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AI-HEAD: Auto-indexing for Helical assembles' diffraction and fast dynamic structure determination

Pei, T.; Yu, M.; Li, S.; Zhang, D.; Sun, F.; Zhang, Y.

2025-11-18 biophysics
10.1101/2025.11.17.688965 bioRxiv
Show abstract

Analyzing the structure of the helical assembly is very important to excavate the mechanism of base life activities such as cell morphology maintaining, cargo transportation, et. al. However, the structure determination of helical assembles still challenging due to ambiguous of helical parameters. Here, we developed automatic, fast and accurate helical parameter and structure calculation method AI-HEAD, which perform diffraction indexing and parameter calculation automatically in seconds, and determine the final structure unambiguously by sorting parameters semi-automatically. AI-HEAD is open source and also provides a user-friendly graphical interface.

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The top 6 journals account for 50% of the predicted probability mass.

1
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16
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236 papers in training set
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1.7%
17
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18
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Top 16%
1.4%
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20
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1.4%
21
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22
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◐ 12 papers in training set
Top 0.1%
0.8%
27
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.