The article presents a systematic meta-algorithm for spawning and aggregating multi-class cryo-EM reconstruction jobs, formalizing iterative classification and filtering strategies used by practitioners. It claims to be the first method capable of ab initio reconstruction on datasets with dozens of distinct species, achieving 97% accuracy on a 45-class subset of Tomotwin-100 and 75% on the full dataset, and successfully recovering ribosomal assembly states from an unfiltered experimental cryo-EM dataset. The approach scales with compute resources and aims to underpin automated cryo-EM workflows in contemporary experimental settings.
By Alkin Kaz, Arda Kaz, Ellen D. Zhong
arXiv:2608.28838v1 Announce Type: cross
Abstract: Cryo-electron microscopy (cryo-EM) determines the structures of proteins and macromolecular assemblies at near-atomic resolution, and the final 3D re...
By Riku Itsuji, Yuanhao Wang, Xingjian Li, Seonghui Min, Hideo Saito, Min Xu
arXiv:2606. 10255v1 Announce Type: cross Abstract: Cryo-electron tomography (cryoET) has emerged as a powerful tool in structural and cellular biology by enabling direct visualization of macromolecular structures within intact cells, thereby linking molecular architecture to cellular organization in a native context.
By Jonathan Schwartz, Utz Heinrich Ermel, C. Braxton Owens, Zhuowen Zhao, Ariana Peck, Gus L. W. Hart, Grant J. Jensen, Bridget Carragher, Dari Kimanius
arXiv:2610.01358v1 Announce Type: cross
Abstract: Single-particle cryo-electron microscopy (cryo-EM) has become a widely adopted technique for biomolecular structure determination. The conventional c...
By Advaith Maddipatla, M\"art-Erik M\"aeots, Marco Pegoraro, Nikolaus Dr\"ager, Roberto Covino, Sanketh Vedula, Martin Pacesa, Alex M. Bronstein
arXiv:2606. 31332v1 Announce Type: new Abstract: Protein automodeling from cryo-EM density maps faces unique challenges in enforcing physicochemical validity and managing conformational heterogeneity.
By Minzhang Li, Mingrui Li, Weichen Qin, Qihe Chen, Sixian Shen, Yuan Pei, Jiakai Zhang, Jingyi Yu
arXiv:2510. 16165v2 Announce Type: replace Abstract: A key question in benchmarking generative crystal reconstruction models is how the amount and type of crystallographic information provided to a generative model affects its ability to reconstruct atomic structures.
By Charles Rhys Campbell, Aldo H. Romero, Kamal Choudhary
arXiv:2609.14097v1 Announce Type: cross
Abstract: Subtomogram classification in cryo-electron tomography (cryo-ET) is a challenging problem due to the scarcity of labeled examples. While cryo-ET simu...
By Siddhant Bharadwaj, Ashish Vashist, Rashi Singh, Pranav Vinodh, Nishanth Artham, Runmin Jiang, Xingjian Li, Min Xu
The paper introduces CARNIVAL, a model for protein annotation in cryo-electron tomography (cryo-ET) volumes that leverages simulated data and a forward model to generate domain‑specific augmented paired views for self‑supervised training. By incorporating simulation‑derived protein positions and identities into the architecture and loss function, the model localises semantic information at protein locations. CARNIVAL is evaluated on real tomograms without finetuning and outperforms a state‑of‑the‑art contrastive model that lacks forward‑model paired views or privileged information.
By Bogdan Toader, Kiarash Jamali, Tanmay A. M. Bharat, Sjors H. W. Scheres
arXiv:2605.21617v3 Announce Type: replace
Abstract: Locating genomic features from genomic contact maps, such as centromere identification from genome-wide chromosome conformation capture techniques,...
By Elo\"ise Touron, Pedro L. C. Rodrigues, Julyan Arbel, Nelle Varoquaux, Michael Arbel
Ambient Dataloops is an iterative framework that refines datasets to improve diffusion model training. By co‑evolving the dataset and the model, each iteration produces higher‑quality data while the model learns to handle slightly less noisy synthetic samples using Ambient Diffusion techniques. The approach achieves state‑of‑the‑art results in unconditional and text‑conditional image generation as well as de novo protein design, and the authors provide a theoretical justification for the benefits of the looping procedure.
By Adri\'an Rodr\'iguez-Mu\~noz, William Daspit, Adam Klivans, Antonio Torralba, Constantinos Daskalakis, Giannis Daras
arXiv:2606. 00955v1 Announce Type: new Abstract: Despite the growing availability of cryo-electron microscopy (cryo-EM) density maps, effectively leveraging them for protein representation remains challenging.
By Dan Luo, Xuan Lin, Peng Zhou, Junwen Zhu, Tengfei Ma, Xiangxiang Zeng, Yiping Liu
arXiv:2606. 05139v1 Announce Type: new Abstract: The rapid advancement of high-throughput sequencing has led to large, high-dimensional omics datasets.
By Luca Thale-Bombien, Jan Ewald, Ralf K\"onig, Aaron Klein