Bioinformatics

Hecatomb: An End-to-End Research Platform for Viral Metagenomics

1. Michael J. Roach
2. Sarah J. Beecroft
3. Kathie A. Mihindukulasuriya
4. Leran Wang
5. Anne Paredes
6. Kara Henry-Cocks
7. Lais Farias Oliveira Lima
8. Elizabeth A. Dinsdale
9. Robert A. Edwards
10. Scott A. Handley

Reviewed by GigaScience

ntsm: an alignment-free, ultra low coverage, sequencing technology agnostic, intraspecies sample comparison tool for sample swap detection

1. Justin Chu
2. Jiazhen Rong
3. Xiaowen Feng
4. Heng Li

Reviewed by GigaScience

MDverse, shedding light on the dark matter of molecular dynamics simulations

1. Johanna KS Tiemann
2. Magdalena Szczuka
3. Lisa Bouarroudj
4. Mohamed Oussaren
5. Steven Garcia
6. Rebecca J Howard
7. Lucie Delemotte
8. Erik Lindahl
9. Marc Baaden
10. Kresten Lindorff-Larsen
11. Matthieu Chavent
12. Pierre Poulain

• Curated by eLife

  eLife assessment

  The study presents a valuable tool for searching molecular dynamics simulation data, making such datasets accessible for open science. The authors provide convincing evidence that it is possible to identify noteworthy molecular dynamics simulation datasets and that their analysis can produce information of value to the community.

Reviewed by eLife

Circulating small extracellular vesicle RNA profiling for the detection of T1a stage colorectal cancer and precancerous advanced adenoma

1. Li Min
2. Fanqin Bu
3. Jingxin Meng
4. Xiang Liu
5. Qingdong Guo
6. Libo Zhao
7. Zhi Li
8. Xiangji Li
9. Shengtao Zhu
10. Shutian Zhang

• Curated by eLife

  eLife assessment

  This study presents a useful description of RNA in extracellular vesicles (EV-RNAs) and highlights the potential to develop biomarkers for the early detection of colorectal cancer (CRC) and precancerous adenoma (AA). The data were analysed using overall solid methodology and would benefit from further validation of predicted lncRNAs and biomarker validation at each stage of CRC/AA to evaluate the potential application to early detection of CRC and AA.

Reviewed by eLife

GTalign: Spatial index-driven protein structure alignment, superposition, and search

1. Mindaugas Margelevičius

Reviewed by Arcadia Science

Identification of type 2 diabetes- and obesity-associated human β-cells using deep transfer learning

1. Gitanjali Roy
2. Rameesha Syed
3. Olivia Lazaro
4. Sylvia Robertson
5. Sean D. McCabe
6. Daniela Rodriguez
7. Alex M. Mawla
8. Travis S. Johnson
9. Michael A. Kalwat

• Curated by eLife

  eLife assessment

  This is a useful study that used DEGAS, a deep transfer learning tool, to identify distinct pancreatic beta cell subpopulations that could be associated with type 2 diabetes (T2D) and/or obesity status. The data supporting the authors' findings is solid and demonstrates that DEGAS will be a helpful tool for analyzing cell-specific transcriptomic phenotypes. This study will be of interest to researchers studying the genetics of T2D.

Reviewed by eLife

Robust virtual staining of landmark organelles

1. Ziwen Liu
2. Eduardo Hirata-Miyasaki
3. Soorya Pradeep
4. Johanna Rahm
5. Christian Foley
6. Talon Chandler
7. Ivan Ivanov
8. Hunter Woosley
9. Tiger Lao
10. Akilandeswari Balasubramanian
11. Rita Marreiros
12. Chad Liu
13. Manu Leonetti
14. Ranen Aviner
15. Carolina Arias
16. Adrian Jacobo
17. Shalin B. Mehta

Reviewed by Arcadia Science

Prediction of anti-freezing proteins from their evolutionary profile

1. Nishant Kumar
2. Shubham Choudhury
3. Nisha Bajiya
4. Sumeet Patiyal
5. Gajendra P. S. Raghava

Reviewed by Arcadia Science

PSAURON: a tool for assessing protein annotation across a broad range of species

1. Markus J. Sommer
2. Aleksey V. Zimin
3. Steven L. Salzberg

Reviewed by Arcadia Science

Combining DNA and protein alignments to improve genome annotation with LiftOn

1. Kuan-Hao Chao
2. Jakob M. Heinz
3. Celine Hoh
4. Alan Mao
5. Alaina Shumate
6. Mihaela Pertea
7. Steven L Salzberg

Reviewed by Arcadia Science