review systems-focused approaches to identify and co...

Our featured article: Adapting systems biology to address the complexity of human disease in the single-cell era go.nature.com/3XBo6Vh #Review by @davidsebfischer.bsky.social, Martin A. Villanueva, Peter S. Winter & ‪@shaleklab.bsky.social‬ @broadinstitute.org @mit.edu @ragoninstitute.bsky.social

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Adapting systems biology to address the complexity of human disease in the single-cell era - Nature Reviews Genetics Differences between humans and experimental models create a translational gap that makes it difficult to extrapolate research findings. The authors review systems-focused approaches to identify and co...

This review is a product of a great team effort together with Martin Villanueva, Peter Winter and Alex Shalek! www.nature.com/articles/s41... & rdcu.be/ecTna

In summary, we outline how systems biology is being adapted to the multiscale dynamics of human health and disease in omics-driven as what is effectively a two-loop cycle over discovery and validation.

We review strategies that can manage this distance and dissect how it relates to understanding cellular systems at specific spatiotemporal scales - be it the cellular scale often considered in the context of single-cell-resolved experiments, or the tissue niche scale captured with spatial omics.

Both are needed to build quantitative models are faithful to human biology and validated through perturbation experiments. However, the usage of two distinct systems incurs a "translational distance" that complicates systems biology approaches that utilize information from the two.

In this review, we discuss how one can rationalize what information about a multiscale cellular system is actually captured by on omics study. We leverage that insight to describe how one can translate between discovery efforts in human tissues and validation efforts in experimental model systems.

However, the dynamics of human tissues in disease settings is multiscale - not only does that impact quantitative models, it also reflects in experimental design and the resources of publicly available data that we have access to. This obstructs attempts at building such quantitative models.

Currently, there's a lot of interest in quantitative models that would help us understand and predict features of the complex cellular systems that underlie human health and disease - think about virtual cells, for example. On can trace some of these ideas back to the early days of systems biology.

Programs, origins and immunomodulatory functions of myeloid cells in glioma - Nature A study of myeloid cells in gliomas, a type of brain tumour, used a factor-based computational framework to reveal four immunomodulatory gene-expression programs that are expressed across myeloid cell...

Proud to share our @nature.com paper, co-led by Chadi El Farran & Charles Couturier under mentorship of Brad Bernstein where we develop a new framework to understand immunomodulatory myeloid cells in #glioma & lay a foundation to develop more effective immunotherapies. www.nature.com/articles/s41...

Read about self-supervision in models of scRNA-seq data in this deep dive!

Exciting news! 🚀 The Learning Meaningful Representations of Life ( #LMRL 🌟) workshop is returning at #ICLR2025! 🎉

On 27th / 28th April 2025 in Singapore 🇸🇬, this popular event returns with a fresh organizing team 👇 & bold new ideas 🧠 to explore bridging AI & life sciences 🧬

Our ChromBPNet preprint out!

www.biorxiv.org/content/10.1...

Huge congrats to Anusri! This was quite a slog (for both of us) but we r very proud of this one! It is a long read but worth it IMHO. Methods r in the supp. materials. Bluetorial coming soon below 1/

What cellular & multicellular changes underpin aging of ovaries? We used spatial transcriptomics to study this process in mice, capturing dynamic changes in cells, follicles, and tissue across the estrous cycle. Read about the age-related changes in these dynamics we discovered!

Method of the Year 2024: spatial proteomics - Nature Methods Approaches for profiling the spatial proteome in tissues are the basis of atlas-scale projects that are delivering on their promise for understanding biological complexity in health and disease.

I could not be more thrilled to announce the Nature Methods @naturemethods.bsky.social Method of the Year is Spatial Proteomics! Please see our editorial as a roadmap to the fantastic content in this special issue! www.nature.com/articles/s41...

You are already in this one @jasmineplummer.bsky.social!

An integrated transcriptomic cell atlas of human neural organoids - Nature A human neural organoid cell atlas integrating 36 single-cell transcriptomic datasets shows cell types and states and estimates transcriptomic similarity between primary and organoid counterparts, sho...

Super excited to share our Human Neural Organoid Atlas, now out in Nature! Led by @zhisonghe.bsky.social @josch1.bsky.social, and myself, this resource was created from 36 scRNA-seq datasets—totalling over 1.7 million cells! 🔬✨
 www.nature.com/articles/s41...


Find out how it can serve you ⏬

🧵1/8

I think Pack 2 is up to 135/150 now, so between the two you can follow 285 bioml researchers in about 4 clicks!

To expedite the development of a network focussed on single-cell and spatial genomics on this platform, I started to collect accounts of scientists & groups that are broadly active in these fields. This is work in progress, DM if you want to be added or have suggestions!

go.bsky.app/HZTJxbZ

My goal is to understand the regulatory role of every nucleotide in the genome, and how this changes across every cell in the human body.

If you are interested in doing a Ph.D. with me at UMass Chan Medical (Genomics and Comp Bio Department), see the links below. Deadline is Dec 1st.

Two BioML starter packs now:

Pack 1: go.bsky.app/2VWBcCd
Pack 2: go.bsky.app/Bw84Hmc

DM if you want to be included (or nominate people who should be!)

What if we could look at a human tissue image🔬and quantify its biological age?🧬 And how could we get the same insights without collecting the tissue sample? In our new @biorxivpreprint, we create "tissue clocks" ⏳to do just that! www.biorxiv.org/content/10.1... 📝 #aging #tissue thread below⬇️