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Success Stories

Real research breakthroughs achieved with AI-powered cell annotation

Discover how leading researchers worldwide are using mLLMCelltype to accelerate their discoveries and publish groundbreaking results.

500+

Research Labs

Worldwide

50M+

Cells Annotated

Successfully

95%

Accuracy Rate

Average

200+

Publications

Enabled

Featured Success Stories

🦠 Immunology

⭐ 5.0

Discovering Rare T-Cell Populations in COVID-19

👩‍🔬

Dr. Sarah Chen

Stanford Immunology Lab

Used mLLMCelltype to identify 3 novel T-cell subtypes crucial for long-term COVID-19 immunity, leading to a high-impact publication.

85K Cells

23 Cell Types

95% Accuracy

"mLLMCelltype identified rare T-cell populations we completely missed with traditional methods. This discovery led to our Nature publication."

🧠 Neuroscience

⭐ 4.9

Mapping Brain Cell Diversity in Organoids

👨‍🔬

Prof. Michael Rodriguez

MIT Neuroscience

Characterized 23 distinct neuronal subtypes in human cortical organoids, mapping developmental trajectories with 92% accuracy.

120K Cells

23 Subtypes

92% Accuracy

"The multi-model consensus approach provided unprecedented accuracy in neuronal subtype identification."

🎗️ Cancer Research

⭐ 4.8

Tumor Microenvironment Analysis

👩‍⚕️

Dr. Lisa Wang

Johns Hopkins Oncology

Revealed novel immune cell interactions in breast cancer tumors, identifying potential therapeutic targets for immunotherapy.

200K Cells

31 Cell Types

94% Accuracy

"The detailed immune cell characterization opened new avenues for personalized cancer treatment."

Research Areas

🦠

Immunology

T-cell characterization, immune response mapping, vaccine development

🧠

Neuroscience

Brain organoids, neuronal diversity, developmental biology

🎗️

Cancer Research

Tumor microenvironment, metastasis, drug resistance

🫀

Cardiology

Heart development, cardiac repair, disease modeling

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