Bioinformatics

Bayesian Inference of Dependent Population Dynamics in Coalescent Models

1. Lorenzo Cappello
2. Jaehee Kim
3. Julia Palacios

Reviewed by ScreenIT

Predictions of immunogenicity reveal potent SARS-CoV-2 CD8+ T-cell epitopes

1. David Gfeller
2. Julien Schmidt
3. Giancarlo Croce
4. Philippe Guillaume
5. Sara Bobisse
6. Raphael Genolet
7. Lise Queiroz
8. Julien Cesbron
9. Julien Racle
10. Alexandre Harari

Reviewed by ScreenIT

Using unsupervised learning algorithms to identify essential genes associated with SARS-CoV-2 as potential therapeutic targets for COVID-19

1. Golnaz Taheri
2. Mahnaz Habibi

Reviewed by ScreenIT

Unsupervised outlier detection applied to SARS-CoV-2 nucleotide sequences can identify sequences of common variants and other variants of interest

1. Georg Hahn
2. Sanghun Lee
3. Dmitry Prokopenko
4. Jonathan Abraham
5. Tanya Novak
6. Julian Hecker
7. Michael Cho
8. Surender Khurana
9. Lindsey R. Baden
10. Adrienne G. Randolph
11. Scott T. Weiss
12. Christoph Lange

Reviewed by ScreenIT

AI-based search for convergently expanding, advantageous mutations in SARS-CoV-2 by focusing on oligonucleotide frequencies

1. Toshimichi Ikemura
2. Yuki Iwasaki
3. Kennosuke Wada
4. Yoshiko Wada
5. Takashi Abe

Reviewed by ScreenIT

Systematic lncRNA mapping to genome-wide co-essential modules uncovers cancer dependency on uncharacterized lncRNAs

1. Ramkrishna Mitra
2. Clare M Adams
3. Christine M Eischen

• Curated by eLife

  Evaluation Summary:

  Mitra et al. developed an analysis framework using large-scale pan-cancer omics datasets to discover the roles of 30 long non-coding RNAs (lncRNAs) in cancer proliferation and growth. Direct function-testing experiments were also performed to validate the biological mechanisms of two lncRNAs. The analysis framework developed here can serve as a resource to study the functions of lncRNA in cancer, and the computational framework can also be further extended to study cancer-relevant transcriptional and post-transcriptional regulation.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their name with the authors.)

Reviewed by eLife

Systematic analysis of alternative splicing in time course data using Spycone

1. Chit Tong Lio
2. Gordon Grabert
3. Zakaria Louadi
4. Amit Fenn
5. Jan Baumbach
6. Tim Kacprowski
7. Markus List
8. Olga Tsoy

Reviewed by ScreenIT

Ligand Binding Prediction Using Protein Structure Graphs and Residual Graph Attention Networks

1. Mohit Pandey
2. Mariia Radaeva
3. Hazem Mslati
4. Olivia Garland
5. Michael Fernandez
6. Martin Ester
7. Artem Cherkasov

Reviewed by ScreenIT

Faster SARS-CoV-2 sequence validation and annotation for GenBank using VADR

1. Eric P Nawrocki

Reviewed by ScreenIT

Read2Tree: scalable and accurate phylogenetic trees from raw reads

1. David Dylus
2. Adrian Altenhoff
3. Sina Majidian
4. Fritz J Sedlazeck
5. Christophe Dessimoz

Reviewed by ScreenIT