Bioinformatics

Weakly supervised learning uncovers phenotypic signatures in single-cell data

1. Anastasia Litinetskaya
2. Soroor Hediyeh-zadeh
3. Amir Ali Moinfar
4. Mohammad Lotfollahi
5. Fabian J. Theis

Reviewed by Arcadia Science

A network regularized linear model to infer spatial expression pattern for single cell

1. Chaohao Gu
2. Hu Chen
3. Zhandong Liu

• Curated by eLife

  eLife Assessment

  The development of glmSMA represents a valuable advancement in spatial transcriptomics analysis, offering a mathematically robust regression-based approach that achieves higher-resolution mapping of single-cell RNA sequencing data to spatial locations than existing methods. The evidence is convincing, as the authors demonstrate the method's superiority by formulating it as a convex optimization problem that ensures stable solutions, coupled with successful validation across multiple biological systems. The rigorous mathematical framework and validation across diverse tissues enable precise spatial mapping of cellular heterogeneity at enhanced resolution.

Reviewed by eLife

Rehabilitating the benefits of gene tree correction in the presence of incomplete lineage sorting

1. Manuel Lafond
2. Celine Scornavacca

Reviewed by Peer Community in Evolutionary Biology

Time-resolved phylogenomics analysis reveals patterns in biosphere nutrient limitation through Earth history

1. Zhanghan Ni
2. Troy Osborn
3. Juntao Zhong
4. Adrian Gonzalez
5. Will Puzella
6. Aya Klos
7. Bryan Le
8. Alec Leonetti
9. Joanne S Boden
10. Eva E Stueeken
11. Rika E Anderson

Reviewed by Arcadia Science

Direct Comparative Analyses of 10X Genomics Chromium and Smart-Seq2

1. Xiliang Wang
2. Yao He
3. Qiming Zhang
4. Xianwen Ren
5. Zemin Zhang

Reviewed by PREreview

pyRootHair: Machine learning accelerated software for high-throughput phenotyping of plant root hair traits

1. Ian Tsang
2. Lawrence Percival-Alwyn
3. Stephen Rawsthorne
4. James Cockram
5. Fiona Leigh
6. Jonathan A Atkinson

Reviewed by GigaScience

EMImR: a Shiny application for identifying transcriptomic and epigenomic changes

1. Hiba Ben Aribi
2. Careen Naitore
3. Farah Ayadi
4. Souheila Guerbouj
5. Olaitan I. Awe

• Curated by GigaByte

  Editors Assessment:

  Coded and written up as part of the African Society for Bioinformatics and Computational Biology (ASBCB) Omicscodeathons, EMImR is a novel Shiny application for transcriptomic and epigenomic change identification and correlation wrapped up using a combination of Bioconductor and CRAN packages. Case studies are on publicly available GEO data corresponding to sequencing data of human blood cell samples of multiple sclerosis patients to demonstrate how the tool works. And a documentation and videos are provided. Peer review and the study highlighting the usefulness of the developed tool for analyzing transcriptomic and epigenomic data.

  This evaluation refers to version 1 of the preprint

Reviewed by GigaByte

Deciphering chromatin architecture and dynamics in Plasmodium falciparum using the nucDetective pipeline

1. Simon Holzinger
2. Leo Schmutterer
3. Victoria Marie Rothe
4. Maria Theresia Watzlowik
5. Uwe Schwartz
6. Gernot Längst

Reviewed by Review Commons

MAVISp : A modular structure‐based framework for protein variant effects

1. Matteo Arnaudi
2. Mattia Utichi
3. Kristine Degn
4. Matteo Tiberti
5. Ludovica Beltrame
6. Karolina Krzesińska
7. Pablo Sánchez‐Izquierdo Besora
8. Eleni Kiachaki
9. Simone Scrima
10. Laura Bauer
11. Katrine Meldgård
12. Anna Melidi
13. Lorenzo Favaro
14. Anu Oswal
15. Guglielmo Tedeschi
16. Terézia Dorčaková
17. Alberte Heering Estad
18. Joachim Breitenstein
19. Jordan Safer
20. Paraskevi Saridaki
21. Valentina Sora
22. Francesca Maselli
23. Philipp Becker
24. Jérémy Vinhas
25. Alberto Pettenella
26. Matteo Lambrughi
27. Claudia Cava
28. Anna Rohlin
29. Mef Nilbert
30. Sumaiya Iqbal
31. Peter Wad Sackett
32. Burcu Aykac Fas
33. Elena Papaleo

Reviewed by Review Commons

Identification and classification of ion channels across the tree of life provide functional insights into understudied CALHM channels

1. Rahil Taujale
2. Sung Jin Park
3. Nathan Gravel
4. Saber Soleymani
5. Rayna Carter
6. Kennady Boyd
7. Sarah I Keuning
8. Zheng Ruan
9. Wei Lü
10. Natarajan Kannan

• Curated by eLife

  eLife Assessment

  In this manuscript Taujale et al describe an interdisciplinary approach to mine the human channelome and further discover orthologues across diverse organisms. Further, this work provides evidence that supports a role for conserved residues in CALHM channel gating. Overall this important work presents findings that can be helpful to the ion channel community, as well as to those interested in improved methods for mining sequence space for their protein of interest. However, further validation of the improvements their approach shows over previous approaches is needed, making this a solid contribution to the literature in this field.

Reviewed by eLife