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New scCycleMol framework predicts cell-cycle changes in drug response

By PulseAugur Editorial · [1 sources] ·

Researchers have developed scCycleMol, a novel framework designed to predict drug perturbation responses in single-cell data, with a specific focus on cell-cycle awareness. This model goes beyond predicting transcriptional changes to also forecast alterations in a cell's proliferative state. By incorporating cell-cycle supervision, scCycleMol demonstrates improved out-of-distribution expression prediction compared to existing baselines on a large benchmark dataset. AI

IMPACT This framework could enhance the accuracy of drug response predictions in biological research by accounting for cell-cycle dynamics.

RANK_REASON The cluster describes a new computational framework and its evaluation on a benchmark dataset, fitting the definition of research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New scCycleMol framework predicts cell-cycle changes in drug response

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The cluster describes a new computational framework and its evaluation on a benchmark dataset, fitting the definition of research. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Dingping Zhao, Jie Lin ·

    Modeling Cell-Cycle-Aware Single-Cell Drug Perturbation Responses

    arXiv:2606.30695v1 Announce Type: cross Abstract: Single-cell drug perturbation models should predict not only transcriptional response magnitude, but also whether a treatment alters the proliferative state of a cell. This is challenging because cell-cycle variation is often trea…

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