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PhenixCraft pipeline enhances cryo-EM density map segmentation using AlphaFold

By PulseAugur Editorial · [1 sources] ·

Researchers have developed PhenixCraft, an automated pipeline designed to improve the process of building atomic models from cryo-electron microscopy (cryo-EM) density maps. This new method integrates predictions from AlphaFold to enhance the map-segmentation step within the existing Phenix software. The pipeline aims to overcome challenges presented by noise and artifacts, demonstrating improved performance in TM-scores and sequence accuracy compared to traditional Phenix model building. AI

IMPACT Enhances atomic model building from cryo-EM data by integrating AI predictions, potentially accelerating biological research.

RANK_REASON This is a research paper detailing a new method for a specific scientific task. [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 →

PhenixCraft pipeline enhances cryo-EM density map segmentation using AlphaFold

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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Chenwei Zhang ·

    Enhancing Cryo-EM Density Map Segmentation in Phenix for Improved Atomic Model Building

    arXiv:2605.05259v1 Announce Type: cross Abstract: We introduce PhenixCraft, a fully automated pipeline for building atomic models from cryo-EM density maps. By integrating AlphaFold predictions, we enhance the map-segmentation step in Phenix during model building, addressing chal…

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