Bioinformatics

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysis

1. Xiao Li
2. Ximo Pechuan-Jorge
3. Tyler Risom
4. Conrad Foo
5. Alexander Prilipko
6. Artem Zubkov
7. Caleb Chan
8. Patrick Chang
9. Frank Peale
10. James Ziai
11. Sandra Rost
12. Derrek Hibar
13. Lisa McGinnis
14. Evgeniy Tabatsky
15. Xin Ye
16. Hector Corrada Bravo
17. Zhen Shi
18. Malgorzata Nowicka
19. Jon Scherdin
20. James Cowan
21. Jennifer Giltnane
22. Darya Orlova
23. Rajiv Jesudason

Reviewed by GigaScience

Predicting functional constraints across evolutionary timescales with phylogeny-informed genomic language models

1. Chengzhong Ye
2. Gonzalo Benegas
3. Carlos Albors
4. Jianan Canal Li
5. Sebastian Prillo
6. Peter D. Fields
7. Brian Clarke
8. Yun S. Song

Reviewed by Arcadia Science

Macroscopic Analyses of RNA-Seq Data to Reveal Chromatin Modifications in Aging and Disease

1. Achal Mahajan
2. Francesca Ratti
3. Ban Wang
4. Hana El-Samad
5. James H Kaufman
6. Vishrawas Gopalakrishnan

• Curated by eLife

  eLife Assessment

  This valuable study analyzes aging-related chromatin changes through the lens of intra-chromosomal gene correlation length, which is a novel computational metric that captures spatial correlations in gene expression along the chromosome. The authors propose that this metric reflects chromatin structure and can serve as a proxy for its changes during aging. While currently the strength of evidence is somewhat incomplete, if revised with further supporting data, this work will provide a systems-level understanding of aging and genome regulation, which is predicted to have a substantive impact on the field.

Reviewed by eLife

Restoring data balance via generative models of T cell receptors for antigen-binding prediction

1. Emanuele Loffredo
2. Mauro Pastore
3. Simona Cocco
4. Rémi Monasson

• Curated by eLife

  eLife Assessment

  This valuable study introduces a data augmentation approach based on generative unsupervised models to address data imbalance in immune receptor modeling. Support for the findings is solid, showing that the use of generated data increases the performance of downstream supervised prediction tasks, e.g., TCR-peptide interaction prediction. However, the validation, mainly relying on synthetic data, could be completed, especially regarding unseen epitopes, and given the exclusive focus on CDR3β. The results should be of interest to the communities working on immunology and biological sequence data analysis.

Reviewed by eLife

The Demodifier: A tool for screening modification-induced alternate peptide taxonomy in palaeoproteomics

1. Miranda Evans

Reviewed by Peer Community in Archaeology

Unbiased whole genome comparison of Pan paniscus (bonobo) and Homo sapiens (human) through a novel sequence match-based approach

1. Christof Rosler
2. Derick DuFriend
3. Evonn Annor
4. Rita Njoroge
5. Elena Davis
6. Ywahae Law Anthem
7. Celestino Velásquez
8. William P. Ranahan
9. Matthew H. Goelzer
10. Stephen Wheat
11. Julianna A. Goelzer

Reviewed by Arcadia Science

Uncovering Developmental Lineages from Single-cell Data with Contrastive Poincaré Maps

1. Nithya Bhasker
2. Hattie Chung
3. Louis Boucherie
4. Vladislav Kim
5. Stefanie Speidel
6. Melanie Weber

Reviewed by Arcadia Science

A Transparent and Generalizable Deep Learning Framework for Genomic Ancestry Prediction

1. Camille Rochefort-Boulanger
2. Matthew Scicluna
3. Raphaël Poujol
4. Jean-Christophe Grenier
5. Pierre Luc Carrier
6. Sébastien Lemieux
7. Julie G Hussin

Reviewed by Arcadia Science

ASPEN: Robust detection of allelic dynamics in single cell RNA-seq

1. Veronika Petrova
2. Muqing Niu
3. Thomas S. Vierbuchen
4. Emily S. Wong

Reviewed by Review Commons