Bioinformatics

Raw signal segmentation for estimating RNA modification from Nanopore direct RNA sequencing data

1. Guangzhao Cheng
2. Aki Vehtari
3. Lu Cheng

• Curated by eLife

  eLife Assessment

  This study presents SegPore, a valuable new method for processing direct RNA nanopore sequencing data, which improves the segmentation of raw signals into individual bases and boosts the accuracy of modified base detection. The evidence presented to benchmark SegPore is solid and the authors provide a fully documented implementation of the method. If updated to process newer RNA nanopore sequencing data types, SegPore will be of great interest to researchers studying RNA modifications.

Reviewed by eLife

Exploring the repository of de novo-designed bifunctional antimicrobial peptides through deep learning

1. Ruihan Dong
2. Rongrong Liu
3. Ziyu Liu
4. Yangang Liu
5. Gaomei Zhao
6. Honglei Li
7. Shiyuan Hou
8. Xiaohan Ma
9. Huarui Kang
10. Jing Liu
11. Fei Guo
12. Ping Zhao
13. Junping Wang
14. Cheng Wang
15. Xingan Wu
16. Sheng Ye
17. Cheng Zhu

• Curated by eLife

  eLife Assessment

  This study presents a useful pipeline for de novo design of antimicrobial peptides active both against bacteria and viruses. The method is based on deep learning, using a GAN generator and a regression tasked to predict antimicrobial activity. The experimental evidence supporting the conclusions is solid, with 24 validated peptides, although some additional justifications of the computational strategy would be a plus. This work will be of interest to the community working on machine learning for biomedical applications and specifically on antimicrobial peptides.

Reviewed by eLife

xRead: a coverage-guided approach for scalable construction of read overlapping graph

1. Tangchao Kong
2. Yadong Wang
3. Bo Liu

Reviewed by GigaScience

TransHLA: A Hybrid Transformer Model for HLA-Presented Epitope Detection

1. Tianchi Lu
2. Xueying Wang
3. Wan Nie
4. Miaozhe Huo
5. Shuaicheng Li

Reviewed by GigaScience

Distilling Structural Representations into Protein Sequence Models

1. Jeffrey Ouyang-Zhang
2. Chengyue Gong
3. Yue Zhao
4. Philipp Krähenbühl
5. Adam R. Klivans
6. Daniel J. Diaz

Reviewed by Arcadia Science

How Does Sampling Affect the AI Prediction Accuracy of Peptides’ Physicochemical Properties?

1. Meiru Yan
2. Ankeer Abuduhebaier
3. Haojin Zhou
4. Jiaqi Wang

Reviewed by PREreview

Permute-match tests: Detecting significant correlations between time series despite nonstationarity and limited replicates

1. Alex E Yuan
2. Wenying Shou

• Curated by eLife

  eLife Assessment

  This manuscript reports an important new statistical method for calculating the significance of correlations between two time-series, which provides more accuracy than other methods when the data has few replicates. The proposed method solves a real-life problem that is frequently encountered and is broadly applicable to many realistic datasets in many experimental contexts. The technique is supported with compelling mathematical derivations as well as analysis of both computer-generated and previously published experimental data.

Reviewed by eLife

Tidyplots empowers life scientists with easy code‐based data visualization

1. Jan Broder Engler

Reviewed by preLights

Untargeted pixel-by-pixel metabolite ratio imaging as a novel tool for biomedical discovery in mass spectrometry imaging

1. Huiyong Cheng
2. Dawson Miller
3. Nneka Southwell
4. Paola Porcari
5. Joshua L Fischer
6. Isobel Taylor
7. J Michael Salbaum
8. Claudia Kappen
9. Fenghua Hu
10. Cha Yang
11. Kayvan R Keshari
12. Steven S Gross
13. Marilena D'Aurelio
14. Qiuying Chen

• Curated by eLife

  eLife Assessment

  This valuable study describes a software package in R for visualizing metabolite ratio pairs. The evidence supporting the claims of the authors is solid and broadly supports the authors' conclusions. This work would be of interest to the mass spectrometry community.

Reviewed by eLife

Protein Language Model Fitness Is a Matter of Preference

1. Cade Gordon
2. Amy X. Lu
3. Pieter Abbeel

Reviewed by Arcadia Science