Bioinformatics

PathoFact 2.0: An Integrative Pipeline for Predicting Antimicrobial Resistance Genes, Virulence Factors, Toxins and Biosynthetic Gene Clusters in Metagenomes

1. Júlia Ortís Sunyer
2. Luis F. Delgado
3. Oskar Hickl
4. Cedric C. Laczny
5. Patrick May
6. Paul Wilmes

Reviewed by GigaScience

FEDRANN: effective long-read overlap detection based on dimensionality reduction and approximate nearest neighbors

1. Jia-Yuan Zhang
2. Changjiu Miao
3. Teng Qiu
4. Junyi He
5. Wenqi Cao
6. Wei Lin
7. Xiaoshuang Xia
8. Lei He
9. Chunlei Yang
10. Yuhui Sun
11. Tao Zeng
12. Yuxiang Li
13. Xun Xu
14. Yijun Ruan
15. Yuliang Dong

Reviewed by GigaScience

METRIN-KG: A knowledge graph integrating plant metabolites, traits, and biotic interactions

1. Disha Tandon
2. Tarcisio Mendes De Farias
3. Pierre-Marie Allard
4. Emmanuel Defossez

Reviewed by GigaScience

DUAL: deep unsupervised simultaneous simulation and denoising for cryo-electron tomography

1. Xiangrui Zeng
2. Yizhe Ding
3. Yueqian Zhang
4. Mostofa Rafid Uddin
5. Ali Dabouei
6. Min Xu

• Curated by eLife

  eLife Assessment

  This important study presents a computational framework inspired by cycleGAN that enables denoising and realistic simulation of cryo-electron tomography data, addressing central challenges in tomogram cleaning, simulation, and downstream annotation. The approach coherently links several key problems in the field and demonstrates strong performance across benchmark datasets, with additional benefits for particle detection and missing-wedge completion, indicating broad relevance across electron tomography. The evidence is solid, with appropriate quantitative benchmarks and applications to diverse datasets supporting the main claims, although validation on additional, more recent tomograms would further strengthen the conclusions.

Reviewed by eLife

TSvelo: Comprehensive RNA velocity by modeling the cascade of gene regulation, transcription and splicing

1. Jiachen Li
2. Zhe Wang
3. Hong-Bin Shen
4. Ye Yuan

• Curated by eLife

  eLife Assessment

  This study presents a valuable RNA velocity method which predicts the transcription rate linearly based on the expression of RNA levels of transcription factors with addition of comprehensive analyses. The evidence supporting the claims of the authors is solid, although inclusion of a full simulation would have strengthened the study. The work will be of interest to scientists working in the field of RNA biology and precision medicine.

Reviewed by eLife

Celldetective, an AI-enhanced image analysis tool for unraveling dynamic cell interactions

1. Rémy Torro
2. Beatriz Díaz-Bello
3. Dalia El Arawi
4. Ksenija Dervanova
5. Lorna Ammer
6. Florian Dupuy
7. Patrick Chames
8. Kheya Sengupta
9. Laurent Limozin

• Curated by eLife

  eLife Assessment

  CellDetective is an important software package for segmentation, tracking, and analysis of time-lapse microscopy datasets, specifically designed to be accessible to researchers without coding expertise. The authors provide convincing evidence of its capabilities through comprehensive validations and well-executed comparisons across immunological assays, and the latest version adds support for defining and visualizing multiple cell subsets. The current implementation remains limited to 2D widefield imaging, though the authors provide a sound rationale for this scope, and one interface issue (a fixed main-window size on some systems) still affects usability. Overall, this work will be of significant interest to the bioimaging community, especially those in immunology and cell biology, and has applicability extending well beyond immune profiling.

Reviewed by eLife

TopoMetry systematically learns and evaluates the latent geometry of single-cell data

1. David Sidarta-Oliveira
2. Ana I Domingos
3. Licio A Velloso

• Curated by eLife

  eLife Assessment

  This important study presents a theoretically grounded framework for dimensionality reduction in single-cell RNA sequencing data, utilizing the principles of Riemannian manifolds. The proposed method addresses a critical challenge in bioinformatics-extracting highly informative latent dimensions without relying on the heuristic assumptions common in existing workflows. The evidence supporting the method's utility in estimating intrinsic dimensionality and identifying cell types is convincing, though the work would benefit from more rigorous validation against established ground truths and a clearer strategy for addressing prevalent batch effects.

Reviewed by eLife

TissueFormer: Extending single-cell foundation models to predict population-level phenotypes

1. Ari S. Benjamin
2. Anthony Zador

Reviewed by PREreview

Sample-level modeling of single-cell data at scale with tinydenseR

1. Pedro Milanez-Almeida
2. Daniela Schildknecht
3. Markus Linder
4. Saskia M. Brachmann
5. Andreas Weiss
6. Flavia Adler
7. Sofia Cardoni Lenticchia
8. Morgane Meistertzheim
9. Sophia Wild
10. Rachel Cuttat
11. Pushpa Jayaraman
12. Lang Ho Lee
13. Tanya Mulvey
14. Nadia Hassounah
15. Gina Crafts
16. David S. Quinn
17. Elena J. Orlando

Reviewed by Review Commons

Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2

1. Markus Hoffmann
2. Lina-Liv Willruth
3. Alexander Dietrich
4. Hye Kyung Lee
5. Ludwig Knabl
6. Nico Trummer
7. Jan Baumbach
8. Priscilla A. Furth
9. Lothar Hennighausen
10. Markus List

Reviewed by Rapid Reviews Infectious Diseases