Chris Sander aka cscbio
@sandercbio
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Do science that is predictive and use it to improve lives.
Boston, MA
Joined March 2009
Postdocs: Sander Lab, Systems Biology, Harvard Medical School. Data Science / AI / CompBio. Solve challenging biological problems. (1) Catch cancer early using AI #CancerRiskNet #ovariancancer
https://t.co/8ymjGpEyxA - Apply to sander.research (gmail) Subj: postdoc application
hms.harvard.edu
An AI tool identified people at the highest risk for pancreatic cancer up to three years before actual diagnosis.
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Announcing our new protein design server https://t.co/uu4co1sHhq: • End-to-end protein design for everyone! • Analyze your generated library interactively and on 3D structures • Export codon-optimized DNA sequences for experimental testing. Developed in collaboration
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Protein design with almost-AI -- evolution does it
"Simultaneous enhancement of multiple functional properties using evolution-informed protein design" Novel b-lactamases designed w/ EVCouplings; "functional designs had large increases in thermostability and most had a broadening of available substrates" https://t.co/d7xgJUECDa
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Read and think !
Happy to be part of the process to develop AI recommendations for UofT. I encourage everyone interested in AI policy to read the report.
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Things get better in science over time with good starting ideas and subsequent hard work. 2016 Evolutionary Couplings for RNA folding. 2025 Comprehensive RNA benchmark and tool comparison for everyone in the biomolecular AI field. Great team work with MarksLab!
RNA, RNA, RNA https://t.co/jFLAofp63p Been a long time goal of @deboramarks.bsky.social to help RNA sequence —> function mapping a million years ago we tried https://t.co/xAnwxeC7Jo Now total refresh for our new world, led by Rohit Arora and Murphy Angelo for seeing this
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How can we use #GenerativeAI for #ProteinDesign? - check out work from our labs @deboramarks and @yaringal
https://t.co/mPxqX5TWxd
nature.com
Nature Biotechnology - Notin, Rollins and colleagues discuss advances in computational protein design with a focus on redesign of existing proteins.
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The February issue, with a focus on protein engineering, is live https://t.co/5zL1A8zf3S Our cover shows the three data types key to machine learning for functional protein design: structure, sequence and labels, from a Review by Notin et al. https://t.co/ZgfK6N0LD7
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A first step toward designing combo anticipatory vaccines !
Previous viral evolution can shed light on future immune evasion. EVEscape, now out in @Nature, is our first step in applying pre-pandemic data to forecast antibody escape through the course of a pandemic. https://t.co/9jE1oaAX6T 🧵1/6
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Looks like I was able to re-purpose ChatGPT's new function return support to enrich answers about human genes using the most up-to-date @genenames data. This still has too much boilerplate stuff in it but here is the full notebook for the curious: https://t.co/dQFXaafqvh
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Postdocs: Sander Lab, Systems Biology, Harvard Medical School. Data Science, AI, CompBio. Solve challenging biological problems. (2) Develop large-scale models of cell biology https://t.co/3YHpBWW3ao
https://bit/ly/CellBox Apply: sander.research (gmail) Subj: postdoc application
wellcomeleap.org
$55M PROGRAM Delta Tissue Delta Tissue: Integrated Platforms for Predicting Changes in Tissue State, is a $55 million effort that brings experts in the life sciences and engineering together from...
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More to come in international open collaboration #CancerRiskNet aka #BianQue << Solve Bo Yuan’s puzzle.
(1/6) Very excited to share our work on @NatureMedicine using #AI to predict #cancer with disease history only (no CT scan!). Glad to co-lead the work with @davplacido @jessicaxhu Chunlei Zheng @sandercbio @TheBrunakLab and many more great colleagues https://t.co/vEY2eOUN4A .
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AI Predicts Future Pancreatic Cancer
hms.harvard.edu
An AI tool identified people at the highest risk for pancreatic cancer up to three years before actual diagnosis.
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Risk of pancreatic cancer predicted using machine learning. International collaboration. @TheBrunakLab @DanaFarber_Hale @harvardmed @HMS_SysBio @GENES_PK @Nrfillmore @boyuan_data @davplacido @deboramarks @sandercbio
https://t.co/7hUonsEeUG
nature.com
Nature Medicine - A deep learning algorithm using electronic health records from two large cohorts of patients predicts the risk of pancreatic cancer from pre-cancer disease trajectories up to...
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Ready to learn about protein design? Our beginner's guide breaks down this complex field into easy-to-understand concepts. Discover the potential of proteins to transform our world: https://t.co/OGrrvh0BnR
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Go cBioPortal ! Lots of new features for easy analytic access to cancer genomics, proteomics and more. Make your own discoveries on community-provided cancer data and analysis tools.
Come learn about cBioPortal at #AACR2023: Talks on Saturday by @NikolausSchultz at 8:30 AM in Room W224 (#NCIITCR session) as well as by Tali Mazor in Room W311 at 8:45 AM (@AACR Project GENIE session), a poster on Tuesday morning, and a booth in the exhibitor space (#1943).
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Wish one could weigh in with NNF to reverse this decision. Very hard to understand. Our collaborations with CPR labs Mann and Brunak have been singularly successful. Great science & scientists.
Tremendously sad day for Danish science as Novo Nordisk Foundation is closing its flagship protein research institute, arguably the best in the world. @UCPH_CPR has been a beacon of science and progress for years. Let's cherish the remaining years & strive to continue the legacy.
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Very pleased to announce that our paper “Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval” was accepted at ICML! Paper: https://t.co/tgpUs90sLz Repo: https://t.co/XHCNwcPL26 (1/10)
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https://t.co/qCCSe23b6O is recruiting an Associate Lab Director! An outstanding opportunity for an ambitious computational biologist to manage projects at the cutting edge of machine learning and genomics. Send CV to deboramarkslab@gmail.com
deboramarkslab.com
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Harvard link
https://t.co/qCCSe23b6O is recruiting an Associate Lab Director! An outstanding opportunity for an ambitious computational biologist to manage projects at the cutting edge of machine learning and genomics. Send CV to deboramarkslab@gmail.com
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Connecting theoretical physics and biology; and genotype to phenotype! - Wishing you all the best in Barcelona.
It is happening! @Jonnygfrazer and I are starting our group at @CRGenomica this Autumn! We will be developing deep generative models to map genetic variation to phenotypic change. Super excited!
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