Ann Huang @_annhuang

i like science and cats. bioinformatics @xaira_thera linkedin.com/in/ac-huang/ Joined September 2020

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CZI Science @cziscience

2 weeks ago

New to virtual cells? @freethink’s primer explains these AI-powered, in silico models—why they’re game-changers for biology & the hurdles still to solve. Worth a read bit.ly/4ljre1j

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In the wake of all the Bio x AI updates, I'm also here to spread awareness of important cat-related research. Isparta et al analyzed 400+ cat videos and found that cats favor the leftward side (p < 0.001), allowing for fast response to stimuli. Paper: cell.com/current-biolog…

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Zhiliang @Zhiliang_Bai

3 months ago

We are looking for talented postdocs/visiting students to join our team @MITdeptofBE and @kochinstitute to innovate spatial multi-omics technologies, map clinical samples, and integrate AI/ML models to advance next-generation cancer immunotherapy. Please help to spread!!

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Ann Huang @_annhuang

2 months ago

Such an exciting initiative. Congrats to all those involved! Hope people put the X-Atlas/Orion dataset to use 💪

Arc Institute @arcinstitute

2 months ago

Such an exciting initiative. Congrats to all those involved! Hope people put the X-Atlas/Orion dataset to use 💪

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XairaTherapeutics @Xaira_Thera

3 months ago

Today, we're releasing the fuel for the next generation of AI in biology 🧬 X-Atlas/Orion is now the largest public genome-wide Perturb-seq dataset, built to create better “virtual cell” models and accelerate drug discovery. Learn more: businesswire.com/news/home/2025…

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Ann Huang @_annhuang

a year ago

Excited to share that we are emerging from stealth mode today! Stay tuned for updates as we use AI to transform the drug discovery process

XairaTherapeutics @Xaira_Thera

a year ago

Excited to share that we are emerging from stealth mode today! Stay tuned for updates as we use AI to transform the drug discovery process

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Simona Cristea @simocristea

3 years ago

I am often asked by scientists across fields for advice & resources on how to get started with #scRNAseq analyses I summarize here such an analysis into a flowchart with 9 core steps. Analyzing your own scRNAseq data today is more accessible than ever And it gets even easier🧵