mapping gene networks to enable network-based therapeutic discovery in cardiovascular disease

Joined September 2022
18 Photos and videos
Happy to share a protocol for discovery of candidate therapeutic targets with Geneformer by @YujieZh1729! Nature Protocols link: rdcu.be/ffApo Google Colab: tinyurl.com/geneformertutori…
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Really enjoyed talking with science journalist Andrew Han about art and science on his new podcast, Ion Genomics! Check it out here: iongenomics.bio/p/podcast-ep…
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Excited to share MaxToki, a temporal AI model that predicts the impact of perturbations on cell states over time along dynamic trajectories. We applied MaxToki to predict how cells age across the human lifespan & discovered new cardiac pro-aging drivers that we validated in vivo.
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Thank you to the whole team for their wonderful collaboration on this work! Javier Gόmez Ortega, @alexis_combes, @andcyang, @StefanieDimmel1, Shinya Yamanaka, @m_alexanian, @NVIDIAHealth
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Congrats to @hanimal725 and @madhavanvvs for their work in Nature Computational Science that demonstrated scaling laws for foundation models for network biology and implemented a quantization approach to enable resource-efficient predictions! rdcu.be/famFk

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Thank you to the whole team on this collaboration: Javier Gómez Ortega, @Sid_Mahesh_12, Tarak Nandi, @madduri, and @PelkaLab!
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We are excited to share work led by @hanimal725 and @madhavanvvs developing a quantized multitask learning strategy for network biology, built on a foundation model pretrained on ~95M single-cell transcriptomes. Manuscript: tinyurl.com/qmtl-gf Model: huggingface.co/ctheodoris/Ge…
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Overall, quantized multi-task learning enables resource-efficient context-specific modeling in gene network biology to yield contextual predictions of key network regulators and candidate therapeutic targets for human disease.
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Thank you to the whole team for the wonderful collaboration! Javier Gómez Ortega, @Sid_Mahesh_12, Tarak Nandi, @madduri, and @PelkaLab! x.com/TheodorisLab/status/18…

We are excited to share work led by @hanimal725 and @madhavanvvs developing a quantized multitask learning strategy for network biology, built on a foundation model pretrained on ~95M single-cell transcriptomes. Manuscript: tinyurl.com/qmtl-gf Model: huggingface.co/ctheodoris/Ge…
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