ClusterChirp is a freely available web tool for scalable interactive visualization, hierarchical clustering, and natural-language-guided analysis of high-dimensional omics datasets.
Kuleshov, Matthew R
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SynthPert fine-tunes LLMs using synthetic reasoning traces to reach state-of-the-art on the PerturbQA benchmark for cellular perturbation prediction, surpassing the generating frontier model while generalizing to unseen cell types with only 2% of filtered data.
Systematic benchmarking shows existing transcriptomic predictors for immune checkpoint inhibitor response have limited cross-cohort generalisability and inconsistent biomarker signals.
citing papers explorer
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ClusterChirp: Scalable Interactive Exploration of Omics Data with Natural Language-Guided Analysis
ClusterChirp is a freely available web tool for scalable interactive visualization, hierarchical clustering, and natural-language-guided analysis of high-dimensional omics datasets.
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SynthPert: Enhancing LLM Biological Reasoning via Synthetic Reasoning Traces for Cellular Perturbation Prediction
SynthPert fine-tunes LLMs using synthetic reasoning traces to reach state-of-the-art on the PerturbQA benchmark for cellular perturbation prediction, surpassing the generating frontier model while generalizing to unseen cell types with only 2% of filtered data.
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Transcriptomic Models for Immunotherapy Response Prediction Show Limited Cross-cohort Generalisability
Systematic benchmarking shows existing transcriptomic predictors for immune checkpoint inhibitor response have limited cross-cohort generalisability and inconsistent biomarker signals.