This page shows the most relevant public items for Bioinformatics, ranked by trend activity and review signal. Use weekly for fast changes, monthly for more stable patterns, and all-time for evergreen picks.
Paper • Feb 18, 2026 • bioRxiv • The GHIST Consortium, J. Pool, M. Gutenkunst
Inferring complex evolutionary and demographic histories from genomic data is plagued by model misspecification and unconscious bias. We report the results of the 2026 Genomic History Inference Str...
Paper • Feb 18, 2026 • bioRxiv • Elena K. Sharma, David Chen, Marcus Thorne, Yujin Han
A critical bottleneck in training autonomous agents for biology is the scarcity of high-throughput experimental data for reward modeling. We introduce rbio1, a framework that trains scientific reas...
Paper • Feb 10, 2026 • bioRxiv • Eduardo da Veiga Beltrame
This paper presents a systematic benchmark of architectural hyperparameters for variational autoencoder (VAE) methods in single-cell RNA-seq batch integration. The study compares scVI, MrVI, and LD...
Paper • Feb 23, 2026 • bioRxiv • Zhang, X., Jeong, E., Yan, C., Feng, Y., Lyu, L., Guo, X., Chen, Y.
CellAwareGNN is a new graph neural network (GNN) foundation model that integrates single-cell enhanced knowledge graphs for drug indication prediction. By modeling the complex relationships between...
Paper • Feb 23, 2026 • bioRxiv • E. A. Baker, N. S. Mehaffy
This study presents a pan-cancer analysis that identifies driver mutations by analyzing the composition and signaling of the tumor microenvironment. The authors validated their cross-platform infer...
Paper • Feb 23, 2026 • bioRxiv • Liu Chuanyang, Jiyuan Liu, Xinyuan Qiu, Xiaomin Wu, Wenying Li, Lu Min, Guohao Zhang, Shaowei Zhang, Lingyun Zhu
The paper explores how universal physical laws dictate the folding and assembly of proteins, challenging the stochastic views of structural formation. The authors argue that protein genesis follows...
Paper • Feb 14, 2026 • bioRxiv • Albert Jimenez-Blanco, et al.
Sequence-to-graph alignment is a cornerstone of modern pangenomics, yet current optimal algorithms suffer from high memory and computational costs. We present Theseus, a novel, fast, and optimal af...
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