Bioinformatics

Genetic, metabolic, and molecular insights into the diverse outcomes of diet-induced obesity in mice

1. Alexis Maximilien Bachmann
2. Jean-David Morel
3. Gaby El Alam
4. Sandra Rodríguez-López
5. Tanes Imamura de lima
6. Ludger J.E. Goeminne
7. Giorgia Benegiamo
8. Maroun Bou Sleiman
9. Johan Auwerx

• Curated by eLife

  Evaluation Summary:

  In the present study, Bachmann and Morel et al., report a comprehensive survey of metabolic phenotypes and liver outcomes (gene expression, complex activities) in a unique subset of genetically diverse mouse strains. The authors focus on sex- and diet-dependent effects where notable differences are observed. These data will be a useful reference source for those interested in diet effects on metabolic phenotypes across various inbred mouse strains.

  (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. The reviewers remained anonymous to the authors.)

Reviewed by eLife

Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains

1. Premnath Madanagopal
2. Harshini Muthukumar
3. Kothai Thiruvengadam

Reviewed by ScreenIT

Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization

1. Gabriel Renaud
2. Maibritt Nørgaard
3. Johan Lindberg
4. Henrik Grönberg
5. Bram De Laere
6. Jørgen Bjerggaard Jensen
7. Michael Borre
8. Claus Lindbjerg Andersen
9. Karina Dalsgaard Sørensen
10. Lasse Maretty
11. Søren Besenbacher

• Curated by eLife

  Evaluation Summary:

  This work describes a shallow WGS sequencing approach (<1x) for genome‐wide cell‐free DNA fragmentation analysis using non-negative matrix factorization (NMF). The concept of utilizing 'fragmentomics' as an early cancer detection tool is a subject of intense investigation and there have been multiple recent publications in the field. This work adds an interesting unsupervised approach.

  (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 agreed to share their name with the authors.)

Reviewed by eLife

EMoMiS: A Pipeline for Epitope-based Molecular Mimicry Search in Protein Structures with Applications to SARS-CoV-2

1. Vitalii Stebliankin
2. Prabin Baral
3. Christian Balbin
4. Janelle Nunez-Castilla
5. Masrur Sobhan
6. Trevor Cickovski
7. Ananda Mohan Mondal
8. Jessica Siltberg-Liberles
9. Prem Chapagain
10. Kalai Mathee
11. Giri Narasimhan

Reviewed by ScreenIT

Machine learning-based approach KEVOLVE efficiently identifies SARS-CoV-2 variant-specific genomic signatures

1. Dylan Lebatteux
2. Hugo Soudeyns
3. Isabelle Boucoiran
4. Soren Gantt
5. Abdoulaye Baniré Diallo

Reviewed by ScreenIT

Comprehensive analysis of next-generation sequencing data in COVID-19 and its secondary complications

1. Muttanagouda Giriyappagoudar
2. Basavaraj Vastrad
3. Rajeshwari Horakeri
4. Chanabasayya Vastrad

Reviewed by ScreenIT

Sentinel Cards Provide Practical SARS-CoV-2 Monitoring in School Settings

1. Victor J. Cantú
2. Karenina Sanders
3. Pedro Belda-Ferre
4. Rodolfo A. Salido
5. Rebecca Tsai
6. Brett Austin
7. William Jordan
8. Menka Asudani
9. Amanda Walster
10. Celestine G. Magallanes
11. Holly Valentine
12. Araz Manjoonian
13. Carrissa Wijaya
14. Vinton Omaleki
15. Stefan Aigner
16. Nathan A. Baer
17. Maryann Betty
18. Anelizze Castro-Martínez
19. Willi Cheung
20. Peter De Hoff
21. Emily Eisner
22. Abbas Hakim
23. Alma L. Lastrella
24. Elijah S. Lawrence
25. Toan T. Ngo
26. Tyler Ostrander
27. Ashley Plascencia
28. Shashank Sathe
29. Elizabeth W. Smoot
30. Aaron F. Carlin
31. Gene W. Yeo
32. Louise C. Laurent
33. Anna Liza Manlutac
34. Rebecca Fielding-Miller
35. Rob Knight

Reviewed by ScreenIT

ImmunoTyper-SR: A computational approach for genotyping immunoglobulin heavy chain variable genes using short-read data

1. Michael K.B. Ford
2. Ananth Hari
3. Oscar Rodriguez
4. Junyan Xu
5. Justin Lack
6. Cihan Oguz
7. Yu Zhang
8. Andrew J. Oler
9. Ottavia M. Delmonte
10. Sarah E. Weber
11. Mary Magliocco
12. Jason Barnett
13. Sandhya Xirasagar
14. Smilee Samuel
15. Luisa Imberti
16. Paolo Bonfanti
17. Andrea Biondi
18. Clifton L. Dalgard
19. Stephen Chanock
20. Lindsey B. Rosen
21. Steven M. Holland
22. Helen C. Su
23. Luigi D. Notarangelo
24. Kerry Dobbs
25. Elana Shaw
26. Miranda F. Tompkins
27. Camille Alba
28. Adelani Adeleye
29. Samuel Li
30. Jingwen Gu
31. Uzi Vishkin
32. Corey T. Watson
33. S. Cenk Sahinalp

Reviewed by ScreenIT

Mapping the Evolutionary Space of SARS-CoV-2 Variants to Anticipate Emergence of Subvariants Resistant to COVID-19 Therapeutics

1. Roberth Anthony Rojas Chávez
2. Mohammad Fili
3. Changze Han
4. Syed A. Rahman
5. Isaiah G. L. Bicar
6. Sullivan Gregory
7. Annika Helverson
8. Guiping Hu
9. Benjamin W. Darbro
10. Jishnu Das
11. Grant D. Brown
12. Hillel Haim

Reviewed by ScreenIT

Design and development of potent h-ACE2 derived peptide mimetics in SARS-CoV-2 Omicron variant therapeutics

1. M. L. Stanly Paul
2. Swathi Nadendla
3. M Elizabeth Sobhia

Reviewed by ScreenIT